User login
Isolating asymptomatic C. diff carriers slashes hospital-acquired infections
Screening asymptomatic patients admitted through the emergency department for occult Clostridium difficile infection, then isolating those found to be carriers throughout their hospital stay, substantially reduced the incidence of hospital-acquired C. difficile infection in a tertiary acute-care hospital, according to a report published online April 25 in JAMA Internal Medicine.
In what investigators described as the first study to assess the benefit of such an intervention, the Quebec Heart and Lung Institute (QHLI) in Quebec City went from being endemic for C. difficile infection to having the lowest incidence among 22 academic hospitals across the province of Quebec. “If confirmed in subsequent studies, isolating asymptomatic carriers could potentially prevent thousands of cases of hospital-acquired C. difficile infection every year in North America,” said Dr. Yves Longtin of the infection prevention and control unit at Jewish General Hospital, Montreal, and his associates.
The QHLI implemented the screen-and-isolate program because, despite robust infection-control efforts, it continued to exceed the government-imposed target level of 9.0 C. difficile infections per 10,000 patient-days. The program, which involved 7,599 patients admitted to the facility through its ED during a 17-month period, called for rectal sampling with a sterile swab, using a polymerase chain reaction (PCR) assay to detect the tcdB gene, obtaining the results within 24 hours, and isolating any carriers for the remainder of their stay. A total of 368 asymptomatic patients (4.8%) were found to be carriers.
Before the intervention, the hospital’s monthly incidence averaged 8.2 cases per 10,000 patient-days, with a high of 28.6 cases per 10,000 patient-days during an epidemic. After the intervention was implemented, the monthly incidence dropped to 3.0 per 10,000 patient-days. The hospital exceeded target levels of cases in 24.4% of the months preceding the intervention, compared with none of the months afterward. The investigators calculated that only 121 patients needed to be screened and 6 asymptomatic carriers needed to be isolated to prevent 1 case of hospital-acquired C. difficile infection.
During the same time period, rates of C. difficile infection remained stable at other hospitals across the province, Dr. Longtin and his associates said (JAMA Intern Med. 2016 Apr 25. doi: 10.1001/jamainternmed.2016.0177).
“The intervention may be effective not only by preventing direct patient-to-patient transmission but also by limiting contamination of the hospital environment,” they noted.
The study was supported by the Quebec Heart and Lung Institute, the Quebec Ministry of Health and Social Services, and the Quebec Foundation for Health Research. Dr. Longtin reported being a coapplicant on a patent for methods, reagents, and kits for the assessment of bacterial infections. His associates reported ties to Sanofi Pasteur, Merck, and Otsuka.
Until now, there were no data to determine whether interventions targeting asymptomatic carriers could reduce hospital-acquired C. difficile infection, so these findings are particularly encouraging. But the feasibility of expanding such programs on a larger scale must be carefully considered.
None of the commercially available PCR assays for diagnosing C. difficile has been approved by the Food and Drug Administration for detection in asymptomatic carriers. In addition, screening all patients admitted through the ED is labor and resource intensive, particularly in view of the high cost of PCR assays, and private rooms for isolation may not be available. Moreover, isolation can cause patients anxiety and depression, especially if it is long-term.
Perhaps targeting the highest-risk patients for screening and isolation would be helpful. Patients at high risk for shedding C. difficile spores (such as those who have a history of the infection or who have recently used antibiotics) and patients admitted to high-risk wards such as the ICU may be a good starting point.
Dr. Alice Y. Guh and Dr. L. Clifford McDonald are with the division of healthcare quality promotion at the U.S. Centers for Disease Control and Prevention, Atlanta. They reported having no relevant financial disclosures. Dr. Guh and Dr. McDonald made these remarks in an invited commentary (JAMA Intern Med. 2016 Apr 25. doi: 10.1001/jamainternmed.2016.1118) accompanying Dr. Longtin’s report.
Until now, there were no data to determine whether interventions targeting asymptomatic carriers could reduce hospital-acquired C. difficile infection, so these findings are particularly encouraging. But the feasibility of expanding such programs on a larger scale must be carefully considered.
None of the commercially available PCR assays for diagnosing C. difficile has been approved by the Food and Drug Administration for detection in asymptomatic carriers. In addition, screening all patients admitted through the ED is labor and resource intensive, particularly in view of the high cost of PCR assays, and private rooms for isolation may not be available. Moreover, isolation can cause patients anxiety and depression, especially if it is long-term.
Perhaps targeting the highest-risk patients for screening and isolation would be helpful. Patients at high risk for shedding C. difficile spores (such as those who have a history of the infection or who have recently used antibiotics) and patients admitted to high-risk wards such as the ICU may be a good starting point.
Dr. Alice Y. Guh and Dr. L. Clifford McDonald are with the division of healthcare quality promotion at the U.S. Centers for Disease Control and Prevention, Atlanta. They reported having no relevant financial disclosures. Dr. Guh and Dr. McDonald made these remarks in an invited commentary (JAMA Intern Med. 2016 Apr 25. doi: 10.1001/jamainternmed.2016.1118) accompanying Dr. Longtin’s report.
Until now, there were no data to determine whether interventions targeting asymptomatic carriers could reduce hospital-acquired C. difficile infection, so these findings are particularly encouraging. But the feasibility of expanding such programs on a larger scale must be carefully considered.
None of the commercially available PCR assays for diagnosing C. difficile has been approved by the Food and Drug Administration for detection in asymptomatic carriers. In addition, screening all patients admitted through the ED is labor and resource intensive, particularly in view of the high cost of PCR assays, and private rooms for isolation may not be available. Moreover, isolation can cause patients anxiety and depression, especially if it is long-term.
Perhaps targeting the highest-risk patients for screening and isolation would be helpful. Patients at high risk for shedding C. difficile spores (such as those who have a history of the infection or who have recently used antibiotics) and patients admitted to high-risk wards such as the ICU may be a good starting point.
Dr. Alice Y. Guh and Dr. L. Clifford McDonald are with the division of healthcare quality promotion at the U.S. Centers for Disease Control and Prevention, Atlanta. They reported having no relevant financial disclosures. Dr. Guh and Dr. McDonald made these remarks in an invited commentary (JAMA Intern Med. 2016 Apr 25. doi: 10.1001/jamainternmed.2016.1118) accompanying Dr. Longtin’s report.
Screening asymptomatic patients admitted through the emergency department for occult Clostridium difficile infection, then isolating those found to be carriers throughout their hospital stay, substantially reduced the incidence of hospital-acquired C. difficile infection in a tertiary acute-care hospital, according to a report published online April 25 in JAMA Internal Medicine.
In what investigators described as the first study to assess the benefit of such an intervention, the Quebec Heart and Lung Institute (QHLI) in Quebec City went from being endemic for C. difficile infection to having the lowest incidence among 22 academic hospitals across the province of Quebec. “If confirmed in subsequent studies, isolating asymptomatic carriers could potentially prevent thousands of cases of hospital-acquired C. difficile infection every year in North America,” said Dr. Yves Longtin of the infection prevention and control unit at Jewish General Hospital, Montreal, and his associates.
The QHLI implemented the screen-and-isolate program because, despite robust infection-control efforts, it continued to exceed the government-imposed target level of 9.0 C. difficile infections per 10,000 patient-days. The program, which involved 7,599 patients admitted to the facility through its ED during a 17-month period, called for rectal sampling with a sterile swab, using a polymerase chain reaction (PCR) assay to detect the tcdB gene, obtaining the results within 24 hours, and isolating any carriers for the remainder of their stay. A total of 368 asymptomatic patients (4.8%) were found to be carriers.
Before the intervention, the hospital’s monthly incidence averaged 8.2 cases per 10,000 patient-days, with a high of 28.6 cases per 10,000 patient-days during an epidemic. After the intervention was implemented, the monthly incidence dropped to 3.0 per 10,000 patient-days. The hospital exceeded target levels of cases in 24.4% of the months preceding the intervention, compared with none of the months afterward. The investigators calculated that only 121 patients needed to be screened and 6 asymptomatic carriers needed to be isolated to prevent 1 case of hospital-acquired C. difficile infection.
During the same time period, rates of C. difficile infection remained stable at other hospitals across the province, Dr. Longtin and his associates said (JAMA Intern Med. 2016 Apr 25. doi: 10.1001/jamainternmed.2016.0177).
“The intervention may be effective not only by preventing direct patient-to-patient transmission but also by limiting contamination of the hospital environment,” they noted.
The study was supported by the Quebec Heart and Lung Institute, the Quebec Ministry of Health and Social Services, and the Quebec Foundation for Health Research. Dr. Longtin reported being a coapplicant on a patent for methods, reagents, and kits for the assessment of bacterial infections. His associates reported ties to Sanofi Pasteur, Merck, and Otsuka.
Screening asymptomatic patients admitted through the emergency department for occult Clostridium difficile infection, then isolating those found to be carriers throughout their hospital stay, substantially reduced the incidence of hospital-acquired C. difficile infection in a tertiary acute-care hospital, according to a report published online April 25 in JAMA Internal Medicine.
In what investigators described as the first study to assess the benefit of such an intervention, the Quebec Heart and Lung Institute (QHLI) in Quebec City went from being endemic for C. difficile infection to having the lowest incidence among 22 academic hospitals across the province of Quebec. “If confirmed in subsequent studies, isolating asymptomatic carriers could potentially prevent thousands of cases of hospital-acquired C. difficile infection every year in North America,” said Dr. Yves Longtin of the infection prevention and control unit at Jewish General Hospital, Montreal, and his associates.
The QHLI implemented the screen-and-isolate program because, despite robust infection-control efforts, it continued to exceed the government-imposed target level of 9.0 C. difficile infections per 10,000 patient-days. The program, which involved 7,599 patients admitted to the facility through its ED during a 17-month period, called for rectal sampling with a sterile swab, using a polymerase chain reaction (PCR) assay to detect the tcdB gene, obtaining the results within 24 hours, and isolating any carriers for the remainder of their stay. A total of 368 asymptomatic patients (4.8%) were found to be carriers.
Before the intervention, the hospital’s monthly incidence averaged 8.2 cases per 10,000 patient-days, with a high of 28.6 cases per 10,000 patient-days during an epidemic. After the intervention was implemented, the monthly incidence dropped to 3.0 per 10,000 patient-days. The hospital exceeded target levels of cases in 24.4% of the months preceding the intervention, compared with none of the months afterward. The investigators calculated that only 121 patients needed to be screened and 6 asymptomatic carriers needed to be isolated to prevent 1 case of hospital-acquired C. difficile infection.
During the same time period, rates of C. difficile infection remained stable at other hospitals across the province, Dr. Longtin and his associates said (JAMA Intern Med. 2016 Apr 25. doi: 10.1001/jamainternmed.2016.0177).
“The intervention may be effective not only by preventing direct patient-to-patient transmission but also by limiting contamination of the hospital environment,” they noted.
The study was supported by the Quebec Heart and Lung Institute, the Quebec Ministry of Health and Social Services, and the Quebec Foundation for Health Research. Dr. Longtin reported being a coapplicant on a patent for methods, reagents, and kits for the assessment of bacterial infections. His associates reported ties to Sanofi Pasteur, Merck, and Otsuka.
FROM JAMA INTERNAL MEDICINE
Key clinical point: Screening asymptomatic patients admitted through the ED for occult C. difficile infection and isolating them throughout their hospital stay substantially reduced the incidence of hospital-acquired C. difficile.
Major finding: 121 patients needed to be screened and 6 asymptomatic carriers needed to be isolated to prevent 1 case of hospital-acquired C. difficile infection.
Data source: A controlled quasi-experimental study comparing rates of C. difficile infection at a single hospital during a 1.5-year period before and after an infection-control program was implemented.
Disclosures: This study was supported by the Quebec Heart and Lung Institute, the Quebec Ministry of Health and Social Services, and the Quebec Foundation for Health Research. Dr. Longtin reported being a coapplicant on a patent for methods, reagents, and kits for the assessment of bacterial infections. His associates reported ties to Sanofi Pasteur, Merck, and Otsuka.
Stigma Keeps Some Cancer Patients from getting Palliative Care
(Reuters Health) - Some cancer patients may turn down care that could ease their pain and improve their quality of life because they think this type of "palliative" treatment amounts
to giving up and simply waiting to die, a small Canadian study suggests.
Even though the World Health Organization recommends early palliative care for patients living with any serious illness, negative attitudes among patients and family caregivers often lead them to reject this option, researchers note in the Canadian Medical Association Journal.
"Patients and caregivers in our study saw palliative care as being equated with death, loss of hope, dependency, and going into places you never get out of again," said lead study author Dr. Camilla Zimmermann, head of the division of palliative care at the University Health Network in Toronto.
"This is in stark contrast with the actual definition of palliative care, which is interdisciplinary care that provides quality of life for patients with any serious illness and their families, and that is provided throughout the course of the illness rather than only at the end of life," Zimmermann added by email.
Zimmermann and colleagues interviewed 48 cancer patients and 23 of their family caregivers in cases when life expectancy was six to 24 months.
The researchers randomly assigned 26 patients to receive palliative care in addition to standard cancer care, while another 22 patients had only standard care.
Twenty-two patients in the palliative care group and 20 in the control group were receiving chemotherapy.
Over four months, patients in the palliative care group had at least monthly palliative care clinic visits, while those in the standard care group didn't receive any formal interventions. Caregivers could attend clinic visits for the palliative care participants, but they weren't required to do so.
Patients were typically in their early to mid 60s. Most were married and had at least some education beyond high school.
Most family caregivers were spouses, but a few were children or other relatives.
Initial perceptions of palliative care were similar in both groups - patients generally thought this was done only for the dying. While patients in both groups thought of palliative care
as providing comfort, they also associated it with giving up on treatment.
Once some patients received palliative care, however, their thinking shifted. Some patients now saw this as a way to live life to the fullest despite the terminal diagnosis, while others
suggested that doctors might have better luck renaming this as something other than "palliative care."
Calling palliative care providers "pain specialists" because they treat discomfort and focus on quality of life would make this sound more appealing and less frightening, some patients
said after getting this type of care.
But in the control group, without any experience with palliative care during the study, patients didn't see the point of renaming it because they thought it would still carry the stigma of giving up and waiting to die.
"Palliative care should not be framed as a last resort option," said Dr. Anthony Caprio, a geriatrician and hospice and palliative medicine physician at Carolinas HealthCare System in
North Carolina.
"These `nothing left to do' conversations often frame palliative care as a way to help people die comfortably, rather than an approach to care that allows them to live with the highest quality of life for as long as possible," said Caprio, who wrote an editorial that was published with the study.
Using different language in discussions with patients can make a big difference, Caprio added.
"I often describe palliative care as an extra layer of support," Caprio said. "Who wouldn't want more support, especially during a difficult illness?"
(Reuters Health) - Some cancer patients may turn down care that could ease their pain and improve their quality of life because they think this type of "palliative" treatment amounts
to giving up and simply waiting to die, a small Canadian study suggests.
Even though the World Health Organization recommends early palliative care for patients living with any serious illness, negative attitudes among patients and family caregivers often lead them to reject this option, researchers note in the Canadian Medical Association Journal.
"Patients and caregivers in our study saw palliative care as being equated with death, loss of hope, dependency, and going into places you never get out of again," said lead study author Dr. Camilla Zimmermann, head of the division of palliative care at the University Health Network in Toronto.
"This is in stark contrast with the actual definition of palliative care, which is interdisciplinary care that provides quality of life for patients with any serious illness and their families, and that is provided throughout the course of the illness rather than only at the end of life," Zimmermann added by email.
Zimmermann and colleagues interviewed 48 cancer patients and 23 of their family caregivers in cases when life expectancy was six to 24 months.
The researchers randomly assigned 26 patients to receive palliative care in addition to standard cancer care, while another 22 patients had only standard care.
Twenty-two patients in the palliative care group and 20 in the control group were receiving chemotherapy.
Over four months, patients in the palliative care group had at least monthly palliative care clinic visits, while those in the standard care group didn't receive any formal interventions. Caregivers could attend clinic visits for the palliative care participants, but they weren't required to do so.
Patients were typically in their early to mid 60s. Most were married and had at least some education beyond high school.
Most family caregivers were spouses, but a few were children or other relatives.
Initial perceptions of palliative care were similar in both groups - patients generally thought this was done only for the dying. While patients in both groups thought of palliative care
as providing comfort, they also associated it with giving up on treatment.
Once some patients received palliative care, however, their thinking shifted. Some patients now saw this as a way to live life to the fullest despite the terminal diagnosis, while others
suggested that doctors might have better luck renaming this as something other than "palliative care."
Calling palliative care providers "pain specialists" because they treat discomfort and focus on quality of life would make this sound more appealing and less frightening, some patients
said after getting this type of care.
But in the control group, without any experience with palliative care during the study, patients didn't see the point of renaming it because they thought it would still carry the stigma of giving up and waiting to die.
"Palliative care should not be framed as a last resort option," said Dr. Anthony Caprio, a geriatrician and hospice and palliative medicine physician at Carolinas HealthCare System in
North Carolina.
"These `nothing left to do' conversations often frame palliative care as a way to help people die comfortably, rather than an approach to care that allows them to live with the highest quality of life for as long as possible," said Caprio, who wrote an editorial that was published with the study.
Using different language in discussions with patients can make a big difference, Caprio added.
"I often describe palliative care as an extra layer of support," Caprio said. "Who wouldn't want more support, especially during a difficult illness?"
(Reuters Health) - Some cancer patients may turn down care that could ease their pain and improve their quality of life because they think this type of "palliative" treatment amounts
to giving up and simply waiting to die, a small Canadian study suggests.
Even though the World Health Organization recommends early palliative care for patients living with any serious illness, negative attitudes among patients and family caregivers often lead them to reject this option, researchers note in the Canadian Medical Association Journal.
"Patients and caregivers in our study saw palliative care as being equated with death, loss of hope, dependency, and going into places you never get out of again," said lead study author Dr. Camilla Zimmermann, head of the division of palliative care at the University Health Network in Toronto.
"This is in stark contrast with the actual definition of palliative care, which is interdisciplinary care that provides quality of life for patients with any serious illness and their families, and that is provided throughout the course of the illness rather than only at the end of life," Zimmermann added by email.
Zimmermann and colleagues interviewed 48 cancer patients and 23 of their family caregivers in cases when life expectancy was six to 24 months.
The researchers randomly assigned 26 patients to receive palliative care in addition to standard cancer care, while another 22 patients had only standard care.
Twenty-two patients in the palliative care group and 20 in the control group were receiving chemotherapy.
Over four months, patients in the palliative care group had at least monthly palliative care clinic visits, while those in the standard care group didn't receive any formal interventions. Caregivers could attend clinic visits for the palliative care participants, but they weren't required to do so.
Patients were typically in their early to mid 60s. Most were married and had at least some education beyond high school.
Most family caregivers were spouses, but a few were children or other relatives.
Initial perceptions of palliative care were similar in both groups - patients generally thought this was done only for the dying. While patients in both groups thought of palliative care
as providing comfort, they also associated it with giving up on treatment.
Once some patients received palliative care, however, their thinking shifted. Some patients now saw this as a way to live life to the fullest despite the terminal diagnosis, while others
suggested that doctors might have better luck renaming this as something other than "palliative care."
Calling palliative care providers "pain specialists" because they treat discomfort and focus on quality of life would make this sound more appealing and less frightening, some patients
said after getting this type of care.
But in the control group, without any experience with palliative care during the study, patients didn't see the point of renaming it because they thought it would still carry the stigma of giving up and waiting to die.
"Palliative care should not be framed as a last resort option," said Dr. Anthony Caprio, a geriatrician and hospice and palliative medicine physician at Carolinas HealthCare System in
North Carolina.
"These `nothing left to do' conversations often frame palliative care as a way to help people die comfortably, rather than an approach to care that allows them to live with the highest quality of life for as long as possible," said Caprio, who wrote an editorial that was published with the study.
Using different language in discussions with patients can make a big difference, Caprio added.
"I often describe palliative care as an extra layer of support," Caprio said. "Who wouldn't want more support, especially during a difficult illness?"
Disposable Navigation for Total Knee Arthroplasty
Total knee arthroplasty (TKA) continues to be a widely utilized treatment option for end-stage knee osteoarthritis, and the number of patients undergoing TKA is projected to continually increase over the next decade.1 Although TKA is highly successful for many patients, studies continue to report that approximately 20% of patients are dissatisfied after undergoing TKA, and nearly 25% of knee revisions are performed for instability or malalignment.2,3 Technological advances have been developed to help improve clinical outcomes and implant survivorship. Over the past decade, computer navigation and intraoperative guides have been introduced to help control surgical variables and overcome the limitations and inaccuracies of traditional mechanical instrumentation. Currently, there are a variety of technologies available to assist surgeons with component alignment, including extramedullary devices, computer-assisted navigation systems (CAS), and patient-specific instrumentation (PSI) that help achieve desired alignment goals.4,5
Computer-assisted navigation tools were introduced in an effort to improve implant alignment and clinical outcomes compared to traditional mechanical guides. Some argue that the use of computer-assisted surgery has a steep learning curve and successful use is dependent on the user’s experience; however, studies have suggested computer-assisted surgery may allow less experienced surgeons to reliably achieve anticipated intraoperative alignment goals with a low complication rate.6,7 Various studies have looked at computer-assisted TKA at short to mid-term follow-up, but few studies have reported long-term outcomes.6-9 de Steiger and colleagues10 recently found that computer-assisted TKA reduced the overall revision rate for aseptic loosening following TKA in patients younger than age 65 years, which suggests benefit of CAS for younger patients. Short-term follow-up has also shown the benefit of CAS TKA in patients with severe extra-articular deformity, where traditional instrumentation cannot be utilized.11 Currently, there is no consensus that computer-assisted TKA leads to improved postoperative patient reported outcomes, because many studies are limited by study design or small cohorts; however, current literature does show an improvement in component alignment as compared to mechanical instrumentation.9,12,13 As future implant and position targets are defined to improve implant survivorship and clinical outcomes in total joint arthroplasty, computer-assisted devices will be useful to help achieve more precise and accurate component positioning.
In addition to CAS devices, some companies have sought to improve TKA surgery by introducing PSI. PSI was introduced to improve component alignment in TKA, with the purported advantages of a shorter surgical time, decrease in the number of instruments needed, and improved clinical outcomes. PSI accuracy remains variable, which may be attributed to the various systems and implant designs in each study.14-17 In addition, advanced preoperative imaging is necessary, which further adds to the overall cost.17 While the recent advancement in technology may provide decreased costs at the time of surgery, the increased cost and time incurred by the patient preoperatively has not resulted in significantly better clinical outcomes.18,19 Additionally, recent work has not shown PSI to have superior accuracy as compared to currently available CAS devices.14 These findings suggest that the additional cost and time incurred by patients may limit the widespread use of PSI.
Although computer navigation has been shown to be more accurate than conventional instrumentation and PSI, the lack of improvement in long-term clinical outcome data has limited its use. In a meta-analysis, Bauwens and colleagues20 suggested that while navigated TKAs have improved component alignment outcomes as compared to conventional surgery, the clinical benefit remains unclear. Less than 5% of surgeons are currently using navigation systems due to the perceived learning curve, cost, additional surgical time, and imaging required to utilize these systems. Certain navigation systems can be seemingly cumbersome, with large consoles, increased number of instruments required, and optical instruments with line-of-sight issues. Recent technological advances have worked to decrease this challenge by using accelerometer- and gyroscope-based electronic components, which combine the accuracy of computer-assisted technology with the ease of use of mechanical guides.
Accelerometer and gyroscope technology systems, such as the iAssist system, are portable devices that do not require a large computer console or navigation arrays. This technology relies on accelerator-based navigation without additional preoperative imaging. A recent study demonstrated the iAssist had reproducible accuracy in component alignment that could be easily incorporated into the operating room without optical trackers.21 The use of portable computer-assisted devices provides a more compact and easily accessible technology that can be used to achieve accurate component alignment without additional large equipment in the operating room.22 These new handheld intraoperative tools have been introduced to place implants according to a preoperative plan in order to minimize failure due to preoperative extra-articular deformity or intraoperative technical miscues.23 Nam and colleagues24 used an accelerometer-based surgical navigation system to perform tibial resections in cadaveric models, and found that the accelerometer-based guide was accurate for tibial resection in both the coronal and sagittal planes. In a prospective randomized controlled trial evaluating 100 patients undergoing a TKA using either an accelerometer-based guide or conventional alignment methods, the authors showed that the accelerometer-based guide decreased outliers in tibial component alignment compared to conventional guides.25 In the accelerometer-based guide cohort, 95.7% of tibial components were within 2° of perpendicular to the tibial mechanical axis, compared to 68.1% in the conventional group (P < .001). These results suggested that portable accelerometer-based navigation allows surgeons to achieve satisfactory tibial component alignment with a decrease in the number of potential outliers.24,25 Similarly, Bugbee and colleagues26 found that accelerometer-based handheld navigation was accurate for tibial coronal and sagittal alignment and no additional surgical time was required compared to conventional techniques.
The relationship between knee alignment and clinical outcomes for TKA remains controversial. Regardless of the surgeon’s alignment preference, it is important to reliably and accurately execute the preoperative plan in a reproducible fashion. Advances in technology that assist with intraoperative component alignment can be useful, and may help decrease the incidence of implant malalignment in clinical practice.
Preoperative Planning and Intraoperative Technique
Preoperative planning is carried out in a manner identical to the use of conventional mechanical guides. Long leg films are taken for evaluation of overall limb alignment, and calibrated lateral images are taken for templating implant sizes. Lines are drawn on the images to determine the difference between the mechanical and anatomic axis of the femur, and a line drawn perpendicular to the mechanical axis is placed to show the expected bone cut. In similar fashion a perpendicular line to the tibial mechanical axis is also drawn to show the expected tibial resection. This preoperative plan allows the surgeon to have an additional intraoperative guide to ensure accuracy of the computer-assisted device.
After standard exposure, the distal femoral or proximal tibial cut can be made based on surgeon preference. The system being demonstrated in the accompanying photos is the KneeAlign 2 system (OrthAlign).
Distal Femoral Cut
The KneeAlign 2 femoral cutting guide is attached to the distal femur with a central pin that is placed in the middle of the distal femur measured from medial to lateral, and 1 cm anterior to the intercondylar notch. It is important to note that this spot is often more medial than traditionally used for insertion of an intramedullary rod. This central point sets the distal point of the femoral mechanical axis. The device is then held in place with 2 oblique pins, and is solidly fixed to the bone. Using a rotating motion, the femur is rotated around the hip joint. The accelerometer and gyroscope in the unit are able to determine the center of the hip joint from this motion, creating the proximal point of the mechanical axis of the femur. Once the mechanical axis of the femur is determined, varus/valgus and flexion/extension can be adjusted on the guide. One adjustment screw is available for varus/valgus, and a second is available for flexion/extension. Numbers on the device screen show real-time alignment, and are easily adjusted to set the desired alignment (Figure 1). Once alignment is obtained, a mechanical stylus is used to determine depth of resection, and the distal femoral cutting block is pinned. After pinning the block, the 3 pins in the device are removed, and the device is removed from the bone. This leaves only the distal femoral cutting block in place. In experienced hands, this part of the procedure takes less than 3 minutes.
Proximal Tibial Cut
The KneeAlign 2 proximal tibial guide is similar in appearance to a standard mechanical tibial cutting guide. It is attached to the proximal tibia with a spring around the calf and 2 pins that hold the device aligned with the medial third of the tibial tubercle. A stylus is then centered on the anterior cruciate ligament (ACL) footprint, which sets the proximal mechanical axis point of the tibia (Figure 2). An offset number is read off the stylus on the ACL footprint, and this number is matched on the ankle offset portion of the guide. The device has 2 sensors. One sensor is on the chassis of the device, and the other is on a mobile arm. Movements between the 2 are monitored by the accelerometers, allowing for accurate maintenance of alignment position even with motion in the leg. A point is taken from the lateral malleolus and then a second point is taken from the medial malleolus. These points are used to determine the center of the ankle joint, which sets the distal mechanical axis point. Once mechanical axis of the tibia is determined, the tibial cutting guide is pinned in place, and can be adjusted with real-time guidance of the varus/valgus and posterior slope values seen on the device (Figure 3). Cut depth is once again determined with a mechanical stylus.
Limitations
Although these devices have proven to be very accurate, surgeons must continue to recognize that all tools can have errors. With computerized guides of any sort, these errors are usually user errors that cannot be detected by the device. Surgeons need to be able to recognize this and always double-check bone cuts for accuracy. Templating the bone cuts prior to surgery is an effective double-check. In addition, many handheld accelerometer devices do not currently assist with the rotational alignment of the femoral component. This is still performed using the surgeon’s preferred technique, and is a limitation of these systems.
Discussion
Currently, TKA provides satisfactory 10-year results with modern implant designs and survival rates as high as 90% to 95%.27,28 Even with good survival rates, a percentage of patients fail within the first 5 years.3 At a single institution, 50% of revision TKAs were related to instability, malalignment, or failure of fixation that occurred less than 2 years after the index procedure.29 In general, TKA with mechanical instrumentation provides satisfactory pain relief and postoperative knee function; however, studies have consistently shown that the use of advanced technology decreases the risk of implant malalignment, which may decrease early implant failure rates as compared to mechanical and some PSI.13,14,22 While there is a paucity of literature that has shown better clinical outcomes with the use of advanced technology, there are studies supporting the notion that proper limb alignment and component positioning improves implant survivorship.23,30
CAS may have additional advantages if the surgeon chooses to place the TKA in an alignment other than a neutral mechanical axis. Kinematic alignment for TKA has gained increasing popularity, where the target of a neutral mechanical axis alignment is not always the goal.31,32 The reported benefit is a more natural ligament tension with the hope of improving patient satisfaction. One concern with this technique is that it is a departure from the long-held teaching that a TKA aligned to a neutral mechanical axis is necessary for long-term implant survivorship.33,34 In addition, if the goal of surgery is to cut the tibia and femur at a specific varus/valgus cut, standard instrumentation may not allow for this level of accuracy. This in turn increases the risk of having a tibial or femoral cut that is outside the commonly accepted standards of alignment, which may lead to early implant failure. If further research suggests alignment is a variable that differs from patient to patient, the use of precise tools to ensure accuracy of executing the preoperatively templated alignment becomes even more important.
As the number of TKAs continues to rise each year, even a small percentage of malaligned knees that go on to revision surgery will create a large burden on the healthcare system.1,3 Although the short-term clinical benefits of CAS have not shown substantial differences as compared to conventional TKA, the number of knees aligned outside of a desired neutral mechanical axis alignment has been shown in multiple studies to be decreased with the use of advanced technology.7,12,34 Although CAS is an additional cost to a primary TKA, if the orthopedic community can decrease the number of TKA revisions due to malalignment from 6.6% to nearly zero, this may decrease the revision burden and overall cost to the healthcare system.1,3
TKA technology continues to evolve, and we must continue to assess each new advance not only to understand how it works, but also to ensure it addresses a specific clinical problem, and to be aware of the costs associated before incorporating it into routine practice. Some argue that the use of advanced technology requires increased surgical time, which in turn ultimately increases costs; however, one study has documented no increase in surgical time with handheld navigation while maintaining the accuracy of the device.34 In addition, no significant radiographic or clinical differences have been found between handheld navigation and larger console CAS systems, but large console systems have been associated with increased surgical times.22 The use of handheld accelerometer- and gyroscope-based guides has proven to provide reliable coronal and sagittal implant alignment that can easily be incorporated into the operating room. More widespread use of such technology will help decrease alignment outliers for TKA, and future long-term clinical outcome studies will be necessary to assess functional outcomes.
Conclusion
Advanced computer based technology offers an additional tool to the surgeon for reliably improving component positioning during TKA. The use of handheld accelerometer- and gyroscope-based guides increases the accuracy of component placement while decreasing the incidence of outliers compared to standard mechanical guides, without the need for a large computer console. Long-term radiographic and patient-reported outcomes are necessary to further validate these devices.
1. Kurtz SM, Ong KL, Lau E, Bozic KJ. Impact of the economic downturn on total joint replacement demand in the United States: updated projections to 2021. J Bone Joint Surg Am. 2014;96(8):624-630.
2. Bourne RB, Chesworth BM, Davis AM, Mahomed NN, Charron KD. Patient satisfaction after total knee arthroplasty: who is satisfied and who is not? Clin Orthop Relat Res. 2010;468(1):57-63.
3. Schroer WC, Berend KR, Lombardi AV, et al. Why are total knees failing today? Etiology of total knee revision in 2010 and 2011. J Arthroplasty. 2013;28( 8 Suppl):116-119.
4. Sassoon A, Nam D, Nunley R, Barrack R. Systematic review of patient-specific instrumentation in total knee arthroplasty: new but not improved. Clin Orthop Relat Res. 2015;473(1):151-158.
5. Anderson KC, Buehler KC, Markel DC. Computer assisted navigation in total knee arthroplasty: comparison with conventional methods. J Arthroplasty. 2005;20(7 Suppl 3):132-138.
6. Mason JB, Fehring TK, Estok R, Banel D, Fahrbach K. Meta-analysis of alignment outcomes in computer-assisted total knee arthroplasty surgery. J Arthroplasty. 2007;22(8):1097-1106.
7. Khakha RS, Chowdhry M, Sivaprakasam M, Kheiran A, Chauhan SK. Radiological and functional outcomes in computer assisted total knee arthroplasty between consultants and trainees - a prospective randomized controlled trial. J Arthroplasty. 2015;30(8):1344-1347.
8. Zhu M, Ang CL, Yeo SJ, Lo NN, Chia SL, Chong HC. Minimally invasive computer-assisted total knee arthroplasty compared with conventional total knee arthroplasty: a prospective 9-year follow-up. J Arthroplasty. 2015. [Epub ahead of print]
9. Roberts TD, Clatworthy MG, Frampton CM, Young SW. Does computer assisted navigation improve functional outcomes and implant survivability after total knee arthroplasty? J Arthroplasty. 2015;30(9 Suppl):59-63.
10. de Steiger RN, Liu YL, Graves SE. Computer navigation for total knee arthroplasty reduces revision rate for patients less than sixty-five years of age. J Bone Joint Surg Am. 2015;97(8):635-642.
11. Fehring TK, Mason JB, Moskal J, Pollock DC, Mann J, Williams VJ. When computer-assisted knee replacement is the best alternative. Clin Orthop Relat Res. 2006;452:132-136.
12. Iorio R, Mazza D, Drogo P, et al. Clinical and radiographic outcomes of an accelerometer-based system for the tibial resection in total knee arthroplasty. Int Orthop. 2015;39(3):461-466.
13. Haaker RG, Stockheim M, Kamp M, Proff G, Breitenfelder J, Ottersbach A. Computer-assisted navigation increases precision of component placement in total knee arthroplasty. Clin Orthop Relat Res. 2005;433:152-159.
14. Ollivier M, Tribot-Laspiere Q, Amzallag J, Boisrenoult P, Pujol N, Beaufils P. Abnormal rate of intraoperative and postoperative implant positioning outliers using “MRI-based patient-specific” compared to “computer assisted” instrumentation in total knee replacement. Knee Surg Sports Traumatol Arthrosc. 2015. [Epub ahead of print]
15. Nunley RM, Ellison BS, Zhu J, Ruh EL, Howell SM, Barrack RL. Do patient-specific guides improve coronal alignment in total knee arthroplasty? Clin Orthop Relat Res. 2012;470(3):895-902.
16. Nunley RM, Ellison BS, Ruh EL, et al. Are patient-specific cutting blocks cost-effective for total knee arthroplasty? Clin Orthop Relat Res. 2012;470(3):889-894.
17. Barrack RL, Ruh EL, Williams BM, Ford AD, Foreman K, Nunley RM. Patient specific cutting blocks are currently of no proven value. J Bone Joint Surg Br. 2012;94(11 Suppl A):95-99.
18. Chen JY, Chin PL, Tay DK, Chia SL, Lo NN, Yeo SJ. Functional outcome and quality of life after patient-specific instrumentation in total knee arthroplasty. J Arthroplasty. 2015;30(10):1724-1728.
19. Goyal N, Patel AR, Yaffe MA, Luo MY, Stulberg SD. Does implant design influence the accuracy of patient specific instrumentation in total knee arthroplasty? J Arthroplasty. 2015;30(9):1526-1530.
20. Bauwens K, Matthes G, Wich M, et al. Navigated total knee replacement. A meta-analysis. J Bone Joint Surg Am. 2007;89(2):261-269.
21. Scuderi GR, Fallaha M, Masse V, Lavigne P, Amiot LP, Berthiaume MJ. Total knee arthroplasty with a novel navigation system within the surgical field. Orthop Clin North Am. 2014;45(2):167-173.
22. Goh GS, Liow MH, Lim WS, Tay DK, Yeo SJ, Tan MH. Accelerometer-based navigation is as accurate as optical computer navigation in restoring the joint line and mechanical axis after total knee arthroplasty: a prospective matched study. J Arthroplasty. 2016;31(1):92-97.
23. Berend KR, Lombardi AV Jr. Liberal indications for minimally invasive oxford unicondylar arthroplasty provide rapid functional recovery and pain relief. Surg Technol Int. 2007;16:193-197.
24. Nam D, Jerabek SA, Cross MB, Mayman DJ. Cadaveric analysis of an accelerometer-based portable navigation device for distal femoral cutting block alignment in total knee arthroplasty. Comput Aided Surg. 2012;17(4):205-210.
25. Nam D, Cody EA, Nguyen JT, Figgie MP, Mayman DJ. Extramedullary guides versus portable, accelerometer-based navigation for tibial alignment in total knee arthroplasty: a randomized, controlled trial: winner of the 2013 HAP PAUL award. J Arthroplasty. 2014;29(2):288-294.
26. Bugbee WD, Kermanshahi AY, Munro MM, McCauley JC, Copp SN. Accuracy of a hand-held surgical navigation system for tibial resection in total knee arthroplasty. Knee. 2014;21(6):1225-1228.
27. Schai PA, Thornhill TS, Scott RD. Total knee arthroplasty with the PFC system. Results at a minimum of ten years and survivorship analysis. J Bone Joint Surg Br. 1998;80(5):850-858.
28. Pradhan NR, Gambhir A, Porter ML. Survivorship analysis of 3234 primary knee arthroplasties implanted over a 26-year period: a study of eight different implant designs. Knee. 2006;13(1):7-11.
29. Sharkey PF, Hozack WJ, Rothman RH, Shastri S, Jacoby SM. Insall Award paper. Why are total knee arthroplasties failing today? Clin Orthop Relat Res. 2002;404:7-13.
30. Fang DM, Ritter MA, Davis KE. Coronal alignment in total knee arthroplasty: just how important is it? J Arthroplasty. 2009;24(6 Suppl):39-43.
31. Cherian JJ, Kapadia BH, Banerjee S, Jauregui JJ, Issa K, Mont MA. Mechanical, anatomical, and kinematic axis in TKA: concepts and practical applications. Curr Rev Musculoskelet Med. 2014;7(2):89-95.
32. Howell SM, Papadopoulos S, Kuznik K, Ghaly LR, Hull ML. Does varus alignment adversely affect implant survival and function six years after kinematically aligned total knee arthroplasty? Int Orthop. 2015;39(11):2117-2124.
33. Ritter MA, Faris PM, Keating EM, Meding JB. Postoperative alignment of total knee replacement. Its effect on survival. Clin Orthop Relat Res. 1994;299:153-156.
34. Huang EH, Copp SN, Bugbee WD. Accuracy of a handheld accelerometer-based navigation system for femoral and tibial resection in total knee arthroplasty. J Arthroplasty. 2015;30(11):1906-1910.
Total knee arthroplasty (TKA) continues to be a widely utilized treatment option for end-stage knee osteoarthritis, and the number of patients undergoing TKA is projected to continually increase over the next decade.1 Although TKA is highly successful for many patients, studies continue to report that approximately 20% of patients are dissatisfied after undergoing TKA, and nearly 25% of knee revisions are performed for instability or malalignment.2,3 Technological advances have been developed to help improve clinical outcomes and implant survivorship. Over the past decade, computer navigation and intraoperative guides have been introduced to help control surgical variables and overcome the limitations and inaccuracies of traditional mechanical instrumentation. Currently, there are a variety of technologies available to assist surgeons with component alignment, including extramedullary devices, computer-assisted navigation systems (CAS), and patient-specific instrumentation (PSI) that help achieve desired alignment goals.4,5
Computer-assisted navigation tools were introduced in an effort to improve implant alignment and clinical outcomes compared to traditional mechanical guides. Some argue that the use of computer-assisted surgery has a steep learning curve and successful use is dependent on the user’s experience; however, studies have suggested computer-assisted surgery may allow less experienced surgeons to reliably achieve anticipated intraoperative alignment goals with a low complication rate.6,7 Various studies have looked at computer-assisted TKA at short to mid-term follow-up, but few studies have reported long-term outcomes.6-9 de Steiger and colleagues10 recently found that computer-assisted TKA reduced the overall revision rate for aseptic loosening following TKA in patients younger than age 65 years, which suggests benefit of CAS for younger patients. Short-term follow-up has also shown the benefit of CAS TKA in patients with severe extra-articular deformity, where traditional instrumentation cannot be utilized.11 Currently, there is no consensus that computer-assisted TKA leads to improved postoperative patient reported outcomes, because many studies are limited by study design or small cohorts; however, current literature does show an improvement in component alignment as compared to mechanical instrumentation.9,12,13 As future implant and position targets are defined to improve implant survivorship and clinical outcomes in total joint arthroplasty, computer-assisted devices will be useful to help achieve more precise and accurate component positioning.
In addition to CAS devices, some companies have sought to improve TKA surgery by introducing PSI. PSI was introduced to improve component alignment in TKA, with the purported advantages of a shorter surgical time, decrease in the number of instruments needed, and improved clinical outcomes. PSI accuracy remains variable, which may be attributed to the various systems and implant designs in each study.14-17 In addition, advanced preoperative imaging is necessary, which further adds to the overall cost.17 While the recent advancement in technology may provide decreased costs at the time of surgery, the increased cost and time incurred by the patient preoperatively has not resulted in significantly better clinical outcomes.18,19 Additionally, recent work has not shown PSI to have superior accuracy as compared to currently available CAS devices.14 These findings suggest that the additional cost and time incurred by patients may limit the widespread use of PSI.
Although computer navigation has been shown to be more accurate than conventional instrumentation and PSI, the lack of improvement in long-term clinical outcome data has limited its use. In a meta-analysis, Bauwens and colleagues20 suggested that while navigated TKAs have improved component alignment outcomes as compared to conventional surgery, the clinical benefit remains unclear. Less than 5% of surgeons are currently using navigation systems due to the perceived learning curve, cost, additional surgical time, and imaging required to utilize these systems. Certain navigation systems can be seemingly cumbersome, with large consoles, increased number of instruments required, and optical instruments with line-of-sight issues. Recent technological advances have worked to decrease this challenge by using accelerometer- and gyroscope-based electronic components, which combine the accuracy of computer-assisted technology with the ease of use of mechanical guides.
Accelerometer and gyroscope technology systems, such as the iAssist system, are portable devices that do not require a large computer console or navigation arrays. This technology relies on accelerator-based navigation without additional preoperative imaging. A recent study demonstrated the iAssist had reproducible accuracy in component alignment that could be easily incorporated into the operating room without optical trackers.21 The use of portable computer-assisted devices provides a more compact and easily accessible technology that can be used to achieve accurate component alignment without additional large equipment in the operating room.22 These new handheld intraoperative tools have been introduced to place implants according to a preoperative plan in order to minimize failure due to preoperative extra-articular deformity or intraoperative technical miscues.23 Nam and colleagues24 used an accelerometer-based surgical navigation system to perform tibial resections in cadaveric models, and found that the accelerometer-based guide was accurate for tibial resection in both the coronal and sagittal planes. In a prospective randomized controlled trial evaluating 100 patients undergoing a TKA using either an accelerometer-based guide or conventional alignment methods, the authors showed that the accelerometer-based guide decreased outliers in tibial component alignment compared to conventional guides.25 In the accelerometer-based guide cohort, 95.7% of tibial components were within 2° of perpendicular to the tibial mechanical axis, compared to 68.1% in the conventional group (P < .001). These results suggested that portable accelerometer-based navigation allows surgeons to achieve satisfactory tibial component alignment with a decrease in the number of potential outliers.24,25 Similarly, Bugbee and colleagues26 found that accelerometer-based handheld navigation was accurate for tibial coronal and sagittal alignment and no additional surgical time was required compared to conventional techniques.
The relationship between knee alignment and clinical outcomes for TKA remains controversial. Regardless of the surgeon’s alignment preference, it is important to reliably and accurately execute the preoperative plan in a reproducible fashion. Advances in technology that assist with intraoperative component alignment can be useful, and may help decrease the incidence of implant malalignment in clinical practice.
Preoperative Planning and Intraoperative Technique
Preoperative planning is carried out in a manner identical to the use of conventional mechanical guides. Long leg films are taken for evaluation of overall limb alignment, and calibrated lateral images are taken for templating implant sizes. Lines are drawn on the images to determine the difference between the mechanical and anatomic axis of the femur, and a line drawn perpendicular to the mechanical axis is placed to show the expected bone cut. In similar fashion a perpendicular line to the tibial mechanical axis is also drawn to show the expected tibial resection. This preoperative plan allows the surgeon to have an additional intraoperative guide to ensure accuracy of the computer-assisted device.
After standard exposure, the distal femoral or proximal tibial cut can be made based on surgeon preference. The system being demonstrated in the accompanying photos is the KneeAlign 2 system (OrthAlign).
Distal Femoral Cut
The KneeAlign 2 femoral cutting guide is attached to the distal femur with a central pin that is placed in the middle of the distal femur measured from medial to lateral, and 1 cm anterior to the intercondylar notch. It is important to note that this spot is often more medial than traditionally used for insertion of an intramedullary rod. This central point sets the distal point of the femoral mechanical axis. The device is then held in place with 2 oblique pins, and is solidly fixed to the bone. Using a rotating motion, the femur is rotated around the hip joint. The accelerometer and gyroscope in the unit are able to determine the center of the hip joint from this motion, creating the proximal point of the mechanical axis of the femur. Once the mechanical axis of the femur is determined, varus/valgus and flexion/extension can be adjusted on the guide. One adjustment screw is available for varus/valgus, and a second is available for flexion/extension. Numbers on the device screen show real-time alignment, and are easily adjusted to set the desired alignment (Figure 1). Once alignment is obtained, a mechanical stylus is used to determine depth of resection, and the distal femoral cutting block is pinned. After pinning the block, the 3 pins in the device are removed, and the device is removed from the bone. This leaves only the distal femoral cutting block in place. In experienced hands, this part of the procedure takes less than 3 minutes.
Proximal Tibial Cut
The KneeAlign 2 proximal tibial guide is similar in appearance to a standard mechanical tibial cutting guide. It is attached to the proximal tibia with a spring around the calf and 2 pins that hold the device aligned with the medial third of the tibial tubercle. A stylus is then centered on the anterior cruciate ligament (ACL) footprint, which sets the proximal mechanical axis point of the tibia (Figure 2). An offset number is read off the stylus on the ACL footprint, and this number is matched on the ankle offset portion of the guide. The device has 2 sensors. One sensor is on the chassis of the device, and the other is on a mobile arm. Movements between the 2 are monitored by the accelerometers, allowing for accurate maintenance of alignment position even with motion in the leg. A point is taken from the lateral malleolus and then a second point is taken from the medial malleolus. These points are used to determine the center of the ankle joint, which sets the distal mechanical axis point. Once mechanical axis of the tibia is determined, the tibial cutting guide is pinned in place, and can be adjusted with real-time guidance of the varus/valgus and posterior slope values seen on the device (Figure 3). Cut depth is once again determined with a mechanical stylus.
Limitations
Although these devices have proven to be very accurate, surgeons must continue to recognize that all tools can have errors. With computerized guides of any sort, these errors are usually user errors that cannot be detected by the device. Surgeons need to be able to recognize this and always double-check bone cuts for accuracy. Templating the bone cuts prior to surgery is an effective double-check. In addition, many handheld accelerometer devices do not currently assist with the rotational alignment of the femoral component. This is still performed using the surgeon’s preferred technique, and is a limitation of these systems.
Discussion
Currently, TKA provides satisfactory 10-year results with modern implant designs and survival rates as high as 90% to 95%.27,28 Even with good survival rates, a percentage of patients fail within the first 5 years.3 At a single institution, 50% of revision TKAs were related to instability, malalignment, or failure of fixation that occurred less than 2 years after the index procedure.29 In general, TKA with mechanical instrumentation provides satisfactory pain relief and postoperative knee function; however, studies have consistently shown that the use of advanced technology decreases the risk of implant malalignment, which may decrease early implant failure rates as compared to mechanical and some PSI.13,14,22 While there is a paucity of literature that has shown better clinical outcomes with the use of advanced technology, there are studies supporting the notion that proper limb alignment and component positioning improves implant survivorship.23,30
CAS may have additional advantages if the surgeon chooses to place the TKA in an alignment other than a neutral mechanical axis. Kinematic alignment for TKA has gained increasing popularity, where the target of a neutral mechanical axis alignment is not always the goal.31,32 The reported benefit is a more natural ligament tension with the hope of improving patient satisfaction. One concern with this technique is that it is a departure from the long-held teaching that a TKA aligned to a neutral mechanical axis is necessary for long-term implant survivorship.33,34 In addition, if the goal of surgery is to cut the tibia and femur at a specific varus/valgus cut, standard instrumentation may not allow for this level of accuracy. This in turn increases the risk of having a tibial or femoral cut that is outside the commonly accepted standards of alignment, which may lead to early implant failure. If further research suggests alignment is a variable that differs from patient to patient, the use of precise tools to ensure accuracy of executing the preoperatively templated alignment becomes even more important.
As the number of TKAs continues to rise each year, even a small percentage of malaligned knees that go on to revision surgery will create a large burden on the healthcare system.1,3 Although the short-term clinical benefits of CAS have not shown substantial differences as compared to conventional TKA, the number of knees aligned outside of a desired neutral mechanical axis alignment has been shown in multiple studies to be decreased with the use of advanced technology.7,12,34 Although CAS is an additional cost to a primary TKA, if the orthopedic community can decrease the number of TKA revisions due to malalignment from 6.6% to nearly zero, this may decrease the revision burden and overall cost to the healthcare system.1,3
TKA technology continues to evolve, and we must continue to assess each new advance not only to understand how it works, but also to ensure it addresses a specific clinical problem, and to be aware of the costs associated before incorporating it into routine practice. Some argue that the use of advanced technology requires increased surgical time, which in turn ultimately increases costs; however, one study has documented no increase in surgical time with handheld navigation while maintaining the accuracy of the device.34 In addition, no significant radiographic or clinical differences have been found between handheld navigation and larger console CAS systems, but large console systems have been associated with increased surgical times.22 The use of handheld accelerometer- and gyroscope-based guides has proven to provide reliable coronal and sagittal implant alignment that can easily be incorporated into the operating room. More widespread use of such technology will help decrease alignment outliers for TKA, and future long-term clinical outcome studies will be necessary to assess functional outcomes.
Conclusion
Advanced computer based technology offers an additional tool to the surgeon for reliably improving component positioning during TKA. The use of handheld accelerometer- and gyroscope-based guides increases the accuracy of component placement while decreasing the incidence of outliers compared to standard mechanical guides, without the need for a large computer console. Long-term radiographic and patient-reported outcomes are necessary to further validate these devices.
Total knee arthroplasty (TKA) continues to be a widely utilized treatment option for end-stage knee osteoarthritis, and the number of patients undergoing TKA is projected to continually increase over the next decade.1 Although TKA is highly successful for many patients, studies continue to report that approximately 20% of patients are dissatisfied after undergoing TKA, and nearly 25% of knee revisions are performed for instability or malalignment.2,3 Technological advances have been developed to help improve clinical outcomes and implant survivorship. Over the past decade, computer navigation and intraoperative guides have been introduced to help control surgical variables and overcome the limitations and inaccuracies of traditional mechanical instrumentation. Currently, there are a variety of technologies available to assist surgeons with component alignment, including extramedullary devices, computer-assisted navigation systems (CAS), and patient-specific instrumentation (PSI) that help achieve desired alignment goals.4,5
Computer-assisted navigation tools were introduced in an effort to improve implant alignment and clinical outcomes compared to traditional mechanical guides. Some argue that the use of computer-assisted surgery has a steep learning curve and successful use is dependent on the user’s experience; however, studies have suggested computer-assisted surgery may allow less experienced surgeons to reliably achieve anticipated intraoperative alignment goals with a low complication rate.6,7 Various studies have looked at computer-assisted TKA at short to mid-term follow-up, but few studies have reported long-term outcomes.6-9 de Steiger and colleagues10 recently found that computer-assisted TKA reduced the overall revision rate for aseptic loosening following TKA in patients younger than age 65 years, which suggests benefit of CAS for younger patients. Short-term follow-up has also shown the benefit of CAS TKA in patients with severe extra-articular deformity, where traditional instrumentation cannot be utilized.11 Currently, there is no consensus that computer-assisted TKA leads to improved postoperative patient reported outcomes, because many studies are limited by study design or small cohorts; however, current literature does show an improvement in component alignment as compared to mechanical instrumentation.9,12,13 As future implant and position targets are defined to improve implant survivorship and clinical outcomes in total joint arthroplasty, computer-assisted devices will be useful to help achieve more precise and accurate component positioning.
In addition to CAS devices, some companies have sought to improve TKA surgery by introducing PSI. PSI was introduced to improve component alignment in TKA, with the purported advantages of a shorter surgical time, decrease in the number of instruments needed, and improved clinical outcomes. PSI accuracy remains variable, which may be attributed to the various systems and implant designs in each study.14-17 In addition, advanced preoperative imaging is necessary, which further adds to the overall cost.17 While the recent advancement in technology may provide decreased costs at the time of surgery, the increased cost and time incurred by the patient preoperatively has not resulted in significantly better clinical outcomes.18,19 Additionally, recent work has not shown PSI to have superior accuracy as compared to currently available CAS devices.14 These findings suggest that the additional cost and time incurred by patients may limit the widespread use of PSI.
Although computer navigation has been shown to be more accurate than conventional instrumentation and PSI, the lack of improvement in long-term clinical outcome data has limited its use. In a meta-analysis, Bauwens and colleagues20 suggested that while navigated TKAs have improved component alignment outcomes as compared to conventional surgery, the clinical benefit remains unclear. Less than 5% of surgeons are currently using navigation systems due to the perceived learning curve, cost, additional surgical time, and imaging required to utilize these systems. Certain navigation systems can be seemingly cumbersome, with large consoles, increased number of instruments required, and optical instruments with line-of-sight issues. Recent technological advances have worked to decrease this challenge by using accelerometer- and gyroscope-based electronic components, which combine the accuracy of computer-assisted technology with the ease of use of mechanical guides.
Accelerometer and gyroscope technology systems, such as the iAssist system, are portable devices that do not require a large computer console or navigation arrays. This technology relies on accelerator-based navigation without additional preoperative imaging. A recent study demonstrated the iAssist had reproducible accuracy in component alignment that could be easily incorporated into the operating room without optical trackers.21 The use of portable computer-assisted devices provides a more compact and easily accessible technology that can be used to achieve accurate component alignment without additional large equipment in the operating room.22 These new handheld intraoperative tools have been introduced to place implants according to a preoperative plan in order to minimize failure due to preoperative extra-articular deformity or intraoperative technical miscues.23 Nam and colleagues24 used an accelerometer-based surgical navigation system to perform tibial resections in cadaveric models, and found that the accelerometer-based guide was accurate for tibial resection in both the coronal and sagittal planes. In a prospective randomized controlled trial evaluating 100 patients undergoing a TKA using either an accelerometer-based guide or conventional alignment methods, the authors showed that the accelerometer-based guide decreased outliers in tibial component alignment compared to conventional guides.25 In the accelerometer-based guide cohort, 95.7% of tibial components were within 2° of perpendicular to the tibial mechanical axis, compared to 68.1% in the conventional group (P < .001). These results suggested that portable accelerometer-based navigation allows surgeons to achieve satisfactory tibial component alignment with a decrease in the number of potential outliers.24,25 Similarly, Bugbee and colleagues26 found that accelerometer-based handheld navigation was accurate for tibial coronal and sagittal alignment and no additional surgical time was required compared to conventional techniques.
The relationship between knee alignment and clinical outcomes for TKA remains controversial. Regardless of the surgeon’s alignment preference, it is important to reliably and accurately execute the preoperative plan in a reproducible fashion. Advances in technology that assist with intraoperative component alignment can be useful, and may help decrease the incidence of implant malalignment in clinical practice.
Preoperative Planning and Intraoperative Technique
Preoperative planning is carried out in a manner identical to the use of conventional mechanical guides. Long leg films are taken for evaluation of overall limb alignment, and calibrated lateral images are taken for templating implant sizes. Lines are drawn on the images to determine the difference between the mechanical and anatomic axis of the femur, and a line drawn perpendicular to the mechanical axis is placed to show the expected bone cut. In similar fashion a perpendicular line to the tibial mechanical axis is also drawn to show the expected tibial resection. This preoperative plan allows the surgeon to have an additional intraoperative guide to ensure accuracy of the computer-assisted device.
After standard exposure, the distal femoral or proximal tibial cut can be made based on surgeon preference. The system being demonstrated in the accompanying photos is the KneeAlign 2 system (OrthAlign).
Distal Femoral Cut
The KneeAlign 2 femoral cutting guide is attached to the distal femur with a central pin that is placed in the middle of the distal femur measured from medial to lateral, and 1 cm anterior to the intercondylar notch. It is important to note that this spot is often more medial than traditionally used for insertion of an intramedullary rod. This central point sets the distal point of the femoral mechanical axis. The device is then held in place with 2 oblique pins, and is solidly fixed to the bone. Using a rotating motion, the femur is rotated around the hip joint. The accelerometer and gyroscope in the unit are able to determine the center of the hip joint from this motion, creating the proximal point of the mechanical axis of the femur. Once the mechanical axis of the femur is determined, varus/valgus and flexion/extension can be adjusted on the guide. One adjustment screw is available for varus/valgus, and a second is available for flexion/extension. Numbers on the device screen show real-time alignment, and are easily adjusted to set the desired alignment (Figure 1). Once alignment is obtained, a mechanical stylus is used to determine depth of resection, and the distal femoral cutting block is pinned. After pinning the block, the 3 pins in the device are removed, and the device is removed from the bone. This leaves only the distal femoral cutting block in place. In experienced hands, this part of the procedure takes less than 3 minutes.
Proximal Tibial Cut
The KneeAlign 2 proximal tibial guide is similar in appearance to a standard mechanical tibial cutting guide. It is attached to the proximal tibia with a spring around the calf and 2 pins that hold the device aligned with the medial third of the tibial tubercle. A stylus is then centered on the anterior cruciate ligament (ACL) footprint, which sets the proximal mechanical axis point of the tibia (Figure 2). An offset number is read off the stylus on the ACL footprint, and this number is matched on the ankle offset portion of the guide. The device has 2 sensors. One sensor is on the chassis of the device, and the other is on a mobile arm. Movements between the 2 are monitored by the accelerometers, allowing for accurate maintenance of alignment position even with motion in the leg. A point is taken from the lateral malleolus and then a second point is taken from the medial malleolus. These points are used to determine the center of the ankle joint, which sets the distal mechanical axis point. Once mechanical axis of the tibia is determined, the tibial cutting guide is pinned in place, and can be adjusted with real-time guidance of the varus/valgus and posterior slope values seen on the device (Figure 3). Cut depth is once again determined with a mechanical stylus.
Limitations
Although these devices have proven to be very accurate, surgeons must continue to recognize that all tools can have errors. With computerized guides of any sort, these errors are usually user errors that cannot be detected by the device. Surgeons need to be able to recognize this and always double-check bone cuts for accuracy. Templating the bone cuts prior to surgery is an effective double-check. In addition, many handheld accelerometer devices do not currently assist with the rotational alignment of the femoral component. This is still performed using the surgeon’s preferred technique, and is a limitation of these systems.
Discussion
Currently, TKA provides satisfactory 10-year results with modern implant designs and survival rates as high as 90% to 95%.27,28 Even with good survival rates, a percentage of patients fail within the first 5 years.3 At a single institution, 50% of revision TKAs were related to instability, malalignment, or failure of fixation that occurred less than 2 years after the index procedure.29 In general, TKA with mechanical instrumentation provides satisfactory pain relief and postoperative knee function; however, studies have consistently shown that the use of advanced technology decreases the risk of implant malalignment, which may decrease early implant failure rates as compared to mechanical and some PSI.13,14,22 While there is a paucity of literature that has shown better clinical outcomes with the use of advanced technology, there are studies supporting the notion that proper limb alignment and component positioning improves implant survivorship.23,30
CAS may have additional advantages if the surgeon chooses to place the TKA in an alignment other than a neutral mechanical axis. Kinematic alignment for TKA has gained increasing popularity, where the target of a neutral mechanical axis alignment is not always the goal.31,32 The reported benefit is a more natural ligament tension with the hope of improving patient satisfaction. One concern with this technique is that it is a departure from the long-held teaching that a TKA aligned to a neutral mechanical axis is necessary for long-term implant survivorship.33,34 In addition, if the goal of surgery is to cut the tibia and femur at a specific varus/valgus cut, standard instrumentation may not allow for this level of accuracy. This in turn increases the risk of having a tibial or femoral cut that is outside the commonly accepted standards of alignment, which may lead to early implant failure. If further research suggests alignment is a variable that differs from patient to patient, the use of precise tools to ensure accuracy of executing the preoperatively templated alignment becomes even more important.
As the number of TKAs continues to rise each year, even a small percentage of malaligned knees that go on to revision surgery will create a large burden on the healthcare system.1,3 Although the short-term clinical benefits of CAS have not shown substantial differences as compared to conventional TKA, the number of knees aligned outside of a desired neutral mechanical axis alignment has been shown in multiple studies to be decreased with the use of advanced technology.7,12,34 Although CAS is an additional cost to a primary TKA, if the orthopedic community can decrease the number of TKA revisions due to malalignment from 6.6% to nearly zero, this may decrease the revision burden and overall cost to the healthcare system.1,3
TKA technology continues to evolve, and we must continue to assess each new advance not only to understand how it works, but also to ensure it addresses a specific clinical problem, and to be aware of the costs associated before incorporating it into routine practice. Some argue that the use of advanced technology requires increased surgical time, which in turn ultimately increases costs; however, one study has documented no increase in surgical time with handheld navigation while maintaining the accuracy of the device.34 In addition, no significant radiographic or clinical differences have been found between handheld navigation and larger console CAS systems, but large console systems have been associated with increased surgical times.22 The use of handheld accelerometer- and gyroscope-based guides has proven to provide reliable coronal and sagittal implant alignment that can easily be incorporated into the operating room. More widespread use of such technology will help decrease alignment outliers for TKA, and future long-term clinical outcome studies will be necessary to assess functional outcomes.
Conclusion
Advanced computer based technology offers an additional tool to the surgeon for reliably improving component positioning during TKA. The use of handheld accelerometer- and gyroscope-based guides increases the accuracy of component placement while decreasing the incidence of outliers compared to standard mechanical guides, without the need for a large computer console. Long-term radiographic and patient-reported outcomes are necessary to further validate these devices.
1. Kurtz SM, Ong KL, Lau E, Bozic KJ. Impact of the economic downturn on total joint replacement demand in the United States: updated projections to 2021. J Bone Joint Surg Am. 2014;96(8):624-630.
2. Bourne RB, Chesworth BM, Davis AM, Mahomed NN, Charron KD. Patient satisfaction after total knee arthroplasty: who is satisfied and who is not? Clin Orthop Relat Res. 2010;468(1):57-63.
3. Schroer WC, Berend KR, Lombardi AV, et al. Why are total knees failing today? Etiology of total knee revision in 2010 and 2011. J Arthroplasty. 2013;28( 8 Suppl):116-119.
4. Sassoon A, Nam D, Nunley R, Barrack R. Systematic review of patient-specific instrumentation in total knee arthroplasty: new but not improved. Clin Orthop Relat Res. 2015;473(1):151-158.
5. Anderson KC, Buehler KC, Markel DC. Computer assisted navigation in total knee arthroplasty: comparison with conventional methods. J Arthroplasty. 2005;20(7 Suppl 3):132-138.
6. Mason JB, Fehring TK, Estok R, Banel D, Fahrbach K. Meta-analysis of alignment outcomes in computer-assisted total knee arthroplasty surgery. J Arthroplasty. 2007;22(8):1097-1106.
7. Khakha RS, Chowdhry M, Sivaprakasam M, Kheiran A, Chauhan SK. Radiological and functional outcomes in computer assisted total knee arthroplasty between consultants and trainees - a prospective randomized controlled trial. J Arthroplasty. 2015;30(8):1344-1347.
8. Zhu M, Ang CL, Yeo SJ, Lo NN, Chia SL, Chong HC. Minimally invasive computer-assisted total knee arthroplasty compared with conventional total knee arthroplasty: a prospective 9-year follow-up. J Arthroplasty. 2015. [Epub ahead of print]
9. Roberts TD, Clatworthy MG, Frampton CM, Young SW. Does computer assisted navigation improve functional outcomes and implant survivability after total knee arthroplasty? J Arthroplasty. 2015;30(9 Suppl):59-63.
10. de Steiger RN, Liu YL, Graves SE. Computer navigation for total knee arthroplasty reduces revision rate for patients less than sixty-five years of age. J Bone Joint Surg Am. 2015;97(8):635-642.
11. Fehring TK, Mason JB, Moskal J, Pollock DC, Mann J, Williams VJ. When computer-assisted knee replacement is the best alternative. Clin Orthop Relat Res. 2006;452:132-136.
12. Iorio R, Mazza D, Drogo P, et al. Clinical and radiographic outcomes of an accelerometer-based system for the tibial resection in total knee arthroplasty. Int Orthop. 2015;39(3):461-466.
13. Haaker RG, Stockheim M, Kamp M, Proff G, Breitenfelder J, Ottersbach A. Computer-assisted navigation increases precision of component placement in total knee arthroplasty. Clin Orthop Relat Res. 2005;433:152-159.
14. Ollivier M, Tribot-Laspiere Q, Amzallag J, Boisrenoult P, Pujol N, Beaufils P. Abnormal rate of intraoperative and postoperative implant positioning outliers using “MRI-based patient-specific” compared to “computer assisted” instrumentation in total knee replacement. Knee Surg Sports Traumatol Arthrosc. 2015. [Epub ahead of print]
15. Nunley RM, Ellison BS, Zhu J, Ruh EL, Howell SM, Barrack RL. Do patient-specific guides improve coronal alignment in total knee arthroplasty? Clin Orthop Relat Res. 2012;470(3):895-902.
16. Nunley RM, Ellison BS, Ruh EL, et al. Are patient-specific cutting blocks cost-effective for total knee arthroplasty? Clin Orthop Relat Res. 2012;470(3):889-894.
17. Barrack RL, Ruh EL, Williams BM, Ford AD, Foreman K, Nunley RM. Patient specific cutting blocks are currently of no proven value. J Bone Joint Surg Br. 2012;94(11 Suppl A):95-99.
18. Chen JY, Chin PL, Tay DK, Chia SL, Lo NN, Yeo SJ. Functional outcome and quality of life after patient-specific instrumentation in total knee arthroplasty. J Arthroplasty. 2015;30(10):1724-1728.
19. Goyal N, Patel AR, Yaffe MA, Luo MY, Stulberg SD. Does implant design influence the accuracy of patient specific instrumentation in total knee arthroplasty? J Arthroplasty. 2015;30(9):1526-1530.
20. Bauwens K, Matthes G, Wich M, et al. Navigated total knee replacement. A meta-analysis. J Bone Joint Surg Am. 2007;89(2):261-269.
21. Scuderi GR, Fallaha M, Masse V, Lavigne P, Amiot LP, Berthiaume MJ. Total knee arthroplasty with a novel navigation system within the surgical field. Orthop Clin North Am. 2014;45(2):167-173.
22. Goh GS, Liow MH, Lim WS, Tay DK, Yeo SJ, Tan MH. Accelerometer-based navigation is as accurate as optical computer navigation in restoring the joint line and mechanical axis after total knee arthroplasty: a prospective matched study. J Arthroplasty. 2016;31(1):92-97.
23. Berend KR, Lombardi AV Jr. Liberal indications for minimally invasive oxford unicondylar arthroplasty provide rapid functional recovery and pain relief. Surg Technol Int. 2007;16:193-197.
24. Nam D, Jerabek SA, Cross MB, Mayman DJ. Cadaveric analysis of an accelerometer-based portable navigation device for distal femoral cutting block alignment in total knee arthroplasty. Comput Aided Surg. 2012;17(4):205-210.
25. Nam D, Cody EA, Nguyen JT, Figgie MP, Mayman DJ. Extramedullary guides versus portable, accelerometer-based navigation for tibial alignment in total knee arthroplasty: a randomized, controlled trial: winner of the 2013 HAP PAUL award. J Arthroplasty. 2014;29(2):288-294.
26. Bugbee WD, Kermanshahi AY, Munro MM, McCauley JC, Copp SN. Accuracy of a hand-held surgical navigation system for tibial resection in total knee arthroplasty. Knee. 2014;21(6):1225-1228.
27. Schai PA, Thornhill TS, Scott RD. Total knee arthroplasty with the PFC system. Results at a minimum of ten years and survivorship analysis. J Bone Joint Surg Br. 1998;80(5):850-858.
28. Pradhan NR, Gambhir A, Porter ML. Survivorship analysis of 3234 primary knee arthroplasties implanted over a 26-year period: a study of eight different implant designs. Knee. 2006;13(1):7-11.
29. Sharkey PF, Hozack WJ, Rothman RH, Shastri S, Jacoby SM. Insall Award paper. Why are total knee arthroplasties failing today? Clin Orthop Relat Res. 2002;404:7-13.
30. Fang DM, Ritter MA, Davis KE. Coronal alignment in total knee arthroplasty: just how important is it? J Arthroplasty. 2009;24(6 Suppl):39-43.
31. Cherian JJ, Kapadia BH, Banerjee S, Jauregui JJ, Issa K, Mont MA. Mechanical, anatomical, and kinematic axis in TKA: concepts and practical applications. Curr Rev Musculoskelet Med. 2014;7(2):89-95.
32. Howell SM, Papadopoulos S, Kuznik K, Ghaly LR, Hull ML. Does varus alignment adversely affect implant survival and function six years after kinematically aligned total knee arthroplasty? Int Orthop. 2015;39(11):2117-2124.
33. Ritter MA, Faris PM, Keating EM, Meding JB. Postoperative alignment of total knee replacement. Its effect on survival. Clin Orthop Relat Res. 1994;299:153-156.
34. Huang EH, Copp SN, Bugbee WD. Accuracy of a handheld accelerometer-based navigation system for femoral and tibial resection in total knee arthroplasty. J Arthroplasty. 2015;30(11):1906-1910.
1. Kurtz SM, Ong KL, Lau E, Bozic KJ. Impact of the economic downturn on total joint replacement demand in the United States: updated projections to 2021. J Bone Joint Surg Am. 2014;96(8):624-630.
2. Bourne RB, Chesworth BM, Davis AM, Mahomed NN, Charron KD. Patient satisfaction after total knee arthroplasty: who is satisfied and who is not? Clin Orthop Relat Res. 2010;468(1):57-63.
3. Schroer WC, Berend KR, Lombardi AV, et al. Why are total knees failing today? Etiology of total knee revision in 2010 and 2011. J Arthroplasty. 2013;28( 8 Suppl):116-119.
4. Sassoon A, Nam D, Nunley R, Barrack R. Systematic review of patient-specific instrumentation in total knee arthroplasty: new but not improved. Clin Orthop Relat Res. 2015;473(1):151-158.
5. Anderson KC, Buehler KC, Markel DC. Computer assisted navigation in total knee arthroplasty: comparison with conventional methods. J Arthroplasty. 2005;20(7 Suppl 3):132-138.
6. Mason JB, Fehring TK, Estok R, Banel D, Fahrbach K. Meta-analysis of alignment outcomes in computer-assisted total knee arthroplasty surgery. J Arthroplasty. 2007;22(8):1097-1106.
7. Khakha RS, Chowdhry M, Sivaprakasam M, Kheiran A, Chauhan SK. Radiological and functional outcomes in computer assisted total knee arthroplasty between consultants and trainees - a prospective randomized controlled trial. J Arthroplasty. 2015;30(8):1344-1347.
8. Zhu M, Ang CL, Yeo SJ, Lo NN, Chia SL, Chong HC. Minimally invasive computer-assisted total knee arthroplasty compared with conventional total knee arthroplasty: a prospective 9-year follow-up. J Arthroplasty. 2015. [Epub ahead of print]
9. Roberts TD, Clatworthy MG, Frampton CM, Young SW. Does computer assisted navigation improve functional outcomes and implant survivability after total knee arthroplasty? J Arthroplasty. 2015;30(9 Suppl):59-63.
10. de Steiger RN, Liu YL, Graves SE. Computer navigation for total knee arthroplasty reduces revision rate for patients less than sixty-five years of age. J Bone Joint Surg Am. 2015;97(8):635-642.
11. Fehring TK, Mason JB, Moskal J, Pollock DC, Mann J, Williams VJ. When computer-assisted knee replacement is the best alternative. Clin Orthop Relat Res. 2006;452:132-136.
12. Iorio R, Mazza D, Drogo P, et al. Clinical and radiographic outcomes of an accelerometer-based system for the tibial resection in total knee arthroplasty. Int Orthop. 2015;39(3):461-466.
13. Haaker RG, Stockheim M, Kamp M, Proff G, Breitenfelder J, Ottersbach A. Computer-assisted navigation increases precision of component placement in total knee arthroplasty. Clin Orthop Relat Res. 2005;433:152-159.
14. Ollivier M, Tribot-Laspiere Q, Amzallag J, Boisrenoult P, Pujol N, Beaufils P. Abnormal rate of intraoperative and postoperative implant positioning outliers using “MRI-based patient-specific” compared to “computer assisted” instrumentation in total knee replacement. Knee Surg Sports Traumatol Arthrosc. 2015. [Epub ahead of print]
15. Nunley RM, Ellison BS, Zhu J, Ruh EL, Howell SM, Barrack RL. Do patient-specific guides improve coronal alignment in total knee arthroplasty? Clin Orthop Relat Res. 2012;470(3):895-902.
16. Nunley RM, Ellison BS, Ruh EL, et al. Are patient-specific cutting blocks cost-effective for total knee arthroplasty? Clin Orthop Relat Res. 2012;470(3):889-894.
17. Barrack RL, Ruh EL, Williams BM, Ford AD, Foreman K, Nunley RM. Patient specific cutting blocks are currently of no proven value. J Bone Joint Surg Br. 2012;94(11 Suppl A):95-99.
18. Chen JY, Chin PL, Tay DK, Chia SL, Lo NN, Yeo SJ. Functional outcome and quality of life after patient-specific instrumentation in total knee arthroplasty. J Arthroplasty. 2015;30(10):1724-1728.
19. Goyal N, Patel AR, Yaffe MA, Luo MY, Stulberg SD. Does implant design influence the accuracy of patient specific instrumentation in total knee arthroplasty? J Arthroplasty. 2015;30(9):1526-1530.
20. Bauwens K, Matthes G, Wich M, et al. Navigated total knee replacement. A meta-analysis. J Bone Joint Surg Am. 2007;89(2):261-269.
21. Scuderi GR, Fallaha M, Masse V, Lavigne P, Amiot LP, Berthiaume MJ. Total knee arthroplasty with a novel navigation system within the surgical field. Orthop Clin North Am. 2014;45(2):167-173.
22. Goh GS, Liow MH, Lim WS, Tay DK, Yeo SJ, Tan MH. Accelerometer-based navigation is as accurate as optical computer navigation in restoring the joint line and mechanical axis after total knee arthroplasty: a prospective matched study. J Arthroplasty. 2016;31(1):92-97.
23. Berend KR, Lombardi AV Jr. Liberal indications for minimally invasive oxford unicondylar arthroplasty provide rapid functional recovery and pain relief. Surg Technol Int. 2007;16:193-197.
24. Nam D, Jerabek SA, Cross MB, Mayman DJ. Cadaveric analysis of an accelerometer-based portable navigation device for distal femoral cutting block alignment in total knee arthroplasty. Comput Aided Surg. 2012;17(4):205-210.
25. Nam D, Cody EA, Nguyen JT, Figgie MP, Mayman DJ. Extramedullary guides versus portable, accelerometer-based navigation for tibial alignment in total knee arthroplasty: a randomized, controlled trial: winner of the 2013 HAP PAUL award. J Arthroplasty. 2014;29(2):288-294.
26. Bugbee WD, Kermanshahi AY, Munro MM, McCauley JC, Copp SN. Accuracy of a hand-held surgical navigation system for tibial resection in total knee arthroplasty. Knee. 2014;21(6):1225-1228.
27. Schai PA, Thornhill TS, Scott RD. Total knee arthroplasty with the PFC system. Results at a minimum of ten years and survivorship analysis. J Bone Joint Surg Br. 1998;80(5):850-858.
28. Pradhan NR, Gambhir A, Porter ML. Survivorship analysis of 3234 primary knee arthroplasties implanted over a 26-year period: a study of eight different implant designs. Knee. 2006;13(1):7-11.
29. Sharkey PF, Hozack WJ, Rothman RH, Shastri S, Jacoby SM. Insall Award paper. Why are total knee arthroplasties failing today? Clin Orthop Relat Res. 2002;404:7-13.
30. Fang DM, Ritter MA, Davis KE. Coronal alignment in total knee arthroplasty: just how important is it? J Arthroplasty. 2009;24(6 Suppl):39-43.
31. Cherian JJ, Kapadia BH, Banerjee S, Jauregui JJ, Issa K, Mont MA. Mechanical, anatomical, and kinematic axis in TKA: concepts and practical applications. Curr Rev Musculoskelet Med. 2014;7(2):89-95.
32. Howell SM, Papadopoulos S, Kuznik K, Ghaly LR, Hull ML. Does varus alignment adversely affect implant survival and function six years after kinematically aligned total knee arthroplasty? Int Orthop. 2015;39(11):2117-2124.
33. Ritter MA, Faris PM, Keating EM, Meding JB. Postoperative alignment of total knee replacement. Its effect on survival. Clin Orthop Relat Res. 1994;299:153-156.
34. Huang EH, Copp SN, Bugbee WD. Accuracy of a handheld accelerometer-based navigation system for femoral and tibial resection in total knee arthroplasty. J Arthroplasty. 2015;30(11):1906-1910.
Bullying
A mentor told me during my pediatrics residency that going to school is “the main job of a teenager.” This is because at school, teenagers will be spending the majority of their time and energy learning and growing to become a thriving adult. However, the school environment matters. We are familiar with how excellent teachers, the availability of tutoring, and an administration dedicated to academic achievement play a big role. We also should be aware that if teenagers feel unsafe going to school – especially if they are victims of bullying – they are unable to take advantage of these resources.
Bullying is a repetitive, unwanted, and aggressive behavior among children and adolescents that involves a real or perceived power imbalance.1 Despite the increasing visibility of lesbian, gay, bisexual, and transgender (LGBT) individuals, bullying remains a serious problem for this population. Although between one in four and one in three of all youth experience bullying,2 according to the Youth Risk Behavior Survey, LGBT students are two to four times as likely to be threatened or injured with a weapon on school property, two to three times as likely not to go to school because they feel unsafe, and about two times as likely to be bullied at school, compared with their heterosexual peers.3 Alarmingly, more than half of transgender students experience bullying and harassment at school.4
A key component of bullying is the power imbalance. Bullying perpetrators feel that they have more power physically (e.g., in size) or socially (e.g., in social status).5 LGBT youth are often the victims of bullying because of the societal stigma against same-sex attraction or gender nonconformity. As a result, they tend to have a lower social status, putting them at risk for bullying. Remember, however, that this power imbalance is perceived. Even straight teenagers can be victims of antigay and antitrans bullying because they don’t conform to gender norms (e.g., a straight boy interested in theater instead of sports).6 Therefore, any teenager can be a victim of antigay and antitrans bullying.
Although many believe that experiencing bullying is a “rite of passage,” a look at the research on bullying contradicts this. Youth who experience bullying have higher rates of depression, loneliness, and, most worrisome of all, suicide.7,8 One study showed that LGBT youth who experience bullying are almost six times as likely to consider suicide.9 Such sobering statistics prove that bullying is harmful. Furthermore, the effects of bullying can last into adulthood. One study showed that LGBT youth who experienced bullying during high school are more likely to have depressive symptoms and to be dissatisfied with life as a young adult.10 If rites of passage are designed to make a teenager into a well-adjusted young adult, then bullying does a poor job.
Although antigay bullying and harassment occur outside the clinic, providers can encounter both the perpetrator and the victim as patients and not realize it. Providers who have patients at risk for bullying – such as LGBT or gender-nonconforming youth – should routinely ask them about bullying through such questions as:
• “How many good friends do you have in school?”
• “Do you ever feel afraid to go to school? Why?”
• “Do other kids ever bully you at school, in your neighborhood, or online? Who bullies you?
• When and where does it happen? What do they say or do?”11
Asking these questions is especially important if you or your patient’s caregivers notice school phobia, attention problems, or psychosomatic complaints.11 Once you identify a victim, refer the patient to a mental health provider to develop skills to cope with the stress of bullying. Such skills include how to make friends. Emphasize that it is not the victim’s fault that they are experiencing bullying. Avoid telling victims to fight back or “suck it up.” In addition, work with parents and school authorities to intervene on behalf of the child to stop the bullying behavior.
At the same time, it is especially important to identify perpetrators. Perpetrators tend to have conduct problems, increased depressive symptoms, and poor school adjustment.12 They may have been bullied themselves. Also refer perpetrators to a mental health provider and other resources to address these problems.
However, with your limited time to screen for bullying or to create an individualized plan to protect bullying victims, approaches to reducing bullying and their adverse effects require a community effort. Use your expertise and access to the latest scientific research to advocate and help create policies schools can use to address antigay bullying. Clark and Tilly recommend a three-tier approach in addressing antigay bullying. In the first tier, schools should create a safe and affirmative environment for all students. An example of such an approach is to have a speaker – such as a physician from the community – talking to students about bullying and encouraging bystanders to speak up (i.e., be an ally) for bullying victims. Although some schools may be hesitant to implement a schoolwide intervention, they may implement a second-tier approach, such as classroom curricula on how to be an ally or incentive programs for helping vulnerable students (e.g., tutoring). Finally, the third tier requires intensive individualized interventions for bullying victims. Schools should have a step-by-step plan involving school authorities that students and their parents can use if students are experiencing bullying.13 Implementation of this plan requires timely follow-up from school officials to ensure cessation of the bullying behavior.10
Another way you can advocate for your LGBT patients is to be knowledgeable about the laws surrounding bullying. Bullying laws vary according to state. This is especially true if such laws specifically prohibit bullying based on sexual orientation or gender identity. This is known as “enumeration.” Enumerated laws grant school authorities the power to prevent and to correct any bullying based on sexual orientation and gender identity. Currently, 18 states and the District of Columbia have enumerated antibullying laws.14 If you live in a state that does not have an enumerated antibullying law, you can contact your state government officials to urge them to pass such a law.
Bullying has a powerful impact on the health and well-being of LGBT youth. Screen for bullying in your LGBT patients and work with schools and parents to protect them from such behaviors. Most importantly, advocate for creating a safe school environment for LGBT youth so that they can focus on their main job of learning and becoming a thriving adult.
Resources
• The website www.stopbullying.gov is a comprehensive resource for bullying and how to address it.
• Society of Adolescent Health & Medicine (SAHM) position statement on bullying (J Adolesc Health. 2005 Jan;36[1]:88-91).
• American Academy of Pediatrics (AAP) position statement on bullying (Pediatrics. 2009 July. doi: 10.1542/peds.2009-0943).
• Gay, Lesbian & Straight Education Network (GLSEN) information on enumerated antibullying laws by state (www.glsen.org/article/state-maps).
References
1. Bullying definition at www.stopbullying.gov.
3. J Adolesc Health. 2014 Sep;55(3):432-8.
5. Can Fam Physician. 2009 Apr;55(4):356-60.
6. J Adolesc Health. 2016 Feb;58(2):S1-S2.
7. Pediatrics. 2003;111(6 Pt 1):1312-7.
8. Journal of Educational Psychology. 2000 Jun;92(2):349-59.
9. Prev Sci. 2015 Apr;16(3):451-62.
10. Dev Psychol. 2010 Nov;46(6):1580-9.
11. Roles for pediatricians in bullying prevention and intervention (www.stopbullying.gov/resources-files/roles-for-pediatricians-tipsheet.pdf).
12. J Adolesc Health. 2005 Jan;36(1):88-91.
13. Clark JP, Tilly, WD. The evolution of response to intervention. In: Clark JP, Alvarez, Michelle, ed. Response to intervention: A guide for school social worker. (New York: Oxford University Press; 2010:3-18).
14. Enumerated antibullying laws by state(www.glsen.org/article/state-maps).
Dr. Montano is an adolescent medicine fellow at Children’s Hospital of Pittsburgh of UPMC and a postdoctoral fellow in the department of pediatrics at the University of Pittsburgh.
A mentor told me during my pediatrics residency that going to school is “the main job of a teenager.” This is because at school, teenagers will be spending the majority of their time and energy learning and growing to become a thriving adult. However, the school environment matters. We are familiar with how excellent teachers, the availability of tutoring, and an administration dedicated to academic achievement play a big role. We also should be aware that if teenagers feel unsafe going to school – especially if they are victims of bullying – they are unable to take advantage of these resources.
Bullying is a repetitive, unwanted, and aggressive behavior among children and adolescents that involves a real or perceived power imbalance.1 Despite the increasing visibility of lesbian, gay, bisexual, and transgender (LGBT) individuals, bullying remains a serious problem for this population. Although between one in four and one in three of all youth experience bullying,2 according to the Youth Risk Behavior Survey, LGBT students are two to four times as likely to be threatened or injured with a weapon on school property, two to three times as likely not to go to school because they feel unsafe, and about two times as likely to be bullied at school, compared with their heterosexual peers.3 Alarmingly, more than half of transgender students experience bullying and harassment at school.4
A key component of bullying is the power imbalance. Bullying perpetrators feel that they have more power physically (e.g., in size) or socially (e.g., in social status).5 LGBT youth are often the victims of bullying because of the societal stigma against same-sex attraction or gender nonconformity. As a result, they tend to have a lower social status, putting them at risk for bullying. Remember, however, that this power imbalance is perceived. Even straight teenagers can be victims of antigay and antitrans bullying because they don’t conform to gender norms (e.g., a straight boy interested in theater instead of sports).6 Therefore, any teenager can be a victim of antigay and antitrans bullying.
Although many believe that experiencing bullying is a “rite of passage,” a look at the research on bullying contradicts this. Youth who experience bullying have higher rates of depression, loneliness, and, most worrisome of all, suicide.7,8 One study showed that LGBT youth who experience bullying are almost six times as likely to consider suicide.9 Such sobering statistics prove that bullying is harmful. Furthermore, the effects of bullying can last into adulthood. One study showed that LGBT youth who experienced bullying during high school are more likely to have depressive symptoms and to be dissatisfied with life as a young adult.10 If rites of passage are designed to make a teenager into a well-adjusted young adult, then bullying does a poor job.
Although antigay bullying and harassment occur outside the clinic, providers can encounter both the perpetrator and the victim as patients and not realize it. Providers who have patients at risk for bullying – such as LGBT or gender-nonconforming youth – should routinely ask them about bullying through such questions as:
• “How many good friends do you have in school?”
• “Do you ever feel afraid to go to school? Why?”
• “Do other kids ever bully you at school, in your neighborhood, or online? Who bullies you?
• When and where does it happen? What do they say or do?”11
Asking these questions is especially important if you or your patient’s caregivers notice school phobia, attention problems, or psychosomatic complaints.11 Once you identify a victim, refer the patient to a mental health provider to develop skills to cope with the stress of bullying. Such skills include how to make friends. Emphasize that it is not the victim’s fault that they are experiencing bullying. Avoid telling victims to fight back or “suck it up.” In addition, work with parents and school authorities to intervene on behalf of the child to stop the bullying behavior.
At the same time, it is especially important to identify perpetrators. Perpetrators tend to have conduct problems, increased depressive symptoms, and poor school adjustment.12 They may have been bullied themselves. Also refer perpetrators to a mental health provider and other resources to address these problems.
However, with your limited time to screen for bullying or to create an individualized plan to protect bullying victims, approaches to reducing bullying and their adverse effects require a community effort. Use your expertise and access to the latest scientific research to advocate and help create policies schools can use to address antigay bullying. Clark and Tilly recommend a three-tier approach in addressing antigay bullying. In the first tier, schools should create a safe and affirmative environment for all students. An example of such an approach is to have a speaker – such as a physician from the community – talking to students about bullying and encouraging bystanders to speak up (i.e., be an ally) for bullying victims. Although some schools may be hesitant to implement a schoolwide intervention, they may implement a second-tier approach, such as classroom curricula on how to be an ally or incentive programs for helping vulnerable students (e.g., tutoring). Finally, the third tier requires intensive individualized interventions for bullying victims. Schools should have a step-by-step plan involving school authorities that students and their parents can use if students are experiencing bullying.13 Implementation of this plan requires timely follow-up from school officials to ensure cessation of the bullying behavior.10
Another way you can advocate for your LGBT patients is to be knowledgeable about the laws surrounding bullying. Bullying laws vary according to state. This is especially true if such laws specifically prohibit bullying based on sexual orientation or gender identity. This is known as “enumeration.” Enumerated laws grant school authorities the power to prevent and to correct any bullying based on sexual orientation and gender identity. Currently, 18 states and the District of Columbia have enumerated antibullying laws.14 If you live in a state that does not have an enumerated antibullying law, you can contact your state government officials to urge them to pass such a law.
Bullying has a powerful impact on the health and well-being of LGBT youth. Screen for bullying in your LGBT patients and work with schools and parents to protect them from such behaviors. Most importantly, advocate for creating a safe school environment for LGBT youth so that they can focus on their main job of learning and becoming a thriving adult.
Resources
• The website www.stopbullying.gov is a comprehensive resource for bullying and how to address it.
• Society of Adolescent Health & Medicine (SAHM) position statement on bullying (J Adolesc Health. 2005 Jan;36[1]:88-91).
• American Academy of Pediatrics (AAP) position statement on bullying (Pediatrics. 2009 July. doi: 10.1542/peds.2009-0943).
• Gay, Lesbian & Straight Education Network (GLSEN) information on enumerated antibullying laws by state (www.glsen.org/article/state-maps).
References
1. Bullying definition at www.stopbullying.gov.
3. J Adolesc Health. 2014 Sep;55(3):432-8.
5. Can Fam Physician. 2009 Apr;55(4):356-60.
6. J Adolesc Health. 2016 Feb;58(2):S1-S2.
7. Pediatrics. 2003;111(6 Pt 1):1312-7.
8. Journal of Educational Psychology. 2000 Jun;92(2):349-59.
9. Prev Sci. 2015 Apr;16(3):451-62.
10. Dev Psychol. 2010 Nov;46(6):1580-9.
11. Roles for pediatricians in bullying prevention and intervention (www.stopbullying.gov/resources-files/roles-for-pediatricians-tipsheet.pdf).
12. J Adolesc Health. 2005 Jan;36(1):88-91.
13. Clark JP, Tilly, WD. The evolution of response to intervention. In: Clark JP, Alvarez, Michelle, ed. Response to intervention: A guide for school social worker. (New York: Oxford University Press; 2010:3-18).
14. Enumerated antibullying laws by state(www.glsen.org/article/state-maps).
Dr. Montano is an adolescent medicine fellow at Children’s Hospital of Pittsburgh of UPMC and a postdoctoral fellow in the department of pediatrics at the University of Pittsburgh.
A mentor told me during my pediatrics residency that going to school is “the main job of a teenager.” This is because at school, teenagers will be spending the majority of their time and energy learning and growing to become a thriving adult. However, the school environment matters. We are familiar with how excellent teachers, the availability of tutoring, and an administration dedicated to academic achievement play a big role. We also should be aware that if teenagers feel unsafe going to school – especially if they are victims of bullying – they are unable to take advantage of these resources.
Bullying is a repetitive, unwanted, and aggressive behavior among children and adolescents that involves a real or perceived power imbalance.1 Despite the increasing visibility of lesbian, gay, bisexual, and transgender (LGBT) individuals, bullying remains a serious problem for this population. Although between one in four and one in three of all youth experience bullying,2 according to the Youth Risk Behavior Survey, LGBT students are two to four times as likely to be threatened or injured with a weapon on school property, two to three times as likely not to go to school because they feel unsafe, and about two times as likely to be bullied at school, compared with their heterosexual peers.3 Alarmingly, more than half of transgender students experience bullying and harassment at school.4
A key component of bullying is the power imbalance. Bullying perpetrators feel that they have more power physically (e.g., in size) or socially (e.g., in social status).5 LGBT youth are often the victims of bullying because of the societal stigma against same-sex attraction or gender nonconformity. As a result, they tend to have a lower social status, putting them at risk for bullying. Remember, however, that this power imbalance is perceived. Even straight teenagers can be victims of antigay and antitrans bullying because they don’t conform to gender norms (e.g., a straight boy interested in theater instead of sports).6 Therefore, any teenager can be a victim of antigay and antitrans bullying.
Although many believe that experiencing bullying is a “rite of passage,” a look at the research on bullying contradicts this. Youth who experience bullying have higher rates of depression, loneliness, and, most worrisome of all, suicide.7,8 One study showed that LGBT youth who experience bullying are almost six times as likely to consider suicide.9 Such sobering statistics prove that bullying is harmful. Furthermore, the effects of bullying can last into adulthood. One study showed that LGBT youth who experienced bullying during high school are more likely to have depressive symptoms and to be dissatisfied with life as a young adult.10 If rites of passage are designed to make a teenager into a well-adjusted young adult, then bullying does a poor job.
Although antigay bullying and harassment occur outside the clinic, providers can encounter both the perpetrator and the victim as patients and not realize it. Providers who have patients at risk for bullying – such as LGBT or gender-nonconforming youth – should routinely ask them about bullying through such questions as:
• “How many good friends do you have in school?”
• “Do you ever feel afraid to go to school? Why?”
• “Do other kids ever bully you at school, in your neighborhood, or online? Who bullies you?
• When and where does it happen? What do they say or do?”11
Asking these questions is especially important if you or your patient’s caregivers notice school phobia, attention problems, or psychosomatic complaints.11 Once you identify a victim, refer the patient to a mental health provider to develop skills to cope with the stress of bullying. Such skills include how to make friends. Emphasize that it is not the victim’s fault that they are experiencing bullying. Avoid telling victims to fight back or “suck it up.” In addition, work with parents and school authorities to intervene on behalf of the child to stop the bullying behavior.
At the same time, it is especially important to identify perpetrators. Perpetrators tend to have conduct problems, increased depressive symptoms, and poor school adjustment.12 They may have been bullied themselves. Also refer perpetrators to a mental health provider and other resources to address these problems.
However, with your limited time to screen for bullying or to create an individualized plan to protect bullying victims, approaches to reducing bullying and their adverse effects require a community effort. Use your expertise and access to the latest scientific research to advocate and help create policies schools can use to address antigay bullying. Clark and Tilly recommend a three-tier approach in addressing antigay bullying. In the first tier, schools should create a safe and affirmative environment for all students. An example of such an approach is to have a speaker – such as a physician from the community – talking to students about bullying and encouraging bystanders to speak up (i.e., be an ally) for bullying victims. Although some schools may be hesitant to implement a schoolwide intervention, they may implement a second-tier approach, such as classroom curricula on how to be an ally or incentive programs for helping vulnerable students (e.g., tutoring). Finally, the third tier requires intensive individualized interventions for bullying victims. Schools should have a step-by-step plan involving school authorities that students and their parents can use if students are experiencing bullying.13 Implementation of this plan requires timely follow-up from school officials to ensure cessation of the bullying behavior.10
Another way you can advocate for your LGBT patients is to be knowledgeable about the laws surrounding bullying. Bullying laws vary according to state. This is especially true if such laws specifically prohibit bullying based on sexual orientation or gender identity. This is known as “enumeration.” Enumerated laws grant school authorities the power to prevent and to correct any bullying based on sexual orientation and gender identity. Currently, 18 states and the District of Columbia have enumerated antibullying laws.14 If you live in a state that does not have an enumerated antibullying law, you can contact your state government officials to urge them to pass such a law.
Bullying has a powerful impact on the health and well-being of LGBT youth. Screen for bullying in your LGBT patients and work with schools and parents to protect them from such behaviors. Most importantly, advocate for creating a safe school environment for LGBT youth so that they can focus on their main job of learning and becoming a thriving adult.
Resources
• The website www.stopbullying.gov is a comprehensive resource for bullying and how to address it.
• Society of Adolescent Health & Medicine (SAHM) position statement on bullying (J Adolesc Health. 2005 Jan;36[1]:88-91).
• American Academy of Pediatrics (AAP) position statement on bullying (Pediatrics. 2009 July. doi: 10.1542/peds.2009-0943).
• Gay, Lesbian & Straight Education Network (GLSEN) information on enumerated antibullying laws by state (www.glsen.org/article/state-maps).
References
1. Bullying definition at www.stopbullying.gov.
3. J Adolesc Health. 2014 Sep;55(3):432-8.
5. Can Fam Physician. 2009 Apr;55(4):356-60.
6. J Adolesc Health. 2016 Feb;58(2):S1-S2.
7. Pediatrics. 2003;111(6 Pt 1):1312-7.
8. Journal of Educational Psychology. 2000 Jun;92(2):349-59.
9. Prev Sci. 2015 Apr;16(3):451-62.
10. Dev Psychol. 2010 Nov;46(6):1580-9.
11. Roles for pediatricians in bullying prevention and intervention (www.stopbullying.gov/resources-files/roles-for-pediatricians-tipsheet.pdf).
12. J Adolesc Health. 2005 Jan;36(1):88-91.
13. Clark JP, Tilly, WD. The evolution of response to intervention. In: Clark JP, Alvarez, Michelle, ed. Response to intervention: A guide for school social worker. (New York: Oxford University Press; 2010:3-18).
14. Enumerated antibullying laws by state(www.glsen.org/article/state-maps).
Dr. Montano is an adolescent medicine fellow at Children’s Hospital of Pittsburgh of UPMC and a postdoctoral fellow in the department of pediatrics at the University of Pittsburgh.
Transitions (The Future of Orthopedics)
A transition is underway at AJO. As we discuss the future of the “new journal,” I often think about the future of orthopedics. I’ve decided my vision of the future is centered on 3 components. First, there will be a change in our training paradigm from an apprenticeship model to standardized training, where core competencies must be demonstrated for certification. Second, robots and computers will improve our diagnostic accuracy and will allow us to perform surgery with improved component positioning, while biologics and genetic analysis will accelerate nature’s ability to heal, and perhaps regenerate, injured tissue. Finally, computerized algorithms and technologically improved surgical outcomes will allow us to deliver high-quality healthcare at a lower cost, producing the value our current health systems are striving for, and leveling the playing field between high-volume centers and rural institutions forced to offer complete service lines.
In this issue, we examine robotic-assisted arthroplasty and its role in modern healthcare. I think the best argument for robots in the operating room might come from the airline industry. I’m sitting on a plane as I write this, without once thinking about how much experience my pilot has in the cockpit. I know our pilot has demonstrated the core competencies required to safely operate the plane, trained on emergency simulations, and logged the necessary hours before being handed the controls. I also know that the instrumentation is so good that the plane can essentially fly itself, making pilot skill and experience less relevant. In short, technology has, in all but rare circumstances, made our pilots virtually interchangeable.
Unfortunately, none of the above is true in orthopedics. Our residents are not required to demonstrate their skills before any licensing authority, simulator training is not available in all programs, and we’ve limited resident work hours. Yet it’s that same interchangeability that most healthcare models assume. No one argues that high-volume centers have better results when it comes to arthroplasty, but only a small percentage of total joints are currently performed at these centers. Surgeon training remains a virtual apprenticeship, lacking standardization, and resulting in a wide variation in skill and experience. Surgical residencies are not awarded based on dexterity, and work hour restrictions, Relative Value Unit-based academic contracts, patient expectations, and staffing pressures can lead to reduced hands-on experience for trainees. The results: an entire generation of surgeons with decreased repetitions in the operating room when compared to their predecessors.
That’s why I believe we are on the cusp of a transition in the operating room, and that computer-assisted surgery is here to stay. While studies exist showing robots have tighter control over virtually every identifiable metric, little data currently exists supporting enhanced long-term outcomes. But as long as component malposition remains a leading cause of early failure, there will be a place for technologies that enhance accuracy of component placement. At odds with the drive for increased technology is the necessity of cost containment, leading us to question the value of robotic-assisted surgery, and whether the improved metrics are clinically important and the additional potential complications are worth the risk.
In the articles in this issue, we will take a critical look at the benefits and drawbacks of robotic surgery. As you read, think about the future of orthopedics and how you will implement new technology into your practice. A transition is coming, and I invite each of you to consider leading it.
A transition is underway at AJO. As we discuss the future of the “new journal,” I often think about the future of orthopedics. I’ve decided my vision of the future is centered on 3 components. First, there will be a change in our training paradigm from an apprenticeship model to standardized training, where core competencies must be demonstrated for certification. Second, robots and computers will improve our diagnostic accuracy and will allow us to perform surgery with improved component positioning, while biologics and genetic analysis will accelerate nature’s ability to heal, and perhaps regenerate, injured tissue. Finally, computerized algorithms and technologically improved surgical outcomes will allow us to deliver high-quality healthcare at a lower cost, producing the value our current health systems are striving for, and leveling the playing field between high-volume centers and rural institutions forced to offer complete service lines.
In this issue, we examine robotic-assisted arthroplasty and its role in modern healthcare. I think the best argument for robots in the operating room might come from the airline industry. I’m sitting on a plane as I write this, without once thinking about how much experience my pilot has in the cockpit. I know our pilot has demonstrated the core competencies required to safely operate the plane, trained on emergency simulations, and logged the necessary hours before being handed the controls. I also know that the instrumentation is so good that the plane can essentially fly itself, making pilot skill and experience less relevant. In short, technology has, in all but rare circumstances, made our pilots virtually interchangeable.
Unfortunately, none of the above is true in orthopedics. Our residents are not required to demonstrate their skills before any licensing authority, simulator training is not available in all programs, and we’ve limited resident work hours. Yet it’s that same interchangeability that most healthcare models assume. No one argues that high-volume centers have better results when it comes to arthroplasty, but only a small percentage of total joints are currently performed at these centers. Surgeon training remains a virtual apprenticeship, lacking standardization, and resulting in a wide variation in skill and experience. Surgical residencies are not awarded based on dexterity, and work hour restrictions, Relative Value Unit-based academic contracts, patient expectations, and staffing pressures can lead to reduced hands-on experience for trainees. The results: an entire generation of surgeons with decreased repetitions in the operating room when compared to their predecessors.
That’s why I believe we are on the cusp of a transition in the operating room, and that computer-assisted surgery is here to stay. While studies exist showing robots have tighter control over virtually every identifiable metric, little data currently exists supporting enhanced long-term outcomes. But as long as component malposition remains a leading cause of early failure, there will be a place for technologies that enhance accuracy of component placement. At odds with the drive for increased technology is the necessity of cost containment, leading us to question the value of robotic-assisted surgery, and whether the improved metrics are clinically important and the additional potential complications are worth the risk.
In the articles in this issue, we will take a critical look at the benefits and drawbacks of robotic surgery. As you read, think about the future of orthopedics and how you will implement new technology into your practice. A transition is coming, and I invite each of you to consider leading it.
A transition is underway at AJO. As we discuss the future of the “new journal,” I often think about the future of orthopedics. I’ve decided my vision of the future is centered on 3 components. First, there will be a change in our training paradigm from an apprenticeship model to standardized training, where core competencies must be demonstrated for certification. Second, robots and computers will improve our diagnostic accuracy and will allow us to perform surgery with improved component positioning, while biologics and genetic analysis will accelerate nature’s ability to heal, and perhaps regenerate, injured tissue. Finally, computerized algorithms and technologically improved surgical outcomes will allow us to deliver high-quality healthcare at a lower cost, producing the value our current health systems are striving for, and leveling the playing field between high-volume centers and rural institutions forced to offer complete service lines.
In this issue, we examine robotic-assisted arthroplasty and its role in modern healthcare. I think the best argument for robots in the operating room might come from the airline industry. I’m sitting on a plane as I write this, without once thinking about how much experience my pilot has in the cockpit. I know our pilot has demonstrated the core competencies required to safely operate the plane, trained on emergency simulations, and logged the necessary hours before being handed the controls. I also know that the instrumentation is so good that the plane can essentially fly itself, making pilot skill and experience less relevant. In short, technology has, in all but rare circumstances, made our pilots virtually interchangeable.
Unfortunately, none of the above is true in orthopedics. Our residents are not required to demonstrate their skills before any licensing authority, simulator training is not available in all programs, and we’ve limited resident work hours. Yet it’s that same interchangeability that most healthcare models assume. No one argues that high-volume centers have better results when it comes to arthroplasty, but only a small percentage of total joints are currently performed at these centers. Surgeon training remains a virtual apprenticeship, lacking standardization, and resulting in a wide variation in skill and experience. Surgical residencies are not awarded based on dexterity, and work hour restrictions, Relative Value Unit-based academic contracts, patient expectations, and staffing pressures can lead to reduced hands-on experience for trainees. The results: an entire generation of surgeons with decreased repetitions in the operating room when compared to their predecessors.
That’s why I believe we are on the cusp of a transition in the operating room, and that computer-assisted surgery is here to stay. While studies exist showing robots have tighter control over virtually every identifiable metric, little data currently exists supporting enhanced long-term outcomes. But as long as component malposition remains a leading cause of early failure, there will be a place for technologies that enhance accuracy of component placement. At odds with the drive for increased technology is the necessity of cost containment, leading us to question the value of robotic-assisted surgery, and whether the improved metrics are clinically important and the additional potential complications are worth the risk.
In the articles in this issue, we will take a critical look at the benefits and drawbacks of robotic surgery. As you read, think about the future of orthopedics and how you will implement new technology into your practice. A transition is coming, and I invite each of you to consider leading it.
Robotic-Assisted Knee Arthroplasty: An Overview
Unicompartmental knee arthroplasty (UKA) and total knee arthroplasty (TKA) are 2 reliable treatment options for patients with primary osteoarthritis. Recently published systematic reviews of cohort studies have shown that 10-year survivorship of medial and lateral UKA is 92% and 91%, respectively,1 while 10-year survivorship of TKA in cohort studies is 95%.2 National and annual registries show a similar trend, although the reported survivorship is lower.1,3-7
In order to improve these survivorship rates, the surgical variables that can intraoperatively be controlled by the orthopedic surgeon have been evaluated. These variables include lower leg alignment, soft tissue balance, joint line maintenance, and alignment, size, and fixation of the tibial and femoral component. Several studies have shown that tight control of lower leg alignment,8-14 balancing of the soft tissues,15-19 joint line maintenance,20-23 component alignment,24-28 component size,29-34 and component fixation35-40 can improve the outcomes of UKA and TKA. As a result, over the past 2 decades, several computer-assisted surgery systems have been developed with the goal of more accurate and reliable control of these factors, and thus improved outcomes of knee arthroplasty.
These systems differ with regard to the number and type of variables they control. Computer navigation systems aim to control one or more of these surgical variables, and several meta-analyses have shown that these systems, when compared to conventional surgery, improve mechanical axis accuracy, decrease the risk for mechanical axis outliers, and improve component positioning in TKA41-49 and UKA surgery.50,51 Interestingly, however, meta-analyses have failed to show the expected superiority in clinical outcomes following computer navigation compared to conventional knee arthroplasty.48,52-55 Furthermore, authors have shown that, despite the fact that computer-navigated surgery increases the accuracy of mechanical alignment and surgical cutting, there is still room for improvement.56 As a consequence, robotic-assisted systems have been developed.
Similar to computer navigation, these robotic-assisted systems aim to control the surgical variables; in addition, they aim to improve the surgical precision of the procedure. Interestingly, 2 recent studies have shown that robotic-assisted systems are superior to computer navigation systems with regard to less cutting time and less resection deviations in coronal and sagittal plane in a cadaveric study,57 and shorter total surgery time, more accurate mechanical axis, and shorter hospital stay in a clinical study.58 Although these results are promising, the exact role of robotic surgery in knee arthroplasty remains unclear. In this review, we aim to report the current state of robotic-assisted knee arthroplasty by discussing (1) the different robotic-assisted knee arthroplasty systems that are available for UKA and TKA surgery, (2) studies that assessed the role of robotic-assisted knee arthroplasty in controlling the aforementioned surgical variables, (3) cadaveric and clinical comparative studies that compared how accurate robotic-assisted and conventional knee surgery control these surgical variables, and (4) studies that assessed the cost-effectiveness of robotic-assisted knee arthroplasty surgery.
Robotic-Assisted Knee Arthroplasty Systems
Several systems have been developed over the years for knee arthroplasty, and these are usually defined as active, semi-active, or passive.59 Active systems are capable of performing tasks or processes autonomously under the watchful eye of the surgeon, while passive systems do not perform actions independently but provide the surgeon with information. In semi-active systems, the surgical action is physically constrained in order to follow a predefined strategy.
In the United States, 3 robotic systems are FDA-approved for knee arthroplasty. The Stryker/Mako haptic guided robot (Mako Surgical Corp.) was introduced in 2005 and has been used for over 50,000 UKA procedures (Figure 1). There are nearly 300 robotic systems used nationally, as it has 20% of the market share for UKA in the United States. The Mako system is a semi-active tactile robotic system that requires preoperative imaging, after which a preoperative planning is performed. Intraoperatively, the robotic arm is under direct surgeon control and gives real-time tactile feedback during the procedure (Figure 2).
Furthermore, the surgeon can intraoperatively virtually adjust component positioning and alignment and move the knee through the range of motion, after which the system can provide information on alignment, component position, and balance of the soft tissue (eg, if the knee is overtight or lax through the flexion-arch).60 This system has a burr that resects the bone and when the surgeon directs the burr outside the preplanned area, the burr stops and prevents unnecessary and unwanted resections (Figure 3).
The Navio Precision Free-Hand Sculptor (PFS) system (Blue Belt Technologies) has been used for 1500 UKA procedures, with 50 robots in use in the United States (Figure 4). This system is an image-free semi-active robotic system and has the same characteristics as the aforementioned Mako system.61 Finally, the OmniBotic robotic system (Omnilife Science) has been released for TKA and has been used for over 7300 procedures (Figure 5). This system has an automated cutting-guide technique in which the surgeon designs a virtual plan on the computer system. After this, the cutting-guides are placed by the robotic system at the planned location for all 5 femoral cuts (ie, distal, anterior chamfer, anterior, posterior chamfer, and posterior) and the surgeon then makes the final cuts.57,62
Three robotic systems for knee arthroplasty surgery have been used in Europe. The Caspar system (URS Ortho) is an active robotic system in which a computed tomography (CT) scan is performed preoperatively, after which a virtual implantation is performed on the screen. The surgeon can then obtain information on lower leg alignment, gap balancing, and component positioning, and after an operative plan is made, the surgical resections are performed by the robot. Reflective markers are attached to the leg and all robotic movements are monitored using an infrared camera system. Any undesired motion will be detected by this camera system and will stop all movements.63 A second and more frequently reported system in the literature is the active Robodoc surgical system (Curexo Technology Corporation). This system is designed for TKA and total hip arthroplasty (THA) surgery. Although initial studies reported a high incidence of system-related complications in THA,64 the use of this system for TKA has frequently been reported in the literature.56,63,65-69 A third robotic system that has been used in Europe is the Acrobot surgical system (Acrobot Company Ltd), which is an image-based semi-active robotic system70 used for both UKA and TKA surgery.70,71
Accuracy of Controlling Surgical Variables in Robotic-Assisted Knee Arthroplasty
Several studies have assessed the accuracy of robotic-assisted surgery in UKA surgery with regard to control of the aforementioned surgical variables. Pearle and colleagues72 assessed the mechanical axis accuracy of the Mako system in 10 patients undergoing medial UKA robotic-assisted surgery. They reported that the intraoperative registration lasted 7.5 minutes and the duration of time needed for robotic-assisted burring was 34.8 minutes. They compared the actual postoperative alignment at 6 weeks follow-up with the planned lower leg alignment and found that all measurements were within 1.6° of the planned lower leg alignment. Dunbar and colleagues73 assessed the accuracy of component positioning of the Mako system in 20 patients undergoing medial UKA surgery by comparing preoperative and postoperative 3-dimensional CT scans. They found that the femoral component was within 0.8 mm and 0.9° in all directions and that the tibial component was within 0.9 mm and 1.7° in all directions. They concluded that the accuracy of component positioning with the Mako system was excellent. Finally, Plate and colleagues17 assessed the accuracy of soft tissue balancing in the Mako system in 52 patients undergoing medial UKA surgery. They compared the balance plan with the soft tissue balance after implantation and the Mako system quantified soft tissue balance as the amount of mm of the knee being tight or loose at 0°, 30°, 60°, 90°, and 110° of flexion. They found that at all flexion angles the ligament balancing was accurate up to 0.53 mm of the original plan. Furthermore, they noted that in 83% of cases the accuracy was within 1 mm at all flexion angles.
For the Navio system, Smith and colleagues74 assessed the accuracy of component positioning using 20 synthetic femurs and tibia. They reported a maximum rotational error of 3.2°, an angular error of 1.46° in all orientations, and a maximum translational error of 1.18 mm for both the tibial and femoral implants. Lonner and colleagues75 assessed the accuracy of component positioning in 25 cadaveric specimens. They found similar results as were found in the study of Smith and colleagues74 and concluded that these results were similar to other semi-active robotic systems designed for UKA.
For TKA surgery, Ponder and colleagues76 assessed the accuracy of the OmniBotic system and found that the average error in the anterior-posterior dimension between the targeted and measured cuts was -0.14 mm, and that the standard deviation in guide positioning for the distal, anterior chamfer, and posterior chamfer resections was 0.03° and 0.17 mm. Koenig and colleagues62 assessed the accuracy of the OmniBotic system in the first 100 cases and found that 98% of the cases were within 3° of the neutral mechanical axis. Furthermore, they found a learning curve with regard to tourniquet time between the first and second 10 patients in which they performed robotic-assisted TKA surgery. Siebert and colleagues63 assessed the accuracy of mechanical alignment in the Caspar system in 70 patients treated with the robotic system. They found that the difference between preoperatively planned and postoperatively achieved mechanical alignment was 0.8°. Similarly, Bellemans and colleagues77 assessed mechanical alignment and the positioning and rotation of the tibial and femoral components in a clinical study of 25 cases using the Caspar system. They noted that none of the patients had mechanical alignment, tibial or femoral component positioning, or rotation beyond 1° of the neutral axis. Liow and colleagues56 assessed the accuracy of mechanical axis alignment and component sizing accuracy using the Robodoc system in 25 patients. They reported that the mean postoperative alignment was 0.4° valgus and that all cases were within 3° of the neutral mechanical axis. Furthermore, they reported a mean surgical time of 96 minutes and reported that preoperative planning yielded femoral and tibial component size accuracy of 100%.
These studies have shown that robotic systems for UKA and TKA are accurate in the surgical variables they aim to control. These studies validated tight control of mechanical axis alignment, decrease for outliers, and component positioning and rotation, and also found that the balancing of soft tissues was improved using robotic-assisted surgery.
Robotic-Assisted vs Conventional Knee Arthroplasty
Despite the fact that these systems are accurate in the variables they aim to control, these systems have to be compared to the gold standard of conventional knee arthroplasty. For UKA, Cobb and colleagues70 performed a randomized clinical trial for patients treated undergoing UKA with robotic-assistance of the Acrobot systems compared to conventional UKA and assessed differences in mechanical accuracy. A total of 27 patients were randomly assigned to one of both treatments. They found that in the group of robotic-assisted surgery, 100% of the patients had a mechanical axis within 2° of neutral, while this was only 40% in the conventional UKA groups (difference P < .001). They also assessed the increase in functional outcomes and noted a trend towards improvement in performance with increasing accuracy at 6 weeks and 3 months postoperatively. Lonner and colleagues78 also compared the tibial component positioning between robotic-assisted UKA surgery using the Mako system and conventional UKA surgery. The authors found that the variance in tibial slope, in coronal plane of the tibial component, and varus/valgus alignment were all larger with conventional UKA when compared to robotic-assisted UKA. Citak and colleagues79 compared the accuracy of tibial and femoral implant positioning between robotic-assisted surgery using the Mako system and conventional UKA in a cadaveric study. They reported that the root mean square (RMS) error of femoral component was 1.9 mm and 3.7° in robotic-assisted surgery and 5.4 mm and 10.2° for conventional UKA, while the RMS error for tibial component were 1.4 mm and 5.0° for robotic-assisted surgery and 5.7 mm and 19.2° for conventional UKA surgery. MacCallum and colleagues80 compared the tibial base plate position in a prospective clinical study of 177 patients treated with conventional UKA and 87 patients treated with robotic-assisted surgery using the Mako system. They found that surgery with robotic-assistance was more precise in the coronal and sagittal plane and was more accurate in coronal alignment when compared to conventional UKA. Finally, the first results of robotic-assisted UKA surgery have been presented. Coon and colleagues81 reported the preliminary results of a multicenter study of 854 patients and found a survivorship of 98.9% and satisfaction rate of 92% at minimum 2-year follow-up. Comparing these results to other large conventional UKA cohorts82,83 suggests that robotic-assisted surgery may improve survivorship at short-term follow-up. However, comparative studies and studies with longer follow-up are necessary to assess the additional value of robotic-assisted UKA surgery. Due to the relatively new concept of robotic-assisted surgery, these studies have not been performed or published yet.
For TKA, several studies also have compared how these robotic-systems control the surgical variables compared to conventional TKA surgery. Siebert and colleagues63 assessed mechanical axis accuracy and mechanical outliers following robotic-assisted TKA surgery using the Caspar system and conventional TKA surgery. They reported the difference between preoperative planned and postoperative achieved alignment was 0.8° for robotic-assisted surgery and 2.6° for conventional TKA surgery. Furthermore, they showed that 1 patient in the robotic-assisted group (1.4%) and 18 patients in the conventional TKA group (35%) had mechanical alignment greater than 3° from the neutral mechanical axis. Liow and colleagues56 found similar differences in their prospective randomized study in which they reported that 0% outliers greater than 3° from the neutral mechanical axis were found in the robotic-assisted group while 19.4% of the patients in the conventional TKA group had mechanical axis outliers. They also assessed the joint-line outliers in both procedures and found that 3.2% had joint-line outliers greater than 5 mm in the robotic-assisted group compared to 20.6% in the conventional TKA group. Kim and colleagues65 assessed implant accuracy in robotic-assisted surgery using the ROBODOC system and in conventional surgery and reported higher implant accuracy and fewer outliers using robotic-assisted surgery. Moon and colleagues66 compared robotic-assisted TKA surgery using the Robodoc system with conventional TKA surgery in 10 cadavers. They found that robotic-assisted surgery had excellent precision in all planes and had better accuracy in femoral rotation alignment compared to conventional TKA surgery. Park and Lee67 compared Robodoc robotic-assisted TKA surgery with conventional TKA surgery in a randomized clinical trial of 72 patients. They found that robotic-assisted surgery had definitive advantages in preoperative planning, accuracy of the procedure, and postoperative follow-up regarding femoral and tibial component flexion angles. Finally, Song and colleagues68,69 performed 2 randomized clinical trials in which they compared mechanical axis alignment, component positioning, soft tissue balancing, and patient preference between conventional TKA surgery and robotic-assisted surgery using the Robodoc system. In the first study,68 they simultaneously performed robotic-assisted surgery in one leg and conventional TKA surgery in the other leg. They found that robotic-assisted surgery resulted in less outlier in mechanical axis and component positioning. Furthermore, they found at latest follow-up of 2 years that 12 patients preferred the leg treated with robotic-assisted surgery while 6 preferred the conventional leg. Despite this finding, no significant differences in functional outcome scores were detected between both treatment options. Furthermore, they found that flexion-extension balance was achieved in 92% of patients treated with robotic-assisted TKA surgery and in 77% of patients treated with conventional TKA surgery. In the other study,69 the authors found that more patients treated with robotic-assisted surgery had <2 mm flexion-extension gap and more satisfactory posterior cruciate ligament tension when compared to conventional surgery.
These studies have shown that robotic-assisted surgery is accurate in controlling surgical variables, such as mechanical lower leg alignment, maintaining joint-line, implant positioning, and soft tissue balancing. Furthermore, these studies have shown that controlling these variables is better than the current gold standard of manual knee arthroplasty. Until now, not many studies have assessed survivorship of robotic-assisted surgery. Furthermore, no studies have, to our knowledge, compared survivorship of robotic-assisted with conventional knee replacement surgery. Finally, studies comparing functional outcomes following robotic-assisted surgery and conventional knee arthroplasty surgery are frequently underpowered due to their small sample sizes.68,70 Since many studies have shown that the surgical variables are more tightly controlled using robotic-assisted surgery when compared to conventional surgery, large comparative studies are necessary to assess the role of robotic-assisted surgery in functional outcomes and survivorship of UKA and TKA.
Cost-Effectiveness of Robotic-Assisted Surgery
High initial capital costs of robotic-assisted surgery is one of the factors that constitute a barrier to the widespread implementation of this technique. Multiple authors have suggested that improved implant survivorship afforded by robotic-assisted surgery may justify the expenditure from both societal and provider perspective.84-86 Two studies have performed a cost-effectiveness analysis for UKA surgery. Swank and colleagues84 reviewed the hospital expenditures and profits associated with robot-assisted knee arthroplasty, citing upfront costs of approximately $800,000. The authors estimated a mean per-case contribution profit of $5790 for robotic-assisted UKA, assuming an inpatient-to-outpatient ratio of 1 to 3. Based on this data, Swank and colleagues84 proposed that the capital costs of robotic-assisted UKA may be recovered in as little as 2 years when in the first 3 consecutive years 50, 70, and 90 cases were performed using robotic-assisted UKA. Moschetti and colleagues85 recently published the first formal cost-effectiveness analysis of robotic-assisted compared to manual UKA. The authors used an annual revision risk of 0.55% for the first 2 years following robot-assisted UKA, based on the aforementioned presented data by Coon and colleagues.81 They based their data on the Mako system and assumed an initial capital expenditure of $934,728 with annual servicing costs of 10% (discounted annually) for 4 years thereafter, resulting in a total cost of the robotic system of $1.362 million. These costs were divided by the number of patients estimated to undergo robotic-assisted UKA per year, which was varied to estimate the effect of case volume on cost-effectiveness. The authors reported that robotic-assisted UKA was associated with higher lifetime costs and net utilities compared to manual UKA, at an incremental cost-effectiveness ratio of $47,180 per quality-adjusted life year (QALY) in a high-volume center. This falls well within the societal willingness-to-pay threshold of $100,000/QALY. Sensitivity analysis showed that robotic-assisted UKA is cost-effective under the following conditions: (1) centers performing at least 94 cases annually, (2) in patients younger than age 67 years, and (3) 2-year revision rate does not exceed 1.2%. While the results of this initial analysis are promising, follow-up cost-effectiveness analysis studies will be required as long-term survivorship data become available.
Conclusion
Tighter control of intraoperative surgical variables, such as lower leg alignment, soft tissue balance, joint-line maintenance, and component alignment and positioning, have been associated with improved survivorship and functional outcomes. Upon reviewing the available literature on robotic-assisted surgery, it becomes clear that this technique can improve the accuracy of these surgical variables and is superior to conventional manual UKA and TKA. Although larger and comparative survivorship studies are necessary to compare robotic-assisted knee arthroplasty to conventional techniques, the early results and cost-effectiveness analysis seem promising.
1. van der List JP, McDonald LS, Pearle AD. Systematic review of medial versus lateral survivorship in unicompartmental knee arthroplasty. Knee. 2015;22(6):454-460.
2. Mont MA, Pivec R, Issa K, Kapadia BH, Maheshwari A, Harwin SF. Long-term implant survivorship of cementless total knee arthroplasty: a systematic review of the literature and meta-analysis. J Knee Surg. 2014;27(5):369-376.
3. Australian Orthopaedic Association National Joint Replacement Registry. Annual Report 2014 Australian Hip and Knee Arthroplasty Register. https://aoanjrr.sahmri.com/documents/10180/172286/Annual%20Report%202014. Accessed April 6, 2016.
4. The Swedish Knee Arthroplasty Register. Annual Report 2015 Swedish Knee Arthroplasty Register. http://www.myknee.se/pdf/SVK_2015_Eng_1.0.pdf. Published December 1, 2015. Accessed April 6, 2016.
5. Centre of excellence of joint replacements. The Norwegian Arthroplasty Register. http://nrlweb.ihelse.net/eng/Report_2010.pdf. Published June 2010. Accessed June 3, 2015.
6. National Joint Registry for England, Wales, Northern Ireland and the Isle of Man. 12th Annual Report 2015. http://www.njrcentre.org.uk/njrcentre/Portals/0/Documents/England/Reports/12th%20annual%20report/NJR%20Online%20Annual%20Report%202015.pdf. Accessed April 6, 2016.
7. The New Zealand Joint Registry. Fourteen Year Report January 1999 to December 2012. http://www.nzoa.org.nz/system/files/NJR%2014%20Year%20Report.pdf. Published November 2013. Accessed April 6, 2016.
8. Jeffery RS, Morris RW, Denham RA. Coronal alignment after total knee replacement. J Bone Joint Surg Br. 1991;73(5):709-714.
9. Rand JA, Coventry MB. Ten-year evaluation of geometric total knee arthroplasty. Clin Orthop Relat Res. 1988;232:168-173.
10. Ritter MA, Faris PM, Keating EM, Meding JB. Postoperative alignment of total knee replacement. Its effect on survival. Clin Orthop Relat Res. 1994;299:153-156.
11. Ryd L, Lindstrand A, Stenström A, Selvik G. Porous coated anatomic tricompartmental tibial components. The relationship between prosthetic position and micromotion. Clin Orthop Relat Res. 1990;251:189-197.
12. van der List JP, Chawla H, Villa JC, Zuiderbaan HA, Pearle AD. Early functional outcome after lateral UKA is sensitive to postoperative lower limb alignment. Knee Surg Sports Traumatol Arthrosc. 2015. [Epub ahead of print]
13. van der List JP, Zuiderbaan HA, Pearle AD. Why do medial unicompartmental knee arthroplasties fail today? J Arthroplasty. 2015. [Epub ahead of print]
14. Vasso M, Del Regno C, D’Amelio A, Viggiano D, Corona K, Schiavone Panni A. Minor varus alignment provides better results than neutral alignment in medial UKA. Knee. 2015;22(2):117-121.
15. Attfield SF, Wilton TJ, Pratt DJ, Sambatakakis A. Soft-tissue balance and recovery of proprioception after total knee replacement. J Bone Joint Surg Br. 1996;78(4):540-545.
16. Pagnano MW, Hanssen AD, Lewallen DG, Stuart MJ. Flexion instability after primary posterior cruciate retaining total knee arthroplasty. Clin Orthop Relat Res. 1998;356:39-46.
17. Plate JF, Mofidi A, Mannava S, et al. Achieving accurate ligament balancing using robotic-assisted unicompartmental knee arthroplasty. Adv Orthop. 2013;2013:837167.
18. Roche M, Elson L, Anderson C. Dynamic soft tissue balancing in total knee arthroplasty. Orthop Clin North Am. 2014;45(2):157-165.
19. Wasielewski RC, Galante JO, Leighty RM, Natarajan RN, Rosenberg AG. Wear patterns on retrieved polyethylene tibial inserts and their relationship to technical considerations during total knee arthroplasty. Clin Orthop Relat Res. 1994;299:31-43.
20. Ji HM, Han J, Jin DS, Seo H, Won YY. Kinematically aligned TKA can align knee joint line to horizontal. Knee Surg Sports Traumatol Arthrosc. 2016. [Epub ahead of print]
21. Khamaisy S, Zuiderbaan HA, van der List JP, Nam D, Pearle AD. Medial unicompartmental knee arthroplasty improves congruence and restores joint space width of the lateral compartment. Knee. 2016. [Epub ahead of print]
22. Niinimaki TT, Murray DW, Partanen J, Pajala A, Leppilahti JI. Unicompartmental knee arthroplasties implanted for osteoarthritis with partial loss of joint space have high re-operation rates. Knee. 2011;18(6):432-435.
23. Zuiderbaan HA, Khamaisy S, Thein R, Nawabi DH, Pearle AD. Congruence and joint space width alterations of the medial compartment following lateral unicompartmental knee arthroplasty. Bone Joint J. 2015;97-B(1):50-55.
24. Barbadoro P, Ensini A, Leardini A, et al. Tibial component alignment and risk of loosening in unicompartmental knee arthroplasty: a radiographic and radiostereometric study. Knee Surg Sports Traumatol Arthrosc. 2014;22(12):3157-3162.
25. Collier MB, Eickmann TH, Sukezaki F, McAuley JP, Engh GA. Patient, implant, and alignment factors associated with revision of medial compartment unicondylar arthroplasty. J Arthroplasty. 2006;21(6 Suppl 2):108-115.
26. Nedopil AJ, Howell SM, Hull ML. Does malrotation of the tibial and femoral components compromise function in kinematically aligned total knee arthroplasty? Orthop Clin North Am. 2016;47(1):41-50.
27. Rosskopf J, Singh PK, Wolf P, Strauch M, Graichen H. Influence of intentional femoral component flexion in navigated TKA on gap balance and sagittal anatomy. Knee Surg Sports Traumatol Arthrosc. 2014;22(3):687-693.
28. Zihlmann MS, Stacoff A, Romero J, Quervain IK, Stüssi E. Biomechanical background and clinical observations of rotational malalignment in TKA: literature review and consequences. Clin Biomech (Bristol, Avon). 2005;20(7):661-668.
29. Bonnin MP, Saffarini M, Shepherd D, Bossard N, Dantony E. Oversizing the tibial component in TKAs: incidence, consequences and risk factors. Knee Surg Sports Traumatol Arthrosc. 2015. [Epub ahead of print]
30. Bonnin MP, Schmidt A, Basiglini L, Bossard N, Dantony E. Mediolateral oversizing influences pain, function, and flexion after TKA. Knee Surg Sports Traumatol Arthrosc. 2013;21(10):2314-2324.
31. Chau R, Gulati A, Pandit H, et al. Tibial component overhang following unicompartmental knee replacement--does it matter? Knee. 2009;16(5):310-313.
32. Mueller JK, Wentorf FA, Moore RE. Femoral and tibial insert downsizing increases the laxity envelope in TKA. Knee Surg Sports Traumatol Arthrosc. 2014;22(12):3003-3011.
33. Sriphirom P, Raungthong N, Chutchawan P, Thiranon C, Sukandhavesa N. Influence of a secondary downsizing of the femoral component on the extension gap: a cadaveric study. Orthopedics. 2012;35(10 Suppl):56-59.
34. Young SW, Clarke HD, Graves SE, Liu YL, de Steiger RN. Higher rate of revision in PFC sigma primary total knee arthroplasty with mismatch of femoro-tibial component sizes. J Arthroplasty. 2015;30(5):813-817.
35. Barink M, Verdonschot N, de Waal Malefijt M. A different fixation of the femoral component in total knee arthroplasty may lead to preservation of femoral bone stock. Proc Inst Mech Eng H. 2003;217(5):325-332.
36. Eagar P, Hull ML, Howell SM. How the fixation method stiffness and initial tension affect anterior load-displacement of the knee and tension in anterior cruciate ligament grafts: a study in cadaveric knees using a double-loop hamstrings graft. J Orthop Res. 2004;22(3):613-624.
37. Fricka KB, Sritulanondha S, McAsey CJ. To cement or not? Two-year results of a prospective, randomized study comparing cemented vs. cementless total knee arthroplasty (TKA). J Arthroplasty. 2015;30(9 Suppl):55-58.
38. Kendrick BJ, Kaptein BL, Valstar ER, et al. Cemented versus cementless Oxford unicompartmental knee arthroplasty using radiostereometric analysis: a randomised controlled trial. Bone Joint J. 2015;97-B(2):185-191.
39. Kim TK, Chang CB, Kang YG, Chung BJ, Cho HJ, Seong SC. Execution accuracy of bone resection and implant fixation in computer assisted minimally invasive total knee arthroplasty. Knee. 2010;17(1):23-28.
40. Whiteside LA. Making your next unicompartmental knee arthroplasty last: three keys to success. J Arthroplasty. 2005;20(4 Suppl 2):2-3.
41. Bauwens K, Matthes G, Wich M, et al. Navigated total knee replacement. A meta-analysis. J Bone Joint Surg Am. 2007;89(2):261-269.
42. Brin YS, Nikolaou VS, Joseph L, Zukor DJ, Antoniou J. Imageless computer assisted versus conventional total knee replacement. A Bayesian meta-analysis of 23 comparative studies. Int Orthop. 2011;35(3):331-339.
43. Cheng T, Zhang G, Zhang X. Imageless navigation system does not improve component rotational alignment in total knee arthroplasty. J Surg Res. 2011;171(2):590-600.
44. Conteduca F, Iorio R, Mazza D, Ferretti A. Patient-specific instruments in total knee arthroplasty. Int Orthop. 2014;38(2):259-265.
45. Fu Y, Wang M, Liu Y, Fu Q. Alignment outcomes in navigated total knee arthroplasty: a meta-analysis. Knee Surg Sports Traumatol Arthrosc. 2012;20(6):1075-1082.
46. Hetaimish BM, Khan MM, Simunovic N, Al-Harbi HH, Bhandari M, Zalzal PK. Meta-analysis of navigation vs conventional total knee arthroplasty. J Arthroplasty. 2012;27(6):1177-1182.
47. Mason JB, Fehring TK, Estok R, Banel D, Fahrbach K. Meta-analysis of alignment outcomes in computer-assisted total knee arthroplasty surgery. J Arthroplasty. 2007;22(8):1097-1106.
48. Moskal JT, Capps SG, Mann JW, Scanelli JA. Navigated versus conventional total knee arthroplasty. J Knee Surg. 2014;27(3):235-248.
49. Shi J, Wei Y, Wang S, et al. Computer navigation and total knee arthroplasty. Orthopedics. 2014;37(1):e39-e43.
50. Nair R, Tripathy G, Deysine GR. Computer navigation systems in unicompartmental knee arthroplasty: a systematic review. Am J Orthop. 2014;43(6):256-261.
51. Weber P, Crispin A, Schmidutz F, et al. Improved accuracy in computer-assisted unicondylar knee arthroplasty: a meta-analysis. Knee Surg Sports Traumatol Arthrosc. 2013;21(11):2453-2461.
52. Alcelik IA, Blomfield MI, Diana G, Gibbon AJ, Carrington N, Burr S. A comparison of short-term outcomes of minimally invasive computer-assisted vs minimally invasive conventional instrumentation for primary total knee arthroplasty: a systematic review and meta-analysis. J Arthroplasty. 2016;31(2):410-418.
53. Cheng T, Pan XY, Mao X, Zhang GY, Zhang XL. Little clinical advantage of computer-assisted navigation over conventional instrumentation in primary total knee arthroplasty at early follow-up. Knee. 2012;19(4):237-245.
54. Rebal BA, Babatunde OM, Lee JH, Geller JA, Patrick DA Jr, Macaulay W. Imageless computer navigation in total knee arthroplasty provides superior short term functional outcomes: a meta-analysis. J Arthroplasty. 2014;29(5):938-944.
55. Zamora LA, Humphreys KJ, Watt AM, Forel D, Cameron AL. Systematic review of computer-navigated total knee arthroplasty. ANZ J Surg. 2013;83(1-2):22-30.
56. Liow MH, Xia Z, Wong MK, Tay KJ, Yeo SJ, Chin PL. Robot-assisted total knee arthroplasty accurately restores the joint line and mechanical axis. A prospective randomised study. J Arthroplasty. 2014;29(12):2373-2377.
57. Koulalis D, O’Loughlin PF, Plaskos C, Kendoff D, Cross MB, Pearle AD. Sequential versus automated cutting guides in computer-assisted total knee arthroplasty. Knee. 2011;18(6):436-442.
58. Clark TC, Schmidt FH. Robot-assisted navigation versus computer-assisted navigation in primary total knee arthroplasty: efficiency and accuracy. ISRN Orthop. 2013;2013:794827.
59. DiGioia AM 3rd, Jaramaz B, Colgan BD. Computer assisted orthopaedic surgery. Image guided and robotic assistive technologies. Clin Orthop Relat Res. 1998(354):8-16.
60. Conditt MA, Roche MW. Minimally invasive robotic-arm-guided unicompartmental knee arthroplasty. J Bone Joint Surg Am. 2009;91 Suppl 1:63-68.
61. Lonner JH. Robotically assisted unicompartmental knee arthroplasty with a handheld image-free sculpting tool. Orthop Clin North Am. 2016;47(1):29-40.
62. Koenig JA, Suero EM, Plaskos C. Surgical accuracy and efficiency of computer-navigated TKA with a robotic cutting guide–report on the first 100 cases. J Bone Joint Surg Br. 2012;94-B(SUPP XLIV):103. Available at: http://www.bjjprocs.boneandjoint.org.uk/content/94-B/SUPP_XLIV/103. Accessed April 6, 2016.
63. Siebert W, Mai S, Kober R, Heeckt PF. Technique and first clinical results of robot-assisted total knee replacement. Knee. 2002;9(3):173-180.
64. Schulz AP, Seide K, Queitsch C, et al. Results of total hip replacement using the Robodoc surgical assistant system: clinical outcome and evaluation of complications for 97 procedures. Int J Med Robot. 2007;3(4):301-306.
65. Kim SM, Park YS, Ha CW, Lim SJ, Moon YW. Robot-assisted implantation improves the precision of component position in minimally invasive TKA. Orthopedics. 2012;35(9):e1334-e1339.
66. Moon YW, Ha CW, Do KH, et al. Comparison of robot-assisted and conventional total knee arthroplasty: a controlled cadaver study using multiparameter quantitative three-dimensional CT assessment of alignment. Comput Aided Surg. 2012;17(2):86-95.
67. Park SE, Lee CT. Comparison of robotic-assisted and conventional manual implantation of a primary total knee arthroplasty. J Arthroplasty. 2007;22(7):1054-1059.
68. Song EK, Seon JK, Park SJ, Jung WB, Park HW, Lee GW. Simultaneous bilateral total knee arthroplasty with robotic and conventional techniques: a prospective, randomized study. Knee Surg Sports Traumatol Arthrosc. 2011;19(7):1069-1076.
69. Song EK, Seon JK, Yim JH, Netravali NA, Bargar WL. Robotic-assisted TKA reduces postoperative alignment outliers and improves gap balance compared to conventional TKA. Clin Orthop Relat Res. 2013;471(1):118-126.
70. Cobb J, Henckel J, Gomes P, et al. Hands-on robotic unicompartmental knee replacement: a prospective, randomised controlled study of the acrobot system. J Bone Joint Surg Br. 2006;88(2):188-197.
71. Jakopec M, Harris SJ, Rodriguez y Baena F, Gomes P, Cobb J, Davies BL. The first clinical application of a “hands-on” robotic knee surgery system. Comput Aided Surg. 2001;6(6):329-339.
72. Pearle AD, O’Loughlin PF, Kendoff DO. Robot-assisted unicompartmental knee arthroplasty. J Arthroplasty. 2010;25(2):230-237.
73. Dunbar NJ, Roche MW, Park BH, Branch SH, Conditt MA, Banks SA. Accuracy of dynamic tactile-guided unicompartmental knee arthroplasty. J Arthroplasty. 2012;27(5):803-808.e1.
74. Smith JR, Riches PE, Rowe PJ. Accuracy of a freehand sculpting tool for unicondylar knee replacement. Int J Med Robot. 2014;10(2):162-169.
75. Lonner JH, Smith JR, Picard F, Hamlin B, Rowe PJ, Riches PE. High degree of accuracy of a novel image-free handheld robot for unicondylar knee arthroplasty in a cadaveric study. Clin Orthop Relat Res. 2015;473(1):206-212.
76. Ponder C, Plaskos C, Cheal E. Press-fit total knee arthroplasty with a robotic-cutting guide: proof of concept and initial clinical experience. Bone & Joint Journal Orthopaedic Proceedings Supplement. 2013;95(SUPP 28):61. Available at: http://www.bjjprocs.boneandjoint.org.uk/content/95-B/SUPP_28/61.abstract. Accessed April 6, 2016.
77. Bellemans J, Vandenneucker H, Vanlauwe J. Robot-assisted total knee arthroplasty. Clin Orthop Relat Res. 2007;464:111-116.
78. Lonner JH, John TK, Conditt MA. Robotic arm-assisted UKA improves tibial component alignment: a pilot study. Clin Orthop Relat Res. 2010;468(1):141-146.
79. Citak M, Suero EM, Citak M, et al. Unicompartmental knee arthroplasty: is robotic technology more accurate than conventional technique? Knee. 2013;20(4):268-271.
80. MacCallum KP, Danoff JR, Geller JA. Tibial baseplate positioning in robotic-assisted and conventional unicompartmental knee arthroplasty. Eur J Orthop Surg Traumatol. 2016;26(1):93-98.
81. Coon T, Roche M, Pearle AD, Dounchis J, Borus T, Buechel F Jr. Two year survivorship of robotically guided unicompartmental knee arthroplasty. Paper presented at: International Society for Technology in Arthroplasty 26th Annual Congress; October 16-19, 2013; Palm Beach, FL.
82. Pandit H, Jenkins C, Gill HS, Barker K, Dodd CA, Murray DW. Minimally invasive Oxford phase 3 unicompartmental knee replacement: results of 1000 cases. J Bone Joint Surg Br. 2011;93(2):198-204.
83. Yoshida K, Tada M, Yoshida H, Takei S, Fukuoka S, Nakamura H. Oxford phase 3 unicompartmental knee arthroplasty in Japan--clinical results in greater than one thousand cases over ten years. J Arthroplasty. 2013;28(9 Suppl):168-171.
84. Swank ML, Alkire M, Conditt M, Lonner JH. Technology and cost-effectiveness in knee arthroplasty: computer navigation and robotics. Am J Orthop. 2009;38(2 Suppl):32-36.
85. Moschetti WE, Konopka JF, Rubash HE, Genuario JW. Can robot-assisted unicompartmental knee arthroplasty be cost-effective? A markovdecision analysis. J Arthroplasty. 2015. [Epub ahead of print]
86. Thienpont E. Improving Accuracy in Knee Arthroplasty. 1st ed. New Delhi, India: Jaypee Brothers Medical Publishers; 2012.
Unicompartmental knee arthroplasty (UKA) and total knee arthroplasty (TKA) are 2 reliable treatment options for patients with primary osteoarthritis. Recently published systematic reviews of cohort studies have shown that 10-year survivorship of medial and lateral UKA is 92% and 91%, respectively,1 while 10-year survivorship of TKA in cohort studies is 95%.2 National and annual registries show a similar trend, although the reported survivorship is lower.1,3-7
In order to improve these survivorship rates, the surgical variables that can intraoperatively be controlled by the orthopedic surgeon have been evaluated. These variables include lower leg alignment, soft tissue balance, joint line maintenance, and alignment, size, and fixation of the tibial and femoral component. Several studies have shown that tight control of lower leg alignment,8-14 balancing of the soft tissues,15-19 joint line maintenance,20-23 component alignment,24-28 component size,29-34 and component fixation35-40 can improve the outcomes of UKA and TKA. As a result, over the past 2 decades, several computer-assisted surgery systems have been developed with the goal of more accurate and reliable control of these factors, and thus improved outcomes of knee arthroplasty.
These systems differ with regard to the number and type of variables they control. Computer navigation systems aim to control one or more of these surgical variables, and several meta-analyses have shown that these systems, when compared to conventional surgery, improve mechanical axis accuracy, decrease the risk for mechanical axis outliers, and improve component positioning in TKA41-49 and UKA surgery.50,51 Interestingly, however, meta-analyses have failed to show the expected superiority in clinical outcomes following computer navigation compared to conventional knee arthroplasty.48,52-55 Furthermore, authors have shown that, despite the fact that computer-navigated surgery increases the accuracy of mechanical alignment and surgical cutting, there is still room for improvement.56 As a consequence, robotic-assisted systems have been developed.
Similar to computer navigation, these robotic-assisted systems aim to control the surgical variables; in addition, they aim to improve the surgical precision of the procedure. Interestingly, 2 recent studies have shown that robotic-assisted systems are superior to computer navigation systems with regard to less cutting time and less resection deviations in coronal and sagittal plane in a cadaveric study,57 and shorter total surgery time, more accurate mechanical axis, and shorter hospital stay in a clinical study.58 Although these results are promising, the exact role of robotic surgery in knee arthroplasty remains unclear. In this review, we aim to report the current state of robotic-assisted knee arthroplasty by discussing (1) the different robotic-assisted knee arthroplasty systems that are available for UKA and TKA surgery, (2) studies that assessed the role of robotic-assisted knee arthroplasty in controlling the aforementioned surgical variables, (3) cadaveric and clinical comparative studies that compared how accurate robotic-assisted and conventional knee surgery control these surgical variables, and (4) studies that assessed the cost-effectiveness of robotic-assisted knee arthroplasty surgery.
Robotic-Assisted Knee Arthroplasty Systems
Several systems have been developed over the years for knee arthroplasty, and these are usually defined as active, semi-active, or passive.59 Active systems are capable of performing tasks or processes autonomously under the watchful eye of the surgeon, while passive systems do not perform actions independently but provide the surgeon with information. In semi-active systems, the surgical action is physically constrained in order to follow a predefined strategy.
In the United States, 3 robotic systems are FDA-approved for knee arthroplasty. The Stryker/Mako haptic guided robot (Mako Surgical Corp.) was introduced in 2005 and has been used for over 50,000 UKA procedures (Figure 1). There are nearly 300 robotic systems used nationally, as it has 20% of the market share for UKA in the United States. The Mako system is a semi-active tactile robotic system that requires preoperative imaging, after which a preoperative planning is performed. Intraoperatively, the robotic arm is under direct surgeon control and gives real-time tactile feedback during the procedure (Figure 2).
Furthermore, the surgeon can intraoperatively virtually adjust component positioning and alignment and move the knee through the range of motion, after which the system can provide information on alignment, component position, and balance of the soft tissue (eg, if the knee is overtight or lax through the flexion-arch).60 This system has a burr that resects the bone and when the surgeon directs the burr outside the preplanned area, the burr stops and prevents unnecessary and unwanted resections (Figure 3).
The Navio Precision Free-Hand Sculptor (PFS) system (Blue Belt Technologies) has been used for 1500 UKA procedures, with 50 robots in use in the United States (Figure 4). This system is an image-free semi-active robotic system and has the same characteristics as the aforementioned Mako system.61 Finally, the OmniBotic robotic system (Omnilife Science) has been released for TKA and has been used for over 7300 procedures (Figure 5). This system has an automated cutting-guide technique in which the surgeon designs a virtual plan on the computer system. After this, the cutting-guides are placed by the robotic system at the planned location for all 5 femoral cuts (ie, distal, anterior chamfer, anterior, posterior chamfer, and posterior) and the surgeon then makes the final cuts.57,62
Three robotic systems for knee arthroplasty surgery have been used in Europe. The Caspar system (URS Ortho) is an active robotic system in which a computed tomography (CT) scan is performed preoperatively, after which a virtual implantation is performed on the screen. The surgeon can then obtain information on lower leg alignment, gap balancing, and component positioning, and after an operative plan is made, the surgical resections are performed by the robot. Reflective markers are attached to the leg and all robotic movements are monitored using an infrared camera system. Any undesired motion will be detected by this camera system and will stop all movements.63 A second and more frequently reported system in the literature is the active Robodoc surgical system (Curexo Technology Corporation). This system is designed for TKA and total hip arthroplasty (THA) surgery. Although initial studies reported a high incidence of system-related complications in THA,64 the use of this system for TKA has frequently been reported in the literature.56,63,65-69 A third robotic system that has been used in Europe is the Acrobot surgical system (Acrobot Company Ltd), which is an image-based semi-active robotic system70 used for both UKA and TKA surgery.70,71
Accuracy of Controlling Surgical Variables in Robotic-Assisted Knee Arthroplasty
Several studies have assessed the accuracy of robotic-assisted surgery in UKA surgery with regard to control of the aforementioned surgical variables. Pearle and colleagues72 assessed the mechanical axis accuracy of the Mako system in 10 patients undergoing medial UKA robotic-assisted surgery. They reported that the intraoperative registration lasted 7.5 minutes and the duration of time needed for robotic-assisted burring was 34.8 minutes. They compared the actual postoperative alignment at 6 weeks follow-up with the planned lower leg alignment and found that all measurements were within 1.6° of the planned lower leg alignment. Dunbar and colleagues73 assessed the accuracy of component positioning of the Mako system in 20 patients undergoing medial UKA surgery by comparing preoperative and postoperative 3-dimensional CT scans. They found that the femoral component was within 0.8 mm and 0.9° in all directions and that the tibial component was within 0.9 mm and 1.7° in all directions. They concluded that the accuracy of component positioning with the Mako system was excellent. Finally, Plate and colleagues17 assessed the accuracy of soft tissue balancing in the Mako system in 52 patients undergoing medial UKA surgery. They compared the balance plan with the soft tissue balance after implantation and the Mako system quantified soft tissue balance as the amount of mm of the knee being tight or loose at 0°, 30°, 60°, 90°, and 110° of flexion. They found that at all flexion angles the ligament balancing was accurate up to 0.53 mm of the original plan. Furthermore, they noted that in 83% of cases the accuracy was within 1 mm at all flexion angles.
For the Navio system, Smith and colleagues74 assessed the accuracy of component positioning using 20 synthetic femurs and tibia. They reported a maximum rotational error of 3.2°, an angular error of 1.46° in all orientations, and a maximum translational error of 1.18 mm for both the tibial and femoral implants. Lonner and colleagues75 assessed the accuracy of component positioning in 25 cadaveric specimens. They found similar results as were found in the study of Smith and colleagues74 and concluded that these results were similar to other semi-active robotic systems designed for UKA.
For TKA surgery, Ponder and colleagues76 assessed the accuracy of the OmniBotic system and found that the average error in the anterior-posterior dimension between the targeted and measured cuts was -0.14 mm, and that the standard deviation in guide positioning for the distal, anterior chamfer, and posterior chamfer resections was 0.03° and 0.17 mm. Koenig and colleagues62 assessed the accuracy of the OmniBotic system in the first 100 cases and found that 98% of the cases were within 3° of the neutral mechanical axis. Furthermore, they found a learning curve with regard to tourniquet time between the first and second 10 patients in which they performed robotic-assisted TKA surgery. Siebert and colleagues63 assessed the accuracy of mechanical alignment in the Caspar system in 70 patients treated with the robotic system. They found that the difference between preoperatively planned and postoperatively achieved mechanical alignment was 0.8°. Similarly, Bellemans and colleagues77 assessed mechanical alignment and the positioning and rotation of the tibial and femoral components in a clinical study of 25 cases using the Caspar system. They noted that none of the patients had mechanical alignment, tibial or femoral component positioning, or rotation beyond 1° of the neutral axis. Liow and colleagues56 assessed the accuracy of mechanical axis alignment and component sizing accuracy using the Robodoc system in 25 patients. They reported that the mean postoperative alignment was 0.4° valgus and that all cases were within 3° of the neutral mechanical axis. Furthermore, they reported a mean surgical time of 96 minutes and reported that preoperative planning yielded femoral and tibial component size accuracy of 100%.
These studies have shown that robotic systems for UKA and TKA are accurate in the surgical variables they aim to control. These studies validated tight control of mechanical axis alignment, decrease for outliers, and component positioning and rotation, and also found that the balancing of soft tissues was improved using robotic-assisted surgery.
Robotic-Assisted vs Conventional Knee Arthroplasty
Despite the fact that these systems are accurate in the variables they aim to control, these systems have to be compared to the gold standard of conventional knee arthroplasty. For UKA, Cobb and colleagues70 performed a randomized clinical trial for patients treated undergoing UKA with robotic-assistance of the Acrobot systems compared to conventional UKA and assessed differences in mechanical accuracy. A total of 27 patients were randomly assigned to one of both treatments. They found that in the group of robotic-assisted surgery, 100% of the patients had a mechanical axis within 2° of neutral, while this was only 40% in the conventional UKA groups (difference P < .001). They also assessed the increase in functional outcomes and noted a trend towards improvement in performance with increasing accuracy at 6 weeks and 3 months postoperatively. Lonner and colleagues78 also compared the tibial component positioning between robotic-assisted UKA surgery using the Mako system and conventional UKA surgery. The authors found that the variance in tibial slope, in coronal plane of the tibial component, and varus/valgus alignment were all larger with conventional UKA when compared to robotic-assisted UKA. Citak and colleagues79 compared the accuracy of tibial and femoral implant positioning between robotic-assisted surgery using the Mako system and conventional UKA in a cadaveric study. They reported that the root mean square (RMS) error of femoral component was 1.9 mm and 3.7° in robotic-assisted surgery and 5.4 mm and 10.2° for conventional UKA, while the RMS error for tibial component were 1.4 mm and 5.0° for robotic-assisted surgery and 5.7 mm and 19.2° for conventional UKA surgery. MacCallum and colleagues80 compared the tibial base plate position in a prospective clinical study of 177 patients treated with conventional UKA and 87 patients treated with robotic-assisted surgery using the Mako system. They found that surgery with robotic-assistance was more precise in the coronal and sagittal plane and was more accurate in coronal alignment when compared to conventional UKA. Finally, the first results of robotic-assisted UKA surgery have been presented. Coon and colleagues81 reported the preliminary results of a multicenter study of 854 patients and found a survivorship of 98.9% and satisfaction rate of 92% at minimum 2-year follow-up. Comparing these results to other large conventional UKA cohorts82,83 suggests that robotic-assisted surgery may improve survivorship at short-term follow-up. However, comparative studies and studies with longer follow-up are necessary to assess the additional value of robotic-assisted UKA surgery. Due to the relatively new concept of robotic-assisted surgery, these studies have not been performed or published yet.
For TKA, several studies also have compared how these robotic-systems control the surgical variables compared to conventional TKA surgery. Siebert and colleagues63 assessed mechanical axis accuracy and mechanical outliers following robotic-assisted TKA surgery using the Caspar system and conventional TKA surgery. They reported the difference between preoperative planned and postoperative achieved alignment was 0.8° for robotic-assisted surgery and 2.6° for conventional TKA surgery. Furthermore, they showed that 1 patient in the robotic-assisted group (1.4%) and 18 patients in the conventional TKA group (35%) had mechanical alignment greater than 3° from the neutral mechanical axis. Liow and colleagues56 found similar differences in their prospective randomized study in which they reported that 0% outliers greater than 3° from the neutral mechanical axis were found in the robotic-assisted group while 19.4% of the patients in the conventional TKA group had mechanical axis outliers. They also assessed the joint-line outliers in both procedures and found that 3.2% had joint-line outliers greater than 5 mm in the robotic-assisted group compared to 20.6% in the conventional TKA group. Kim and colleagues65 assessed implant accuracy in robotic-assisted surgery using the ROBODOC system and in conventional surgery and reported higher implant accuracy and fewer outliers using robotic-assisted surgery. Moon and colleagues66 compared robotic-assisted TKA surgery using the Robodoc system with conventional TKA surgery in 10 cadavers. They found that robotic-assisted surgery had excellent precision in all planes and had better accuracy in femoral rotation alignment compared to conventional TKA surgery. Park and Lee67 compared Robodoc robotic-assisted TKA surgery with conventional TKA surgery in a randomized clinical trial of 72 patients. They found that robotic-assisted surgery had definitive advantages in preoperative planning, accuracy of the procedure, and postoperative follow-up regarding femoral and tibial component flexion angles. Finally, Song and colleagues68,69 performed 2 randomized clinical trials in which they compared mechanical axis alignment, component positioning, soft tissue balancing, and patient preference between conventional TKA surgery and robotic-assisted surgery using the Robodoc system. In the first study,68 they simultaneously performed robotic-assisted surgery in one leg and conventional TKA surgery in the other leg. They found that robotic-assisted surgery resulted in less outlier in mechanical axis and component positioning. Furthermore, they found at latest follow-up of 2 years that 12 patients preferred the leg treated with robotic-assisted surgery while 6 preferred the conventional leg. Despite this finding, no significant differences in functional outcome scores were detected between both treatment options. Furthermore, they found that flexion-extension balance was achieved in 92% of patients treated with robotic-assisted TKA surgery and in 77% of patients treated with conventional TKA surgery. In the other study,69 the authors found that more patients treated with robotic-assisted surgery had <2 mm flexion-extension gap and more satisfactory posterior cruciate ligament tension when compared to conventional surgery.
These studies have shown that robotic-assisted surgery is accurate in controlling surgical variables, such as mechanical lower leg alignment, maintaining joint-line, implant positioning, and soft tissue balancing. Furthermore, these studies have shown that controlling these variables is better than the current gold standard of manual knee arthroplasty. Until now, not many studies have assessed survivorship of robotic-assisted surgery. Furthermore, no studies have, to our knowledge, compared survivorship of robotic-assisted with conventional knee replacement surgery. Finally, studies comparing functional outcomes following robotic-assisted surgery and conventional knee arthroplasty surgery are frequently underpowered due to their small sample sizes.68,70 Since many studies have shown that the surgical variables are more tightly controlled using robotic-assisted surgery when compared to conventional surgery, large comparative studies are necessary to assess the role of robotic-assisted surgery in functional outcomes and survivorship of UKA and TKA.
Cost-Effectiveness of Robotic-Assisted Surgery
High initial capital costs of robotic-assisted surgery is one of the factors that constitute a barrier to the widespread implementation of this technique. Multiple authors have suggested that improved implant survivorship afforded by robotic-assisted surgery may justify the expenditure from both societal and provider perspective.84-86 Two studies have performed a cost-effectiveness analysis for UKA surgery. Swank and colleagues84 reviewed the hospital expenditures and profits associated with robot-assisted knee arthroplasty, citing upfront costs of approximately $800,000. The authors estimated a mean per-case contribution profit of $5790 for robotic-assisted UKA, assuming an inpatient-to-outpatient ratio of 1 to 3. Based on this data, Swank and colleagues84 proposed that the capital costs of robotic-assisted UKA may be recovered in as little as 2 years when in the first 3 consecutive years 50, 70, and 90 cases were performed using robotic-assisted UKA. Moschetti and colleagues85 recently published the first formal cost-effectiveness analysis of robotic-assisted compared to manual UKA. The authors used an annual revision risk of 0.55% for the first 2 years following robot-assisted UKA, based on the aforementioned presented data by Coon and colleagues.81 They based their data on the Mako system and assumed an initial capital expenditure of $934,728 with annual servicing costs of 10% (discounted annually) for 4 years thereafter, resulting in a total cost of the robotic system of $1.362 million. These costs were divided by the number of patients estimated to undergo robotic-assisted UKA per year, which was varied to estimate the effect of case volume on cost-effectiveness. The authors reported that robotic-assisted UKA was associated with higher lifetime costs and net utilities compared to manual UKA, at an incremental cost-effectiveness ratio of $47,180 per quality-adjusted life year (QALY) in a high-volume center. This falls well within the societal willingness-to-pay threshold of $100,000/QALY. Sensitivity analysis showed that robotic-assisted UKA is cost-effective under the following conditions: (1) centers performing at least 94 cases annually, (2) in patients younger than age 67 years, and (3) 2-year revision rate does not exceed 1.2%. While the results of this initial analysis are promising, follow-up cost-effectiveness analysis studies will be required as long-term survivorship data become available.
Conclusion
Tighter control of intraoperative surgical variables, such as lower leg alignment, soft tissue balance, joint-line maintenance, and component alignment and positioning, have been associated with improved survivorship and functional outcomes. Upon reviewing the available literature on robotic-assisted surgery, it becomes clear that this technique can improve the accuracy of these surgical variables and is superior to conventional manual UKA and TKA. Although larger and comparative survivorship studies are necessary to compare robotic-assisted knee arthroplasty to conventional techniques, the early results and cost-effectiveness analysis seem promising.
Unicompartmental knee arthroplasty (UKA) and total knee arthroplasty (TKA) are 2 reliable treatment options for patients with primary osteoarthritis. Recently published systematic reviews of cohort studies have shown that 10-year survivorship of medial and lateral UKA is 92% and 91%, respectively,1 while 10-year survivorship of TKA in cohort studies is 95%.2 National and annual registries show a similar trend, although the reported survivorship is lower.1,3-7
In order to improve these survivorship rates, the surgical variables that can intraoperatively be controlled by the orthopedic surgeon have been evaluated. These variables include lower leg alignment, soft tissue balance, joint line maintenance, and alignment, size, and fixation of the tibial and femoral component. Several studies have shown that tight control of lower leg alignment,8-14 balancing of the soft tissues,15-19 joint line maintenance,20-23 component alignment,24-28 component size,29-34 and component fixation35-40 can improve the outcomes of UKA and TKA. As a result, over the past 2 decades, several computer-assisted surgery systems have been developed with the goal of more accurate and reliable control of these factors, and thus improved outcomes of knee arthroplasty.
These systems differ with regard to the number and type of variables they control. Computer navigation systems aim to control one or more of these surgical variables, and several meta-analyses have shown that these systems, when compared to conventional surgery, improve mechanical axis accuracy, decrease the risk for mechanical axis outliers, and improve component positioning in TKA41-49 and UKA surgery.50,51 Interestingly, however, meta-analyses have failed to show the expected superiority in clinical outcomes following computer navigation compared to conventional knee arthroplasty.48,52-55 Furthermore, authors have shown that, despite the fact that computer-navigated surgery increases the accuracy of mechanical alignment and surgical cutting, there is still room for improvement.56 As a consequence, robotic-assisted systems have been developed.
Similar to computer navigation, these robotic-assisted systems aim to control the surgical variables; in addition, they aim to improve the surgical precision of the procedure. Interestingly, 2 recent studies have shown that robotic-assisted systems are superior to computer navigation systems with regard to less cutting time and less resection deviations in coronal and sagittal plane in a cadaveric study,57 and shorter total surgery time, more accurate mechanical axis, and shorter hospital stay in a clinical study.58 Although these results are promising, the exact role of robotic surgery in knee arthroplasty remains unclear. In this review, we aim to report the current state of robotic-assisted knee arthroplasty by discussing (1) the different robotic-assisted knee arthroplasty systems that are available for UKA and TKA surgery, (2) studies that assessed the role of robotic-assisted knee arthroplasty in controlling the aforementioned surgical variables, (3) cadaveric and clinical comparative studies that compared how accurate robotic-assisted and conventional knee surgery control these surgical variables, and (4) studies that assessed the cost-effectiveness of robotic-assisted knee arthroplasty surgery.
Robotic-Assisted Knee Arthroplasty Systems
Several systems have been developed over the years for knee arthroplasty, and these are usually defined as active, semi-active, or passive.59 Active systems are capable of performing tasks or processes autonomously under the watchful eye of the surgeon, while passive systems do not perform actions independently but provide the surgeon with information. In semi-active systems, the surgical action is physically constrained in order to follow a predefined strategy.
In the United States, 3 robotic systems are FDA-approved for knee arthroplasty. The Stryker/Mako haptic guided robot (Mako Surgical Corp.) was introduced in 2005 and has been used for over 50,000 UKA procedures (Figure 1). There are nearly 300 robotic systems used nationally, as it has 20% of the market share for UKA in the United States. The Mako system is a semi-active tactile robotic system that requires preoperative imaging, after which a preoperative planning is performed. Intraoperatively, the robotic arm is under direct surgeon control and gives real-time tactile feedback during the procedure (Figure 2).
Furthermore, the surgeon can intraoperatively virtually adjust component positioning and alignment and move the knee through the range of motion, after which the system can provide information on alignment, component position, and balance of the soft tissue (eg, if the knee is overtight or lax through the flexion-arch).60 This system has a burr that resects the bone and when the surgeon directs the burr outside the preplanned area, the burr stops and prevents unnecessary and unwanted resections (Figure 3).
The Navio Precision Free-Hand Sculptor (PFS) system (Blue Belt Technologies) has been used for 1500 UKA procedures, with 50 robots in use in the United States (Figure 4). This system is an image-free semi-active robotic system and has the same characteristics as the aforementioned Mako system.61 Finally, the OmniBotic robotic system (Omnilife Science) has been released for TKA and has been used for over 7300 procedures (Figure 5). This system has an automated cutting-guide technique in which the surgeon designs a virtual plan on the computer system. After this, the cutting-guides are placed by the robotic system at the planned location for all 5 femoral cuts (ie, distal, anterior chamfer, anterior, posterior chamfer, and posterior) and the surgeon then makes the final cuts.57,62
Three robotic systems for knee arthroplasty surgery have been used in Europe. The Caspar system (URS Ortho) is an active robotic system in which a computed tomography (CT) scan is performed preoperatively, after which a virtual implantation is performed on the screen. The surgeon can then obtain information on lower leg alignment, gap balancing, and component positioning, and after an operative plan is made, the surgical resections are performed by the robot. Reflective markers are attached to the leg and all robotic movements are monitored using an infrared camera system. Any undesired motion will be detected by this camera system and will stop all movements.63 A second and more frequently reported system in the literature is the active Robodoc surgical system (Curexo Technology Corporation). This system is designed for TKA and total hip arthroplasty (THA) surgery. Although initial studies reported a high incidence of system-related complications in THA,64 the use of this system for TKA has frequently been reported in the literature.56,63,65-69 A third robotic system that has been used in Europe is the Acrobot surgical system (Acrobot Company Ltd), which is an image-based semi-active robotic system70 used for both UKA and TKA surgery.70,71
Accuracy of Controlling Surgical Variables in Robotic-Assisted Knee Arthroplasty
Several studies have assessed the accuracy of robotic-assisted surgery in UKA surgery with regard to control of the aforementioned surgical variables. Pearle and colleagues72 assessed the mechanical axis accuracy of the Mako system in 10 patients undergoing medial UKA robotic-assisted surgery. They reported that the intraoperative registration lasted 7.5 minutes and the duration of time needed for robotic-assisted burring was 34.8 minutes. They compared the actual postoperative alignment at 6 weeks follow-up with the planned lower leg alignment and found that all measurements were within 1.6° of the planned lower leg alignment. Dunbar and colleagues73 assessed the accuracy of component positioning of the Mako system in 20 patients undergoing medial UKA surgery by comparing preoperative and postoperative 3-dimensional CT scans. They found that the femoral component was within 0.8 mm and 0.9° in all directions and that the tibial component was within 0.9 mm and 1.7° in all directions. They concluded that the accuracy of component positioning with the Mako system was excellent. Finally, Plate and colleagues17 assessed the accuracy of soft tissue balancing in the Mako system in 52 patients undergoing medial UKA surgery. They compared the balance plan with the soft tissue balance after implantation and the Mako system quantified soft tissue balance as the amount of mm of the knee being tight or loose at 0°, 30°, 60°, 90°, and 110° of flexion. They found that at all flexion angles the ligament balancing was accurate up to 0.53 mm of the original plan. Furthermore, they noted that in 83% of cases the accuracy was within 1 mm at all flexion angles.
For the Navio system, Smith and colleagues74 assessed the accuracy of component positioning using 20 synthetic femurs and tibia. They reported a maximum rotational error of 3.2°, an angular error of 1.46° in all orientations, and a maximum translational error of 1.18 mm for both the tibial and femoral implants. Lonner and colleagues75 assessed the accuracy of component positioning in 25 cadaveric specimens. They found similar results as were found in the study of Smith and colleagues74 and concluded that these results were similar to other semi-active robotic systems designed for UKA.
For TKA surgery, Ponder and colleagues76 assessed the accuracy of the OmniBotic system and found that the average error in the anterior-posterior dimension between the targeted and measured cuts was -0.14 mm, and that the standard deviation in guide positioning for the distal, anterior chamfer, and posterior chamfer resections was 0.03° and 0.17 mm. Koenig and colleagues62 assessed the accuracy of the OmniBotic system in the first 100 cases and found that 98% of the cases were within 3° of the neutral mechanical axis. Furthermore, they found a learning curve with regard to tourniquet time between the first and second 10 patients in which they performed robotic-assisted TKA surgery. Siebert and colleagues63 assessed the accuracy of mechanical alignment in the Caspar system in 70 patients treated with the robotic system. They found that the difference between preoperatively planned and postoperatively achieved mechanical alignment was 0.8°. Similarly, Bellemans and colleagues77 assessed mechanical alignment and the positioning and rotation of the tibial and femoral components in a clinical study of 25 cases using the Caspar system. They noted that none of the patients had mechanical alignment, tibial or femoral component positioning, or rotation beyond 1° of the neutral axis. Liow and colleagues56 assessed the accuracy of mechanical axis alignment and component sizing accuracy using the Robodoc system in 25 patients. They reported that the mean postoperative alignment was 0.4° valgus and that all cases were within 3° of the neutral mechanical axis. Furthermore, they reported a mean surgical time of 96 minutes and reported that preoperative planning yielded femoral and tibial component size accuracy of 100%.
These studies have shown that robotic systems for UKA and TKA are accurate in the surgical variables they aim to control. These studies validated tight control of mechanical axis alignment, decrease for outliers, and component positioning and rotation, and also found that the balancing of soft tissues was improved using robotic-assisted surgery.
Robotic-Assisted vs Conventional Knee Arthroplasty
Despite the fact that these systems are accurate in the variables they aim to control, these systems have to be compared to the gold standard of conventional knee arthroplasty. For UKA, Cobb and colleagues70 performed a randomized clinical trial for patients treated undergoing UKA with robotic-assistance of the Acrobot systems compared to conventional UKA and assessed differences in mechanical accuracy. A total of 27 patients were randomly assigned to one of both treatments. They found that in the group of robotic-assisted surgery, 100% of the patients had a mechanical axis within 2° of neutral, while this was only 40% in the conventional UKA groups (difference P < .001). They also assessed the increase in functional outcomes and noted a trend towards improvement in performance with increasing accuracy at 6 weeks and 3 months postoperatively. Lonner and colleagues78 also compared the tibial component positioning between robotic-assisted UKA surgery using the Mako system and conventional UKA surgery. The authors found that the variance in tibial slope, in coronal plane of the tibial component, and varus/valgus alignment were all larger with conventional UKA when compared to robotic-assisted UKA. Citak and colleagues79 compared the accuracy of tibial and femoral implant positioning between robotic-assisted surgery using the Mako system and conventional UKA in a cadaveric study. They reported that the root mean square (RMS) error of femoral component was 1.9 mm and 3.7° in robotic-assisted surgery and 5.4 mm and 10.2° for conventional UKA, while the RMS error for tibial component were 1.4 mm and 5.0° for robotic-assisted surgery and 5.7 mm and 19.2° for conventional UKA surgery. MacCallum and colleagues80 compared the tibial base plate position in a prospective clinical study of 177 patients treated with conventional UKA and 87 patients treated with robotic-assisted surgery using the Mako system. They found that surgery with robotic-assistance was more precise in the coronal and sagittal plane and was more accurate in coronal alignment when compared to conventional UKA. Finally, the first results of robotic-assisted UKA surgery have been presented. Coon and colleagues81 reported the preliminary results of a multicenter study of 854 patients and found a survivorship of 98.9% and satisfaction rate of 92% at minimum 2-year follow-up. Comparing these results to other large conventional UKA cohorts82,83 suggests that robotic-assisted surgery may improve survivorship at short-term follow-up. However, comparative studies and studies with longer follow-up are necessary to assess the additional value of robotic-assisted UKA surgery. Due to the relatively new concept of robotic-assisted surgery, these studies have not been performed or published yet.
For TKA, several studies also have compared how these robotic-systems control the surgical variables compared to conventional TKA surgery. Siebert and colleagues63 assessed mechanical axis accuracy and mechanical outliers following robotic-assisted TKA surgery using the Caspar system and conventional TKA surgery. They reported the difference between preoperative planned and postoperative achieved alignment was 0.8° for robotic-assisted surgery and 2.6° for conventional TKA surgery. Furthermore, they showed that 1 patient in the robotic-assisted group (1.4%) and 18 patients in the conventional TKA group (35%) had mechanical alignment greater than 3° from the neutral mechanical axis. Liow and colleagues56 found similar differences in their prospective randomized study in which they reported that 0% outliers greater than 3° from the neutral mechanical axis were found in the robotic-assisted group while 19.4% of the patients in the conventional TKA group had mechanical axis outliers. They also assessed the joint-line outliers in both procedures and found that 3.2% had joint-line outliers greater than 5 mm in the robotic-assisted group compared to 20.6% in the conventional TKA group. Kim and colleagues65 assessed implant accuracy in robotic-assisted surgery using the ROBODOC system and in conventional surgery and reported higher implant accuracy and fewer outliers using robotic-assisted surgery. Moon and colleagues66 compared robotic-assisted TKA surgery using the Robodoc system with conventional TKA surgery in 10 cadavers. They found that robotic-assisted surgery had excellent precision in all planes and had better accuracy in femoral rotation alignment compared to conventional TKA surgery. Park and Lee67 compared Robodoc robotic-assisted TKA surgery with conventional TKA surgery in a randomized clinical trial of 72 patients. They found that robotic-assisted surgery had definitive advantages in preoperative planning, accuracy of the procedure, and postoperative follow-up regarding femoral and tibial component flexion angles. Finally, Song and colleagues68,69 performed 2 randomized clinical trials in which they compared mechanical axis alignment, component positioning, soft tissue balancing, and patient preference between conventional TKA surgery and robotic-assisted surgery using the Robodoc system. In the first study,68 they simultaneously performed robotic-assisted surgery in one leg and conventional TKA surgery in the other leg. They found that robotic-assisted surgery resulted in less outlier in mechanical axis and component positioning. Furthermore, they found at latest follow-up of 2 years that 12 patients preferred the leg treated with robotic-assisted surgery while 6 preferred the conventional leg. Despite this finding, no significant differences in functional outcome scores were detected between both treatment options. Furthermore, they found that flexion-extension balance was achieved in 92% of patients treated with robotic-assisted TKA surgery and in 77% of patients treated with conventional TKA surgery. In the other study,69 the authors found that more patients treated with robotic-assisted surgery had <2 mm flexion-extension gap and more satisfactory posterior cruciate ligament tension when compared to conventional surgery.
These studies have shown that robotic-assisted surgery is accurate in controlling surgical variables, such as mechanical lower leg alignment, maintaining joint-line, implant positioning, and soft tissue balancing. Furthermore, these studies have shown that controlling these variables is better than the current gold standard of manual knee arthroplasty. Until now, not many studies have assessed survivorship of robotic-assisted surgery. Furthermore, no studies have, to our knowledge, compared survivorship of robotic-assisted with conventional knee replacement surgery. Finally, studies comparing functional outcomes following robotic-assisted surgery and conventional knee arthroplasty surgery are frequently underpowered due to their small sample sizes.68,70 Since many studies have shown that the surgical variables are more tightly controlled using robotic-assisted surgery when compared to conventional surgery, large comparative studies are necessary to assess the role of robotic-assisted surgery in functional outcomes and survivorship of UKA and TKA.
Cost-Effectiveness of Robotic-Assisted Surgery
High initial capital costs of robotic-assisted surgery is one of the factors that constitute a barrier to the widespread implementation of this technique. Multiple authors have suggested that improved implant survivorship afforded by robotic-assisted surgery may justify the expenditure from both societal and provider perspective.84-86 Two studies have performed a cost-effectiveness analysis for UKA surgery. Swank and colleagues84 reviewed the hospital expenditures and profits associated with robot-assisted knee arthroplasty, citing upfront costs of approximately $800,000. The authors estimated a mean per-case contribution profit of $5790 for robotic-assisted UKA, assuming an inpatient-to-outpatient ratio of 1 to 3. Based on this data, Swank and colleagues84 proposed that the capital costs of robotic-assisted UKA may be recovered in as little as 2 years when in the first 3 consecutive years 50, 70, and 90 cases were performed using robotic-assisted UKA. Moschetti and colleagues85 recently published the first formal cost-effectiveness analysis of robotic-assisted compared to manual UKA. The authors used an annual revision risk of 0.55% for the first 2 years following robot-assisted UKA, based on the aforementioned presented data by Coon and colleagues.81 They based their data on the Mako system and assumed an initial capital expenditure of $934,728 with annual servicing costs of 10% (discounted annually) for 4 years thereafter, resulting in a total cost of the robotic system of $1.362 million. These costs were divided by the number of patients estimated to undergo robotic-assisted UKA per year, which was varied to estimate the effect of case volume on cost-effectiveness. The authors reported that robotic-assisted UKA was associated with higher lifetime costs and net utilities compared to manual UKA, at an incremental cost-effectiveness ratio of $47,180 per quality-adjusted life year (QALY) in a high-volume center. This falls well within the societal willingness-to-pay threshold of $100,000/QALY. Sensitivity analysis showed that robotic-assisted UKA is cost-effective under the following conditions: (1) centers performing at least 94 cases annually, (2) in patients younger than age 67 years, and (3) 2-year revision rate does not exceed 1.2%. While the results of this initial analysis are promising, follow-up cost-effectiveness analysis studies will be required as long-term survivorship data become available.
Conclusion
Tighter control of intraoperative surgical variables, such as lower leg alignment, soft tissue balance, joint-line maintenance, and component alignment and positioning, have been associated with improved survivorship and functional outcomes. Upon reviewing the available literature on robotic-assisted surgery, it becomes clear that this technique can improve the accuracy of these surgical variables and is superior to conventional manual UKA and TKA. Although larger and comparative survivorship studies are necessary to compare robotic-assisted knee arthroplasty to conventional techniques, the early results and cost-effectiveness analysis seem promising.
1. van der List JP, McDonald LS, Pearle AD. Systematic review of medial versus lateral survivorship in unicompartmental knee arthroplasty. Knee. 2015;22(6):454-460.
2. Mont MA, Pivec R, Issa K, Kapadia BH, Maheshwari A, Harwin SF. Long-term implant survivorship of cementless total knee arthroplasty: a systematic review of the literature and meta-analysis. J Knee Surg. 2014;27(5):369-376.
3. Australian Orthopaedic Association National Joint Replacement Registry. Annual Report 2014 Australian Hip and Knee Arthroplasty Register. https://aoanjrr.sahmri.com/documents/10180/172286/Annual%20Report%202014. Accessed April 6, 2016.
4. The Swedish Knee Arthroplasty Register. Annual Report 2015 Swedish Knee Arthroplasty Register. http://www.myknee.se/pdf/SVK_2015_Eng_1.0.pdf. Published December 1, 2015. Accessed April 6, 2016.
5. Centre of excellence of joint replacements. The Norwegian Arthroplasty Register. http://nrlweb.ihelse.net/eng/Report_2010.pdf. Published June 2010. Accessed June 3, 2015.
6. National Joint Registry for England, Wales, Northern Ireland and the Isle of Man. 12th Annual Report 2015. http://www.njrcentre.org.uk/njrcentre/Portals/0/Documents/England/Reports/12th%20annual%20report/NJR%20Online%20Annual%20Report%202015.pdf. Accessed April 6, 2016.
7. The New Zealand Joint Registry. Fourteen Year Report January 1999 to December 2012. http://www.nzoa.org.nz/system/files/NJR%2014%20Year%20Report.pdf. Published November 2013. Accessed April 6, 2016.
8. Jeffery RS, Morris RW, Denham RA. Coronal alignment after total knee replacement. J Bone Joint Surg Br. 1991;73(5):709-714.
9. Rand JA, Coventry MB. Ten-year evaluation of geometric total knee arthroplasty. Clin Orthop Relat Res. 1988;232:168-173.
10. Ritter MA, Faris PM, Keating EM, Meding JB. Postoperative alignment of total knee replacement. Its effect on survival. Clin Orthop Relat Res. 1994;299:153-156.
11. Ryd L, Lindstrand A, Stenström A, Selvik G. Porous coated anatomic tricompartmental tibial components. The relationship between prosthetic position and micromotion. Clin Orthop Relat Res. 1990;251:189-197.
12. van der List JP, Chawla H, Villa JC, Zuiderbaan HA, Pearle AD. Early functional outcome after lateral UKA is sensitive to postoperative lower limb alignment. Knee Surg Sports Traumatol Arthrosc. 2015. [Epub ahead of print]
13. van der List JP, Zuiderbaan HA, Pearle AD. Why do medial unicompartmental knee arthroplasties fail today? J Arthroplasty. 2015. [Epub ahead of print]
14. Vasso M, Del Regno C, D’Amelio A, Viggiano D, Corona K, Schiavone Panni A. Minor varus alignment provides better results than neutral alignment in medial UKA. Knee. 2015;22(2):117-121.
15. Attfield SF, Wilton TJ, Pratt DJ, Sambatakakis A. Soft-tissue balance and recovery of proprioception after total knee replacement. J Bone Joint Surg Br. 1996;78(4):540-545.
16. Pagnano MW, Hanssen AD, Lewallen DG, Stuart MJ. Flexion instability after primary posterior cruciate retaining total knee arthroplasty. Clin Orthop Relat Res. 1998;356:39-46.
17. Plate JF, Mofidi A, Mannava S, et al. Achieving accurate ligament balancing using robotic-assisted unicompartmental knee arthroplasty. Adv Orthop. 2013;2013:837167.
18. Roche M, Elson L, Anderson C. Dynamic soft tissue balancing in total knee arthroplasty. Orthop Clin North Am. 2014;45(2):157-165.
19. Wasielewski RC, Galante JO, Leighty RM, Natarajan RN, Rosenberg AG. Wear patterns on retrieved polyethylene tibial inserts and their relationship to technical considerations during total knee arthroplasty. Clin Orthop Relat Res. 1994;299:31-43.
20. Ji HM, Han J, Jin DS, Seo H, Won YY. Kinematically aligned TKA can align knee joint line to horizontal. Knee Surg Sports Traumatol Arthrosc. 2016. [Epub ahead of print]
21. Khamaisy S, Zuiderbaan HA, van der List JP, Nam D, Pearle AD. Medial unicompartmental knee arthroplasty improves congruence and restores joint space width of the lateral compartment. Knee. 2016. [Epub ahead of print]
22. Niinimaki TT, Murray DW, Partanen J, Pajala A, Leppilahti JI. Unicompartmental knee arthroplasties implanted for osteoarthritis with partial loss of joint space have high re-operation rates. Knee. 2011;18(6):432-435.
23. Zuiderbaan HA, Khamaisy S, Thein R, Nawabi DH, Pearle AD. Congruence and joint space width alterations of the medial compartment following lateral unicompartmental knee arthroplasty. Bone Joint J. 2015;97-B(1):50-55.
24. Barbadoro P, Ensini A, Leardini A, et al. Tibial component alignment and risk of loosening in unicompartmental knee arthroplasty: a radiographic and radiostereometric study. Knee Surg Sports Traumatol Arthrosc. 2014;22(12):3157-3162.
25. Collier MB, Eickmann TH, Sukezaki F, McAuley JP, Engh GA. Patient, implant, and alignment factors associated with revision of medial compartment unicondylar arthroplasty. J Arthroplasty. 2006;21(6 Suppl 2):108-115.
26. Nedopil AJ, Howell SM, Hull ML. Does malrotation of the tibial and femoral components compromise function in kinematically aligned total knee arthroplasty? Orthop Clin North Am. 2016;47(1):41-50.
27. Rosskopf J, Singh PK, Wolf P, Strauch M, Graichen H. Influence of intentional femoral component flexion in navigated TKA on gap balance and sagittal anatomy. Knee Surg Sports Traumatol Arthrosc. 2014;22(3):687-693.
28. Zihlmann MS, Stacoff A, Romero J, Quervain IK, Stüssi E. Biomechanical background and clinical observations of rotational malalignment in TKA: literature review and consequences. Clin Biomech (Bristol, Avon). 2005;20(7):661-668.
29. Bonnin MP, Saffarini M, Shepherd D, Bossard N, Dantony E. Oversizing the tibial component in TKAs: incidence, consequences and risk factors. Knee Surg Sports Traumatol Arthrosc. 2015. [Epub ahead of print]
30. Bonnin MP, Schmidt A, Basiglini L, Bossard N, Dantony E. Mediolateral oversizing influences pain, function, and flexion after TKA. Knee Surg Sports Traumatol Arthrosc. 2013;21(10):2314-2324.
31. Chau R, Gulati A, Pandit H, et al. Tibial component overhang following unicompartmental knee replacement--does it matter? Knee. 2009;16(5):310-313.
32. Mueller JK, Wentorf FA, Moore RE. Femoral and tibial insert downsizing increases the laxity envelope in TKA. Knee Surg Sports Traumatol Arthrosc. 2014;22(12):3003-3011.
33. Sriphirom P, Raungthong N, Chutchawan P, Thiranon C, Sukandhavesa N. Influence of a secondary downsizing of the femoral component on the extension gap: a cadaveric study. Orthopedics. 2012;35(10 Suppl):56-59.
34. Young SW, Clarke HD, Graves SE, Liu YL, de Steiger RN. Higher rate of revision in PFC sigma primary total knee arthroplasty with mismatch of femoro-tibial component sizes. J Arthroplasty. 2015;30(5):813-817.
35. Barink M, Verdonschot N, de Waal Malefijt M. A different fixation of the femoral component in total knee arthroplasty may lead to preservation of femoral bone stock. Proc Inst Mech Eng H. 2003;217(5):325-332.
36. Eagar P, Hull ML, Howell SM. How the fixation method stiffness and initial tension affect anterior load-displacement of the knee and tension in anterior cruciate ligament grafts: a study in cadaveric knees using a double-loop hamstrings graft. J Orthop Res. 2004;22(3):613-624.
37. Fricka KB, Sritulanondha S, McAsey CJ. To cement or not? Two-year results of a prospective, randomized study comparing cemented vs. cementless total knee arthroplasty (TKA). J Arthroplasty. 2015;30(9 Suppl):55-58.
38. Kendrick BJ, Kaptein BL, Valstar ER, et al. Cemented versus cementless Oxford unicompartmental knee arthroplasty using radiostereometric analysis: a randomised controlled trial. Bone Joint J. 2015;97-B(2):185-191.
39. Kim TK, Chang CB, Kang YG, Chung BJ, Cho HJ, Seong SC. Execution accuracy of bone resection and implant fixation in computer assisted minimally invasive total knee arthroplasty. Knee. 2010;17(1):23-28.
40. Whiteside LA. Making your next unicompartmental knee arthroplasty last: three keys to success. J Arthroplasty. 2005;20(4 Suppl 2):2-3.
41. Bauwens K, Matthes G, Wich M, et al. Navigated total knee replacement. A meta-analysis. J Bone Joint Surg Am. 2007;89(2):261-269.
42. Brin YS, Nikolaou VS, Joseph L, Zukor DJ, Antoniou J. Imageless computer assisted versus conventional total knee replacement. A Bayesian meta-analysis of 23 comparative studies. Int Orthop. 2011;35(3):331-339.
43. Cheng T, Zhang G, Zhang X. Imageless navigation system does not improve component rotational alignment in total knee arthroplasty. J Surg Res. 2011;171(2):590-600.
44. Conteduca F, Iorio R, Mazza D, Ferretti A. Patient-specific instruments in total knee arthroplasty. Int Orthop. 2014;38(2):259-265.
45. Fu Y, Wang M, Liu Y, Fu Q. Alignment outcomes in navigated total knee arthroplasty: a meta-analysis. Knee Surg Sports Traumatol Arthrosc. 2012;20(6):1075-1082.
46. Hetaimish BM, Khan MM, Simunovic N, Al-Harbi HH, Bhandari M, Zalzal PK. Meta-analysis of navigation vs conventional total knee arthroplasty. J Arthroplasty. 2012;27(6):1177-1182.
47. Mason JB, Fehring TK, Estok R, Banel D, Fahrbach K. Meta-analysis of alignment outcomes in computer-assisted total knee arthroplasty surgery. J Arthroplasty. 2007;22(8):1097-1106.
48. Moskal JT, Capps SG, Mann JW, Scanelli JA. Navigated versus conventional total knee arthroplasty. J Knee Surg. 2014;27(3):235-248.
49. Shi J, Wei Y, Wang S, et al. Computer navigation and total knee arthroplasty. Orthopedics. 2014;37(1):e39-e43.
50. Nair R, Tripathy G, Deysine GR. Computer navigation systems in unicompartmental knee arthroplasty: a systematic review. Am J Orthop. 2014;43(6):256-261.
51. Weber P, Crispin A, Schmidutz F, et al. Improved accuracy in computer-assisted unicondylar knee arthroplasty: a meta-analysis. Knee Surg Sports Traumatol Arthrosc. 2013;21(11):2453-2461.
52. Alcelik IA, Blomfield MI, Diana G, Gibbon AJ, Carrington N, Burr S. A comparison of short-term outcomes of minimally invasive computer-assisted vs minimally invasive conventional instrumentation for primary total knee arthroplasty: a systematic review and meta-analysis. J Arthroplasty. 2016;31(2):410-418.
53. Cheng T, Pan XY, Mao X, Zhang GY, Zhang XL. Little clinical advantage of computer-assisted navigation over conventional instrumentation in primary total knee arthroplasty at early follow-up. Knee. 2012;19(4):237-245.
54. Rebal BA, Babatunde OM, Lee JH, Geller JA, Patrick DA Jr, Macaulay W. Imageless computer navigation in total knee arthroplasty provides superior short term functional outcomes: a meta-analysis. J Arthroplasty. 2014;29(5):938-944.
55. Zamora LA, Humphreys KJ, Watt AM, Forel D, Cameron AL. Systematic review of computer-navigated total knee arthroplasty. ANZ J Surg. 2013;83(1-2):22-30.
56. Liow MH, Xia Z, Wong MK, Tay KJ, Yeo SJ, Chin PL. Robot-assisted total knee arthroplasty accurately restores the joint line and mechanical axis. A prospective randomised study. J Arthroplasty. 2014;29(12):2373-2377.
57. Koulalis D, O’Loughlin PF, Plaskos C, Kendoff D, Cross MB, Pearle AD. Sequential versus automated cutting guides in computer-assisted total knee arthroplasty. Knee. 2011;18(6):436-442.
58. Clark TC, Schmidt FH. Robot-assisted navigation versus computer-assisted navigation in primary total knee arthroplasty: efficiency and accuracy. ISRN Orthop. 2013;2013:794827.
59. DiGioia AM 3rd, Jaramaz B, Colgan BD. Computer assisted orthopaedic surgery. Image guided and robotic assistive technologies. Clin Orthop Relat Res. 1998(354):8-16.
60. Conditt MA, Roche MW. Minimally invasive robotic-arm-guided unicompartmental knee arthroplasty. J Bone Joint Surg Am. 2009;91 Suppl 1:63-68.
61. Lonner JH. Robotically assisted unicompartmental knee arthroplasty with a handheld image-free sculpting tool. Orthop Clin North Am. 2016;47(1):29-40.
62. Koenig JA, Suero EM, Plaskos C. Surgical accuracy and efficiency of computer-navigated TKA with a robotic cutting guide–report on the first 100 cases. J Bone Joint Surg Br. 2012;94-B(SUPP XLIV):103. Available at: http://www.bjjprocs.boneandjoint.org.uk/content/94-B/SUPP_XLIV/103. Accessed April 6, 2016.
63. Siebert W, Mai S, Kober R, Heeckt PF. Technique and first clinical results of robot-assisted total knee replacement. Knee. 2002;9(3):173-180.
64. Schulz AP, Seide K, Queitsch C, et al. Results of total hip replacement using the Robodoc surgical assistant system: clinical outcome and evaluation of complications for 97 procedures. Int J Med Robot. 2007;3(4):301-306.
65. Kim SM, Park YS, Ha CW, Lim SJ, Moon YW. Robot-assisted implantation improves the precision of component position in minimally invasive TKA. Orthopedics. 2012;35(9):e1334-e1339.
66. Moon YW, Ha CW, Do KH, et al. Comparison of robot-assisted and conventional total knee arthroplasty: a controlled cadaver study using multiparameter quantitative three-dimensional CT assessment of alignment. Comput Aided Surg. 2012;17(2):86-95.
67. Park SE, Lee CT. Comparison of robotic-assisted and conventional manual implantation of a primary total knee arthroplasty. J Arthroplasty. 2007;22(7):1054-1059.
68. Song EK, Seon JK, Park SJ, Jung WB, Park HW, Lee GW. Simultaneous bilateral total knee arthroplasty with robotic and conventional techniques: a prospective, randomized study. Knee Surg Sports Traumatol Arthrosc. 2011;19(7):1069-1076.
69. Song EK, Seon JK, Yim JH, Netravali NA, Bargar WL. Robotic-assisted TKA reduces postoperative alignment outliers and improves gap balance compared to conventional TKA. Clin Orthop Relat Res. 2013;471(1):118-126.
70. Cobb J, Henckel J, Gomes P, et al. Hands-on robotic unicompartmental knee replacement: a prospective, randomised controlled study of the acrobot system. J Bone Joint Surg Br. 2006;88(2):188-197.
71. Jakopec M, Harris SJ, Rodriguez y Baena F, Gomes P, Cobb J, Davies BL. The first clinical application of a “hands-on” robotic knee surgery system. Comput Aided Surg. 2001;6(6):329-339.
72. Pearle AD, O’Loughlin PF, Kendoff DO. Robot-assisted unicompartmental knee arthroplasty. J Arthroplasty. 2010;25(2):230-237.
73. Dunbar NJ, Roche MW, Park BH, Branch SH, Conditt MA, Banks SA. Accuracy of dynamic tactile-guided unicompartmental knee arthroplasty. J Arthroplasty. 2012;27(5):803-808.e1.
74. Smith JR, Riches PE, Rowe PJ. Accuracy of a freehand sculpting tool for unicondylar knee replacement. Int J Med Robot. 2014;10(2):162-169.
75. Lonner JH, Smith JR, Picard F, Hamlin B, Rowe PJ, Riches PE. High degree of accuracy of a novel image-free handheld robot for unicondylar knee arthroplasty in a cadaveric study. Clin Orthop Relat Res. 2015;473(1):206-212.
76. Ponder C, Plaskos C, Cheal E. Press-fit total knee arthroplasty with a robotic-cutting guide: proof of concept and initial clinical experience. Bone & Joint Journal Orthopaedic Proceedings Supplement. 2013;95(SUPP 28):61. Available at: http://www.bjjprocs.boneandjoint.org.uk/content/95-B/SUPP_28/61.abstract. Accessed April 6, 2016.
77. Bellemans J, Vandenneucker H, Vanlauwe J. Robot-assisted total knee arthroplasty. Clin Orthop Relat Res. 2007;464:111-116.
78. Lonner JH, John TK, Conditt MA. Robotic arm-assisted UKA improves tibial component alignment: a pilot study. Clin Orthop Relat Res. 2010;468(1):141-146.
79. Citak M, Suero EM, Citak M, et al. Unicompartmental knee arthroplasty: is robotic technology more accurate than conventional technique? Knee. 2013;20(4):268-271.
80. MacCallum KP, Danoff JR, Geller JA. Tibial baseplate positioning in robotic-assisted and conventional unicompartmental knee arthroplasty. Eur J Orthop Surg Traumatol. 2016;26(1):93-98.
81. Coon T, Roche M, Pearle AD, Dounchis J, Borus T, Buechel F Jr. Two year survivorship of robotically guided unicompartmental knee arthroplasty. Paper presented at: International Society for Technology in Arthroplasty 26th Annual Congress; October 16-19, 2013; Palm Beach, FL.
82. Pandit H, Jenkins C, Gill HS, Barker K, Dodd CA, Murray DW. Minimally invasive Oxford phase 3 unicompartmental knee replacement: results of 1000 cases. J Bone Joint Surg Br. 2011;93(2):198-204.
83. Yoshida K, Tada M, Yoshida H, Takei S, Fukuoka S, Nakamura H. Oxford phase 3 unicompartmental knee arthroplasty in Japan--clinical results in greater than one thousand cases over ten years. J Arthroplasty. 2013;28(9 Suppl):168-171.
84. Swank ML, Alkire M, Conditt M, Lonner JH. Technology and cost-effectiveness in knee arthroplasty: computer navigation and robotics. Am J Orthop. 2009;38(2 Suppl):32-36.
85. Moschetti WE, Konopka JF, Rubash HE, Genuario JW. Can robot-assisted unicompartmental knee arthroplasty be cost-effective? A markovdecision analysis. J Arthroplasty. 2015. [Epub ahead of print]
86. Thienpont E. Improving Accuracy in Knee Arthroplasty. 1st ed. New Delhi, India: Jaypee Brothers Medical Publishers; 2012.
1. van der List JP, McDonald LS, Pearle AD. Systematic review of medial versus lateral survivorship in unicompartmental knee arthroplasty. Knee. 2015;22(6):454-460.
2. Mont MA, Pivec R, Issa K, Kapadia BH, Maheshwari A, Harwin SF. Long-term implant survivorship of cementless total knee arthroplasty: a systematic review of the literature and meta-analysis. J Knee Surg. 2014;27(5):369-376.
3. Australian Orthopaedic Association National Joint Replacement Registry. Annual Report 2014 Australian Hip and Knee Arthroplasty Register. https://aoanjrr.sahmri.com/documents/10180/172286/Annual%20Report%202014. Accessed April 6, 2016.
4. The Swedish Knee Arthroplasty Register. Annual Report 2015 Swedish Knee Arthroplasty Register. http://www.myknee.se/pdf/SVK_2015_Eng_1.0.pdf. Published December 1, 2015. Accessed April 6, 2016.
5. Centre of excellence of joint replacements. The Norwegian Arthroplasty Register. http://nrlweb.ihelse.net/eng/Report_2010.pdf. Published June 2010. Accessed June 3, 2015.
6. National Joint Registry for England, Wales, Northern Ireland and the Isle of Man. 12th Annual Report 2015. http://www.njrcentre.org.uk/njrcentre/Portals/0/Documents/England/Reports/12th%20annual%20report/NJR%20Online%20Annual%20Report%202015.pdf. Accessed April 6, 2016.
7. The New Zealand Joint Registry. Fourteen Year Report January 1999 to December 2012. http://www.nzoa.org.nz/system/files/NJR%2014%20Year%20Report.pdf. Published November 2013. Accessed April 6, 2016.
8. Jeffery RS, Morris RW, Denham RA. Coronal alignment after total knee replacement. J Bone Joint Surg Br. 1991;73(5):709-714.
9. Rand JA, Coventry MB. Ten-year evaluation of geometric total knee arthroplasty. Clin Orthop Relat Res. 1988;232:168-173.
10. Ritter MA, Faris PM, Keating EM, Meding JB. Postoperative alignment of total knee replacement. Its effect on survival. Clin Orthop Relat Res. 1994;299:153-156.
11. Ryd L, Lindstrand A, Stenström A, Selvik G. Porous coated anatomic tricompartmental tibial components. The relationship between prosthetic position and micromotion. Clin Orthop Relat Res. 1990;251:189-197.
12. van der List JP, Chawla H, Villa JC, Zuiderbaan HA, Pearle AD. Early functional outcome after lateral UKA is sensitive to postoperative lower limb alignment. Knee Surg Sports Traumatol Arthrosc. 2015. [Epub ahead of print]
13. van der List JP, Zuiderbaan HA, Pearle AD. Why do medial unicompartmental knee arthroplasties fail today? J Arthroplasty. 2015. [Epub ahead of print]
14. Vasso M, Del Regno C, D’Amelio A, Viggiano D, Corona K, Schiavone Panni A. Minor varus alignment provides better results than neutral alignment in medial UKA. Knee. 2015;22(2):117-121.
15. Attfield SF, Wilton TJ, Pratt DJ, Sambatakakis A. Soft-tissue balance and recovery of proprioception after total knee replacement. J Bone Joint Surg Br. 1996;78(4):540-545.
16. Pagnano MW, Hanssen AD, Lewallen DG, Stuart MJ. Flexion instability after primary posterior cruciate retaining total knee arthroplasty. Clin Orthop Relat Res. 1998;356:39-46.
17. Plate JF, Mofidi A, Mannava S, et al. Achieving accurate ligament balancing using robotic-assisted unicompartmental knee arthroplasty. Adv Orthop. 2013;2013:837167.
18. Roche M, Elson L, Anderson C. Dynamic soft tissue balancing in total knee arthroplasty. Orthop Clin North Am. 2014;45(2):157-165.
19. Wasielewski RC, Galante JO, Leighty RM, Natarajan RN, Rosenberg AG. Wear patterns on retrieved polyethylene tibial inserts and their relationship to technical considerations during total knee arthroplasty. Clin Orthop Relat Res. 1994;299:31-43.
20. Ji HM, Han J, Jin DS, Seo H, Won YY. Kinematically aligned TKA can align knee joint line to horizontal. Knee Surg Sports Traumatol Arthrosc. 2016. [Epub ahead of print]
21. Khamaisy S, Zuiderbaan HA, van der List JP, Nam D, Pearle AD. Medial unicompartmental knee arthroplasty improves congruence and restores joint space width of the lateral compartment. Knee. 2016. [Epub ahead of print]
22. Niinimaki TT, Murray DW, Partanen J, Pajala A, Leppilahti JI. Unicompartmental knee arthroplasties implanted for osteoarthritis with partial loss of joint space have high re-operation rates. Knee. 2011;18(6):432-435.
23. Zuiderbaan HA, Khamaisy S, Thein R, Nawabi DH, Pearle AD. Congruence and joint space width alterations of the medial compartment following lateral unicompartmental knee arthroplasty. Bone Joint J. 2015;97-B(1):50-55.
24. Barbadoro P, Ensini A, Leardini A, et al. Tibial component alignment and risk of loosening in unicompartmental knee arthroplasty: a radiographic and radiostereometric study. Knee Surg Sports Traumatol Arthrosc. 2014;22(12):3157-3162.
25. Collier MB, Eickmann TH, Sukezaki F, McAuley JP, Engh GA. Patient, implant, and alignment factors associated with revision of medial compartment unicondylar arthroplasty. J Arthroplasty. 2006;21(6 Suppl 2):108-115.
26. Nedopil AJ, Howell SM, Hull ML. Does malrotation of the tibial and femoral components compromise function in kinematically aligned total knee arthroplasty? Orthop Clin North Am. 2016;47(1):41-50.
27. Rosskopf J, Singh PK, Wolf P, Strauch M, Graichen H. Influence of intentional femoral component flexion in navigated TKA on gap balance and sagittal anatomy. Knee Surg Sports Traumatol Arthrosc. 2014;22(3):687-693.
28. Zihlmann MS, Stacoff A, Romero J, Quervain IK, Stüssi E. Biomechanical background and clinical observations of rotational malalignment in TKA: literature review and consequences. Clin Biomech (Bristol, Avon). 2005;20(7):661-668.
29. Bonnin MP, Saffarini M, Shepherd D, Bossard N, Dantony E. Oversizing the tibial component in TKAs: incidence, consequences and risk factors. Knee Surg Sports Traumatol Arthrosc. 2015. [Epub ahead of print]
30. Bonnin MP, Schmidt A, Basiglini L, Bossard N, Dantony E. Mediolateral oversizing influences pain, function, and flexion after TKA. Knee Surg Sports Traumatol Arthrosc. 2013;21(10):2314-2324.
31. Chau R, Gulati A, Pandit H, et al. Tibial component overhang following unicompartmental knee replacement--does it matter? Knee. 2009;16(5):310-313.
32. Mueller JK, Wentorf FA, Moore RE. Femoral and tibial insert downsizing increases the laxity envelope in TKA. Knee Surg Sports Traumatol Arthrosc. 2014;22(12):3003-3011.
33. Sriphirom P, Raungthong N, Chutchawan P, Thiranon C, Sukandhavesa N. Influence of a secondary downsizing of the femoral component on the extension gap: a cadaveric study. Orthopedics. 2012;35(10 Suppl):56-59.
34. Young SW, Clarke HD, Graves SE, Liu YL, de Steiger RN. Higher rate of revision in PFC sigma primary total knee arthroplasty with mismatch of femoro-tibial component sizes. J Arthroplasty. 2015;30(5):813-817.
35. Barink M, Verdonschot N, de Waal Malefijt M. A different fixation of the femoral component in total knee arthroplasty may lead to preservation of femoral bone stock. Proc Inst Mech Eng H. 2003;217(5):325-332.
36. Eagar P, Hull ML, Howell SM. How the fixation method stiffness and initial tension affect anterior load-displacement of the knee and tension in anterior cruciate ligament grafts: a study in cadaveric knees using a double-loop hamstrings graft. J Orthop Res. 2004;22(3):613-624.
37. Fricka KB, Sritulanondha S, McAsey CJ. To cement or not? Two-year results of a prospective, randomized study comparing cemented vs. cementless total knee arthroplasty (TKA). J Arthroplasty. 2015;30(9 Suppl):55-58.
38. Kendrick BJ, Kaptein BL, Valstar ER, et al. Cemented versus cementless Oxford unicompartmental knee arthroplasty using radiostereometric analysis: a randomised controlled trial. Bone Joint J. 2015;97-B(2):185-191.
39. Kim TK, Chang CB, Kang YG, Chung BJ, Cho HJ, Seong SC. Execution accuracy of bone resection and implant fixation in computer assisted minimally invasive total knee arthroplasty. Knee. 2010;17(1):23-28.
40. Whiteside LA. Making your next unicompartmental knee arthroplasty last: three keys to success. J Arthroplasty. 2005;20(4 Suppl 2):2-3.
41. Bauwens K, Matthes G, Wich M, et al. Navigated total knee replacement. A meta-analysis. J Bone Joint Surg Am. 2007;89(2):261-269.
42. Brin YS, Nikolaou VS, Joseph L, Zukor DJ, Antoniou J. Imageless computer assisted versus conventional total knee replacement. A Bayesian meta-analysis of 23 comparative studies. Int Orthop. 2011;35(3):331-339.
43. Cheng T, Zhang G, Zhang X. Imageless navigation system does not improve component rotational alignment in total knee arthroplasty. J Surg Res. 2011;171(2):590-600.
44. Conteduca F, Iorio R, Mazza D, Ferretti A. Patient-specific instruments in total knee arthroplasty. Int Orthop. 2014;38(2):259-265.
45. Fu Y, Wang M, Liu Y, Fu Q. Alignment outcomes in navigated total knee arthroplasty: a meta-analysis. Knee Surg Sports Traumatol Arthrosc. 2012;20(6):1075-1082.
46. Hetaimish BM, Khan MM, Simunovic N, Al-Harbi HH, Bhandari M, Zalzal PK. Meta-analysis of navigation vs conventional total knee arthroplasty. J Arthroplasty. 2012;27(6):1177-1182.
47. Mason JB, Fehring TK, Estok R, Banel D, Fahrbach K. Meta-analysis of alignment outcomes in computer-assisted total knee arthroplasty surgery. J Arthroplasty. 2007;22(8):1097-1106.
48. Moskal JT, Capps SG, Mann JW, Scanelli JA. Navigated versus conventional total knee arthroplasty. J Knee Surg. 2014;27(3):235-248.
49. Shi J, Wei Y, Wang S, et al. Computer navigation and total knee arthroplasty. Orthopedics. 2014;37(1):e39-e43.
50. Nair R, Tripathy G, Deysine GR. Computer navigation systems in unicompartmental knee arthroplasty: a systematic review. Am J Orthop. 2014;43(6):256-261.
51. Weber P, Crispin A, Schmidutz F, et al. Improved accuracy in computer-assisted unicondylar knee arthroplasty: a meta-analysis. Knee Surg Sports Traumatol Arthrosc. 2013;21(11):2453-2461.
52. Alcelik IA, Blomfield MI, Diana G, Gibbon AJ, Carrington N, Burr S. A comparison of short-term outcomes of minimally invasive computer-assisted vs minimally invasive conventional instrumentation for primary total knee arthroplasty: a systematic review and meta-analysis. J Arthroplasty. 2016;31(2):410-418.
53. Cheng T, Pan XY, Mao X, Zhang GY, Zhang XL. Little clinical advantage of computer-assisted navigation over conventional instrumentation in primary total knee arthroplasty at early follow-up. Knee. 2012;19(4):237-245.
54. Rebal BA, Babatunde OM, Lee JH, Geller JA, Patrick DA Jr, Macaulay W. Imageless computer navigation in total knee arthroplasty provides superior short term functional outcomes: a meta-analysis. J Arthroplasty. 2014;29(5):938-944.
55. Zamora LA, Humphreys KJ, Watt AM, Forel D, Cameron AL. Systematic review of computer-navigated total knee arthroplasty. ANZ J Surg. 2013;83(1-2):22-30.
56. Liow MH, Xia Z, Wong MK, Tay KJ, Yeo SJ, Chin PL. Robot-assisted total knee arthroplasty accurately restores the joint line and mechanical axis. A prospective randomised study. J Arthroplasty. 2014;29(12):2373-2377.
57. Koulalis D, O’Loughlin PF, Plaskos C, Kendoff D, Cross MB, Pearle AD. Sequential versus automated cutting guides in computer-assisted total knee arthroplasty. Knee. 2011;18(6):436-442.
58. Clark TC, Schmidt FH. Robot-assisted navigation versus computer-assisted navigation in primary total knee arthroplasty: efficiency and accuracy. ISRN Orthop. 2013;2013:794827.
59. DiGioia AM 3rd, Jaramaz B, Colgan BD. Computer assisted orthopaedic surgery. Image guided and robotic assistive technologies. Clin Orthop Relat Res. 1998(354):8-16.
60. Conditt MA, Roche MW. Minimally invasive robotic-arm-guided unicompartmental knee arthroplasty. J Bone Joint Surg Am. 2009;91 Suppl 1:63-68.
61. Lonner JH. Robotically assisted unicompartmental knee arthroplasty with a handheld image-free sculpting tool. Orthop Clin North Am. 2016;47(1):29-40.
62. Koenig JA, Suero EM, Plaskos C. Surgical accuracy and efficiency of computer-navigated TKA with a robotic cutting guide–report on the first 100 cases. J Bone Joint Surg Br. 2012;94-B(SUPP XLIV):103. Available at: http://www.bjjprocs.boneandjoint.org.uk/content/94-B/SUPP_XLIV/103. Accessed April 6, 2016.
63. Siebert W, Mai S, Kober R, Heeckt PF. Technique and first clinical results of robot-assisted total knee replacement. Knee. 2002;9(3):173-180.
64. Schulz AP, Seide K, Queitsch C, et al. Results of total hip replacement using the Robodoc surgical assistant system: clinical outcome and evaluation of complications for 97 procedures. Int J Med Robot. 2007;3(4):301-306.
65. Kim SM, Park YS, Ha CW, Lim SJ, Moon YW. Robot-assisted implantation improves the precision of component position in minimally invasive TKA. Orthopedics. 2012;35(9):e1334-e1339.
66. Moon YW, Ha CW, Do KH, et al. Comparison of robot-assisted and conventional total knee arthroplasty: a controlled cadaver study using multiparameter quantitative three-dimensional CT assessment of alignment. Comput Aided Surg. 2012;17(2):86-95.
67. Park SE, Lee CT. Comparison of robotic-assisted and conventional manual implantation of a primary total knee arthroplasty. J Arthroplasty. 2007;22(7):1054-1059.
68. Song EK, Seon JK, Park SJ, Jung WB, Park HW, Lee GW. Simultaneous bilateral total knee arthroplasty with robotic and conventional techniques: a prospective, randomized study. Knee Surg Sports Traumatol Arthrosc. 2011;19(7):1069-1076.
69. Song EK, Seon JK, Yim JH, Netravali NA, Bargar WL. Robotic-assisted TKA reduces postoperative alignment outliers and improves gap balance compared to conventional TKA. Clin Orthop Relat Res. 2013;471(1):118-126.
70. Cobb J, Henckel J, Gomes P, et al. Hands-on robotic unicompartmental knee replacement: a prospective, randomised controlled study of the acrobot system. J Bone Joint Surg Br. 2006;88(2):188-197.
71. Jakopec M, Harris SJ, Rodriguez y Baena F, Gomes P, Cobb J, Davies BL. The first clinical application of a “hands-on” robotic knee surgery system. Comput Aided Surg. 2001;6(6):329-339.
72. Pearle AD, O’Loughlin PF, Kendoff DO. Robot-assisted unicompartmental knee arthroplasty. J Arthroplasty. 2010;25(2):230-237.
73. Dunbar NJ, Roche MW, Park BH, Branch SH, Conditt MA, Banks SA. Accuracy of dynamic tactile-guided unicompartmental knee arthroplasty. J Arthroplasty. 2012;27(5):803-808.e1.
74. Smith JR, Riches PE, Rowe PJ. Accuracy of a freehand sculpting tool for unicondylar knee replacement. Int J Med Robot. 2014;10(2):162-169.
75. Lonner JH, Smith JR, Picard F, Hamlin B, Rowe PJ, Riches PE. High degree of accuracy of a novel image-free handheld robot for unicondylar knee arthroplasty in a cadaveric study. Clin Orthop Relat Res. 2015;473(1):206-212.
76. Ponder C, Plaskos C, Cheal E. Press-fit total knee arthroplasty with a robotic-cutting guide: proof of concept and initial clinical experience. Bone & Joint Journal Orthopaedic Proceedings Supplement. 2013;95(SUPP 28):61. Available at: http://www.bjjprocs.boneandjoint.org.uk/content/95-B/SUPP_28/61.abstract. Accessed April 6, 2016.
77. Bellemans J, Vandenneucker H, Vanlauwe J. Robot-assisted total knee arthroplasty. Clin Orthop Relat Res. 2007;464:111-116.
78. Lonner JH, John TK, Conditt MA. Robotic arm-assisted UKA improves tibial component alignment: a pilot study. Clin Orthop Relat Res. 2010;468(1):141-146.
79. Citak M, Suero EM, Citak M, et al. Unicompartmental knee arthroplasty: is robotic technology more accurate than conventional technique? Knee. 2013;20(4):268-271.
80. MacCallum KP, Danoff JR, Geller JA. Tibial baseplate positioning in robotic-assisted and conventional unicompartmental knee arthroplasty. Eur J Orthop Surg Traumatol. 2016;26(1):93-98.
81. Coon T, Roche M, Pearle AD, Dounchis J, Borus T, Buechel F Jr. Two year survivorship of robotically guided unicompartmental knee arthroplasty. Paper presented at: International Society for Technology in Arthroplasty 26th Annual Congress; October 16-19, 2013; Palm Beach, FL.
82. Pandit H, Jenkins C, Gill HS, Barker K, Dodd CA, Murray DW. Minimally invasive Oxford phase 3 unicompartmental knee replacement: results of 1000 cases. J Bone Joint Surg Br. 2011;93(2):198-204.
83. Yoshida K, Tada M, Yoshida H, Takei S, Fukuoka S, Nakamura H. Oxford phase 3 unicompartmental knee arthroplasty in Japan--clinical results in greater than one thousand cases over ten years. J Arthroplasty. 2013;28(9 Suppl):168-171.
84. Swank ML, Alkire M, Conditt M, Lonner JH. Technology and cost-effectiveness in knee arthroplasty: computer navigation and robotics. Am J Orthop. 2009;38(2 Suppl):32-36.
85. Moschetti WE, Konopka JF, Rubash HE, Genuario JW. Can robot-assisted unicompartmental knee arthroplasty be cost-effective? A markovdecision analysis. J Arthroplasty. 2015. [Epub ahead of print]
86. Thienpont E. Improving Accuracy in Knee Arthroplasty. 1st ed. New Delhi, India: Jaypee Brothers Medical Publishers; 2012.
Chlorhexidine-alcohol skin prep reduced SSIs after abdominal hysterectomy
INDIAN WELLS, CALIF. – Using chlorhexidine-alcohol preoperative skin antisepsis at the time of abdominal hysterectomy is associated with a lower incidence of surgical site infections (SSIs), compared with using povidone-iodine antiseptic solution, a large retrospective study showed.
“Surgical site infections have been linked to longer hospital stays, higher readmission rates, and overall increased healthcare costs,” Ali Bazzi, the lead study author, said at the annual scientific meeting of the Society of Gynecologic Surgeons. “Preoperative topical skin antiseptics have decreased the rate of SSIs over the years and have led to improved patient outcomes. Current published guidelines for skin preparations, specifically abdominal hysterectomies, do not routinely specify a choice of antiseptic. With greater than 500,000 hysterectomies performed each year in the United States, and about half done via laparotomy, this can have significant clinical implications.”
In an effort to determine whether the choice of preoperative topical antisepsis independently affects SSIs, Mr. Bazzi, a fourth-year medical student at the University of Michigan, Ann Arbor, and his associates in the university’s department of gynecologic oncology evaluated chlorhexidine-gluconate in alcohol versus povidone-iodine in aqueous solution. The second objective focused on determining certain patient factors and operative predictors of SSIs.
The researchers used the Michigan Surgical Quality Collaborative database to perform a retrospective cohort analysis of patients who underwent abdominal hysterectomy from July 2012 to February 2015. The primary outcome was diagnosis of a superficial, deep, or organ space SSI within 30 days of surgery, while the primary predictor was whether the individual cases received either the chlorhexidine-alcohol or the povidone-iodine antiseptic solution.
The researchers excluded cases with missing data, preoperative sepsis or emergent operative cases, and patients on chronic steroids due to immunosuppression, since these cases were associated with a higher than baseline risk of developing SSIs. Other types of skin preparation agents did not meet a large enough sample size and thus were underpowered. These cases were not included in the final analysis. Multivariate logistic regression models estimated the independent effect of skin antiseptic choice on the rate of SSI.
Mr. Bazzi reported results from 5,074 abdominal hysterectomies. Compared with patients in the povidone-iodine group, those in the chlorhexidine-alcohol group had several medical comorbidities, demographic and perioperative factors associated with the development of SSIs, including being more likely to have a BMI of 30 kg/m2 or greater; American Society of Anesthesiology Class of 3 or greater; dependent functional status; malignancy as a preoperative indication for surgery; estimated blood loss of greater than 250 cc; and surgery lasting longer than 3 hours.
The overall rate of any SSI was 3.6%. The unadjusted SSI rates based on antiseptic choice were 3.5% in the chlorhexidine-alcohol group and 3.8% in the povidone-iodine group. After using multivariate logistic regression adjusted for population differences, the researchers determined that chlorhexidine-alcohol was associated with a 30% lower odds of developing SSIs, compared with those in the povidone-iodine group (odds ratio, 0.71; 95% confidence interval, 0.51-0.98; P = .037).
Mr. Bazzi, who begins an ob.gyn. residency at St. John Hospital and Medical Center in Detroit in July 2016, acknowledged that other qualitative factors not included in the analysis could affect the incidence of SSIs, such as operative experience, surgical technique, resident exposure, type of ligature used, and excessive use of electrosurgical devices.
He noted that future randomized, controlled trials of skin antiseptic preparations given prior to abdominal hysterectomy would be helpful. For now, “we believe that future guidelines should specify the choice of antisepsis prior to abdominal hysterectomy,” he said at the meeting, which is jointly sponsored by the American College of Surgeons.
Mr. Bazzi reported having no financial disclosures.
INDIAN WELLS, CALIF. – Using chlorhexidine-alcohol preoperative skin antisepsis at the time of abdominal hysterectomy is associated with a lower incidence of surgical site infections (SSIs), compared with using povidone-iodine antiseptic solution, a large retrospective study showed.
“Surgical site infections have been linked to longer hospital stays, higher readmission rates, and overall increased healthcare costs,” Ali Bazzi, the lead study author, said at the annual scientific meeting of the Society of Gynecologic Surgeons. “Preoperative topical skin antiseptics have decreased the rate of SSIs over the years and have led to improved patient outcomes. Current published guidelines for skin preparations, specifically abdominal hysterectomies, do not routinely specify a choice of antiseptic. With greater than 500,000 hysterectomies performed each year in the United States, and about half done via laparotomy, this can have significant clinical implications.”
In an effort to determine whether the choice of preoperative topical antisepsis independently affects SSIs, Mr. Bazzi, a fourth-year medical student at the University of Michigan, Ann Arbor, and his associates in the university’s department of gynecologic oncology evaluated chlorhexidine-gluconate in alcohol versus povidone-iodine in aqueous solution. The second objective focused on determining certain patient factors and operative predictors of SSIs.
The researchers used the Michigan Surgical Quality Collaborative database to perform a retrospective cohort analysis of patients who underwent abdominal hysterectomy from July 2012 to February 2015. The primary outcome was diagnosis of a superficial, deep, or organ space SSI within 30 days of surgery, while the primary predictor was whether the individual cases received either the chlorhexidine-alcohol or the povidone-iodine antiseptic solution.
The researchers excluded cases with missing data, preoperative sepsis or emergent operative cases, and patients on chronic steroids due to immunosuppression, since these cases were associated with a higher than baseline risk of developing SSIs. Other types of skin preparation agents did not meet a large enough sample size and thus were underpowered. These cases were not included in the final analysis. Multivariate logistic regression models estimated the independent effect of skin antiseptic choice on the rate of SSI.
Mr. Bazzi reported results from 5,074 abdominal hysterectomies. Compared with patients in the povidone-iodine group, those in the chlorhexidine-alcohol group had several medical comorbidities, demographic and perioperative factors associated with the development of SSIs, including being more likely to have a BMI of 30 kg/m2 or greater; American Society of Anesthesiology Class of 3 or greater; dependent functional status; malignancy as a preoperative indication for surgery; estimated blood loss of greater than 250 cc; and surgery lasting longer than 3 hours.
The overall rate of any SSI was 3.6%. The unadjusted SSI rates based on antiseptic choice were 3.5% in the chlorhexidine-alcohol group and 3.8% in the povidone-iodine group. After using multivariate logistic regression adjusted for population differences, the researchers determined that chlorhexidine-alcohol was associated with a 30% lower odds of developing SSIs, compared with those in the povidone-iodine group (odds ratio, 0.71; 95% confidence interval, 0.51-0.98; P = .037).
Mr. Bazzi, who begins an ob.gyn. residency at St. John Hospital and Medical Center in Detroit in July 2016, acknowledged that other qualitative factors not included in the analysis could affect the incidence of SSIs, such as operative experience, surgical technique, resident exposure, type of ligature used, and excessive use of electrosurgical devices.
He noted that future randomized, controlled trials of skin antiseptic preparations given prior to abdominal hysterectomy would be helpful. For now, “we believe that future guidelines should specify the choice of antisepsis prior to abdominal hysterectomy,” he said at the meeting, which is jointly sponsored by the American College of Surgeons.
Mr. Bazzi reported having no financial disclosures.
INDIAN WELLS, CALIF. – Using chlorhexidine-alcohol preoperative skin antisepsis at the time of abdominal hysterectomy is associated with a lower incidence of surgical site infections (SSIs), compared with using povidone-iodine antiseptic solution, a large retrospective study showed.
“Surgical site infections have been linked to longer hospital stays, higher readmission rates, and overall increased healthcare costs,” Ali Bazzi, the lead study author, said at the annual scientific meeting of the Society of Gynecologic Surgeons. “Preoperative topical skin antiseptics have decreased the rate of SSIs over the years and have led to improved patient outcomes. Current published guidelines for skin preparations, specifically abdominal hysterectomies, do not routinely specify a choice of antiseptic. With greater than 500,000 hysterectomies performed each year in the United States, and about half done via laparotomy, this can have significant clinical implications.”
In an effort to determine whether the choice of preoperative topical antisepsis independently affects SSIs, Mr. Bazzi, a fourth-year medical student at the University of Michigan, Ann Arbor, and his associates in the university’s department of gynecologic oncology evaluated chlorhexidine-gluconate in alcohol versus povidone-iodine in aqueous solution. The second objective focused on determining certain patient factors and operative predictors of SSIs.
The researchers used the Michigan Surgical Quality Collaborative database to perform a retrospective cohort analysis of patients who underwent abdominal hysterectomy from July 2012 to February 2015. The primary outcome was diagnosis of a superficial, deep, or organ space SSI within 30 days of surgery, while the primary predictor was whether the individual cases received either the chlorhexidine-alcohol or the povidone-iodine antiseptic solution.
The researchers excluded cases with missing data, preoperative sepsis or emergent operative cases, and patients on chronic steroids due to immunosuppression, since these cases were associated with a higher than baseline risk of developing SSIs. Other types of skin preparation agents did not meet a large enough sample size and thus were underpowered. These cases were not included in the final analysis. Multivariate logistic regression models estimated the independent effect of skin antiseptic choice on the rate of SSI.
Mr. Bazzi reported results from 5,074 abdominal hysterectomies. Compared with patients in the povidone-iodine group, those in the chlorhexidine-alcohol group had several medical comorbidities, demographic and perioperative factors associated with the development of SSIs, including being more likely to have a BMI of 30 kg/m2 or greater; American Society of Anesthesiology Class of 3 or greater; dependent functional status; malignancy as a preoperative indication for surgery; estimated blood loss of greater than 250 cc; and surgery lasting longer than 3 hours.
The overall rate of any SSI was 3.6%. The unadjusted SSI rates based on antiseptic choice were 3.5% in the chlorhexidine-alcohol group and 3.8% in the povidone-iodine group. After using multivariate logistic regression adjusted for population differences, the researchers determined that chlorhexidine-alcohol was associated with a 30% lower odds of developing SSIs, compared with those in the povidone-iodine group (odds ratio, 0.71; 95% confidence interval, 0.51-0.98; P = .037).
Mr. Bazzi, who begins an ob.gyn. residency at St. John Hospital and Medical Center in Detroit in July 2016, acknowledged that other qualitative factors not included in the analysis could affect the incidence of SSIs, such as operative experience, surgical technique, resident exposure, type of ligature used, and excessive use of electrosurgical devices.
He noted that future randomized, controlled trials of skin antiseptic preparations given prior to abdominal hysterectomy would be helpful. For now, “we believe that future guidelines should specify the choice of antisepsis prior to abdominal hysterectomy,” he said at the meeting, which is jointly sponsored by the American College of Surgeons.
Mr. Bazzi reported having no financial disclosures.
AT SGS 2016
Key clinical point: Chlorhexidine-alcohol preoperative skin antisepsis at the time of abdominal hysterectomy was superior to povidone-iodine antiseptic solution in reducing SSIs.
Major finding: The use of chlorhexidine-alcohol preoperative skin antisepsis at the time of abdominal hysterectomy was associated with about a 30% lower odds of developing SSIs, compared with using povidone-iodine antiseptic solution (odds ratio, 0.71).
Data source: A retrospective cohort analysis of 5,074 patients who underwent abdominal hysterectomy from July 2012 to February 2015.
Disclosures: Mr. Bazzi reported having no financial disclosures.
Study identifies cognitive impairment in elderly urogynecologic patients
INDIAN WELLS, CALIF. – A rapid screening tool found that about 5% of urogynecologic patients aged 65-74 years showed signs of cognitive impairment, with that figure rising to more than 30% for patients age 85 and older, according to the results of a single-center study.
“As our gynecologic patients continue to age, it’s increasingly important that we continue to identify and manage the risk factors for cognitive decline that occur in the ambulatory and the perioperative care settings,” Dr. Elisa R. Trowbridge, lead study author, said at the annual scientific meeting of the Society of Gynecologic Surgeons. “However, data are lacking to describe the prevalence of cognitive impairment in this very specific population.”
In 2013, the Centers for Disease Control and Prevention estimated that one in eight patients older than 60 years of age deal with memory loss and confusion. However, fewer than 20% of these patients report this to their health care providers, said Dr. Trowbridge, division director of the University of Virginia Women’s Center for Continence and Pelvic Surgery in Charlottesville.
“For this reason the aim of our study was to evaluate the prevalence of cognitive impairment in a urogynecologic ambulatory population, and to evaluate the feasibility of using a standardized, validated screening questionnaire in the tertiary care setting,” she said.
The researchers invited 371 English-speaking patients aged 65 and older to participate and used two cognitive screening tools: the Mini-Cog and the AD8 (8-item Interview to Differentiate Aging and Dementia). They also used the Geriatric Depression Scale, as there is an association between depression and cognition in the elderly.
“Advantages of the Mini-Cog are that it’s administered in less than 3 minutes, it requires no special equipment, and it is not influenced by level of education, or any language variations,” Dr. Trowbridge said.
Of the 371 patients, 39 were excluded due to pre-existing cognitive impairment/dementia, active psychotic disorders, acute/unstable medical conditions, neurologic injury/disorders, alcohol/drug abuse, severe visual/hearing impairment, and illiteracy. An additional 37 patients declined to participate because they “were frustrated that we had asked to evaluate their memory,” she said. This left a total of 295 patients with a mean age of 75 years. Most (97%) were Caucasian, 62% were married, and each had an average of four major medical conditions, including hypertension, hyperlipidemia, and depression. The researchers stratified patients into three age groups: 65-74, 75-84, and 85 and older.
Cognitive impairment as measured by the Mini-Cog was identified in 5.3% of patients aged 65-74 years, 13.7% of those aged 75-84 years, and 31% of those aged 85 and older. The difference in impairment between those aged 65-74 years and those aged 75 years and older reached significance, with a P value of less than .001.
Cognitive impairment as measured by the AD8 found that all three age groups perceived themselves to have early cognitive changes: 25.9% of patients aged 65-74 years, 31.9% of those aged 75-84 years, and 40% of those aged 85 and older. There were no significant between-group differences in these results (P = .4). The most commonly identified areas of impairment were problems with thinking and memory (62%), judgment (52%), and trouble learning new tools or gadgets (44%).
Dr. Trowbridge also reported that 6.4% of the study population screened positive for depression on the Geriatric Depression Scale, with no significant differences between the age groups.
“In our study population, cognitive impairment as measured by a validated questionnaire is prevalent among women greater than 75 years of age,” she said at the meeting, which was jointly sponsored by the American College of Surgeons. “The Mini-Cog is a feasible screening tool for routine use in clinical practice that can be integrated easily into the urogynecologic evaluation. However, remember these are screening tools that effectively screen for previously unrecognized impairment, but a definitive diagnosis requires additional evaluation.”
Dr. Trowbridge reported having no financial disclosures.
INDIAN WELLS, CALIF. – A rapid screening tool found that about 5% of urogynecologic patients aged 65-74 years showed signs of cognitive impairment, with that figure rising to more than 30% for patients age 85 and older, according to the results of a single-center study.
“As our gynecologic patients continue to age, it’s increasingly important that we continue to identify and manage the risk factors for cognitive decline that occur in the ambulatory and the perioperative care settings,” Dr. Elisa R. Trowbridge, lead study author, said at the annual scientific meeting of the Society of Gynecologic Surgeons. “However, data are lacking to describe the prevalence of cognitive impairment in this very specific population.”
In 2013, the Centers for Disease Control and Prevention estimated that one in eight patients older than 60 years of age deal with memory loss and confusion. However, fewer than 20% of these patients report this to their health care providers, said Dr. Trowbridge, division director of the University of Virginia Women’s Center for Continence and Pelvic Surgery in Charlottesville.
“For this reason the aim of our study was to evaluate the prevalence of cognitive impairment in a urogynecologic ambulatory population, and to evaluate the feasibility of using a standardized, validated screening questionnaire in the tertiary care setting,” she said.
The researchers invited 371 English-speaking patients aged 65 and older to participate and used two cognitive screening tools: the Mini-Cog and the AD8 (8-item Interview to Differentiate Aging and Dementia). They also used the Geriatric Depression Scale, as there is an association between depression and cognition in the elderly.
“Advantages of the Mini-Cog are that it’s administered in less than 3 minutes, it requires no special equipment, and it is not influenced by level of education, or any language variations,” Dr. Trowbridge said.
Of the 371 patients, 39 were excluded due to pre-existing cognitive impairment/dementia, active psychotic disorders, acute/unstable medical conditions, neurologic injury/disorders, alcohol/drug abuse, severe visual/hearing impairment, and illiteracy. An additional 37 patients declined to participate because they “were frustrated that we had asked to evaluate their memory,” she said. This left a total of 295 patients with a mean age of 75 years. Most (97%) were Caucasian, 62% were married, and each had an average of four major medical conditions, including hypertension, hyperlipidemia, and depression. The researchers stratified patients into three age groups: 65-74, 75-84, and 85 and older.
Cognitive impairment as measured by the Mini-Cog was identified in 5.3% of patients aged 65-74 years, 13.7% of those aged 75-84 years, and 31% of those aged 85 and older. The difference in impairment between those aged 65-74 years and those aged 75 years and older reached significance, with a P value of less than .001.
Cognitive impairment as measured by the AD8 found that all three age groups perceived themselves to have early cognitive changes: 25.9% of patients aged 65-74 years, 31.9% of those aged 75-84 years, and 40% of those aged 85 and older. There were no significant between-group differences in these results (P = .4). The most commonly identified areas of impairment were problems with thinking and memory (62%), judgment (52%), and trouble learning new tools or gadgets (44%).
Dr. Trowbridge also reported that 6.4% of the study population screened positive for depression on the Geriatric Depression Scale, with no significant differences between the age groups.
“In our study population, cognitive impairment as measured by a validated questionnaire is prevalent among women greater than 75 years of age,” she said at the meeting, which was jointly sponsored by the American College of Surgeons. “The Mini-Cog is a feasible screening tool for routine use in clinical practice that can be integrated easily into the urogynecologic evaluation. However, remember these are screening tools that effectively screen for previously unrecognized impairment, but a definitive diagnosis requires additional evaluation.”
Dr. Trowbridge reported having no financial disclosures.
INDIAN WELLS, CALIF. – A rapid screening tool found that about 5% of urogynecologic patients aged 65-74 years showed signs of cognitive impairment, with that figure rising to more than 30% for patients age 85 and older, according to the results of a single-center study.
“As our gynecologic patients continue to age, it’s increasingly important that we continue to identify and manage the risk factors for cognitive decline that occur in the ambulatory and the perioperative care settings,” Dr. Elisa R. Trowbridge, lead study author, said at the annual scientific meeting of the Society of Gynecologic Surgeons. “However, data are lacking to describe the prevalence of cognitive impairment in this very specific population.”
In 2013, the Centers for Disease Control and Prevention estimated that one in eight patients older than 60 years of age deal with memory loss and confusion. However, fewer than 20% of these patients report this to their health care providers, said Dr. Trowbridge, division director of the University of Virginia Women’s Center for Continence and Pelvic Surgery in Charlottesville.
“For this reason the aim of our study was to evaluate the prevalence of cognitive impairment in a urogynecologic ambulatory population, and to evaluate the feasibility of using a standardized, validated screening questionnaire in the tertiary care setting,” she said.
The researchers invited 371 English-speaking patients aged 65 and older to participate and used two cognitive screening tools: the Mini-Cog and the AD8 (8-item Interview to Differentiate Aging and Dementia). They also used the Geriatric Depression Scale, as there is an association between depression and cognition in the elderly.
“Advantages of the Mini-Cog are that it’s administered in less than 3 minutes, it requires no special equipment, and it is not influenced by level of education, or any language variations,” Dr. Trowbridge said.
Of the 371 patients, 39 were excluded due to pre-existing cognitive impairment/dementia, active psychotic disorders, acute/unstable medical conditions, neurologic injury/disorders, alcohol/drug abuse, severe visual/hearing impairment, and illiteracy. An additional 37 patients declined to participate because they “were frustrated that we had asked to evaluate their memory,” she said. This left a total of 295 patients with a mean age of 75 years. Most (97%) were Caucasian, 62% were married, and each had an average of four major medical conditions, including hypertension, hyperlipidemia, and depression. The researchers stratified patients into three age groups: 65-74, 75-84, and 85 and older.
Cognitive impairment as measured by the Mini-Cog was identified in 5.3% of patients aged 65-74 years, 13.7% of those aged 75-84 years, and 31% of those aged 85 and older. The difference in impairment between those aged 65-74 years and those aged 75 years and older reached significance, with a P value of less than .001.
Cognitive impairment as measured by the AD8 found that all three age groups perceived themselves to have early cognitive changes: 25.9% of patients aged 65-74 years, 31.9% of those aged 75-84 years, and 40% of those aged 85 and older. There were no significant between-group differences in these results (P = .4). The most commonly identified areas of impairment were problems with thinking and memory (62%), judgment (52%), and trouble learning new tools or gadgets (44%).
Dr. Trowbridge also reported that 6.4% of the study population screened positive for depression on the Geriatric Depression Scale, with no significant differences between the age groups.
“In our study population, cognitive impairment as measured by a validated questionnaire is prevalent among women greater than 75 years of age,” she said at the meeting, which was jointly sponsored by the American College of Surgeons. “The Mini-Cog is a feasible screening tool for routine use in clinical practice that can be integrated easily into the urogynecologic evaluation. However, remember these are screening tools that effectively screen for previously unrecognized impairment, but a definitive diagnosis requires additional evaluation.”
Dr. Trowbridge reported having no financial disclosures.
AT SGS 2016
Key clinical point: The Mini-Cog is a feasible screening tool for routine use in clinical practice that can be integrated easily into the urogynecologic evaluation.
Major finding: Cognitive impairment as measured by the Mini-Cog was identified in 5.3% of patients aged 65-74 years, 13.7% of those aged 75-84 years, and 31% of those aged 85 and older.
Data source: A single-center study of 295 urogynecologic patients aged 65 and older.
Disclosures: Dr. Trowbridge reported having no financial disclosures.
Bortezomib-based regimen + transplant increased progression-free survival in primary plasma cell leukemia
In a prospective study of 40 patients with primary plasma cell leukemia, upfront autotransplantation followed by allotransplant for younger patients and by consolidation/maintenance for older patients was associated with a median overall survival of 36.3 months and a median progression-free survival of 15.1 months.
Patients with this aggressive form of multiple myeloma received a regimen that combined standard chemotherapy, a proteasome inhibitor, high-dose melphalan followed by autologous stem cell transplantation, and allogeneic transplantation or immunomodulatory drugs, reported Dr. Bruno Royer of University Hospital in Amiens, France, and his associates.
Induction therapy consisted of four 21-day cycles: Cycles 1 and 3 included subcutaneous bortezomib, intravenous pegylated doxorubicin, and oral dexamethasone; cycles 2 and 4 included subcutaneous bortezomib, oral cyclophosphamide, and oral dexamethasone. Of 39 patients – one patient died 24 hours after study inclusion – 35 completed the four cycles. The overall response rate to induction was 69%: 10% of patients had a complete response and 26% had a very good partial response. Of 27 responding patients, 25 underwent high-dose melphalan followed by autologous stem cell transplantation.
The high response rates allowed 16 patients who were younger than 66 years and had an HLA-matched donor to then receive high-dose melphalan followed by autologous stem cell transplantation followed by consolidation with either an reduced-intensity conditioning allograft or a second high-dose melphalan followed by autologous stem cell transplantation and subsequent maintenance with lenalidomide, bortezomib, and dexamethasone for 1 year, the researchers said (J Clin Oncol. 2016 Apr 25. doi: 10.1200/JCO.2015.63.1929).
A total of 20% of patients had a complete response to the entire treatment protocol, 13% had a stringent complete response, 26% had a very good partial response, 5% had stable disease, and 5% had progressive disease. Thirteen patients died of progressive disease and four died of infections, including three that occurred during induction or after allograft.
This is only the second prospective trial in patients with primary plasma cell leukemia, an aggressive form of multiple myeloma that accounts for 2%-4% of cases, the researchers said. Future prospective trials should seek to optimize induction with newer combinations, such as carfilzomib, lenalidomide, dexamethasone, or monoclonal anti-CD38 antibodies. Also, optimizing the stem cell conditioning procedure and the postallograft immunomodulation may further benefit younger patients.
Dr. Royer reported receiving honoraria from Amgen and having served as a consultant or advisor for Octapharma Plasma. Fifteen coinvestigators also reported financial relationships with a number of pharmaceutical companies.
The study by Dr. Royer and associates is the first prospective trial to confirm that bortezomib-based regimens combined with a transplantation program may be effective and feasible in a significant proportion of patients with primary plasma cell leukemia. Response to induction therapy, however, was not remarkable; thus, although both cyclophosphamide and doxorubicin have demonstrated efficacy in primary plasma cell leukemia, the introduction of lenalidomide and/or incorporation of newer agents such as pomalidomide, carfilzomib, or daratumumab could hopefully optimize the induction phase and increase the rate and quality of response in future studies.
Hopefully, sequential phases of induction therapy, multiple transplantations (if applicable), further consolidation, and maintenance should ensure rapid disease control and reduction of early deaths from initial complications, a contrasting of clonal evolution that may induce drug resistance, and activity on residual disease by decreasing the risk of relapse. Feasibility of these approaches, however, may be limited, especially for older and frail patients who are unable to tolerate intensive induction or prolonged treatments. Personalized therapies with acceptable toxicities should be considered for these patients.
Dr. Pellegrino Musto is at Referral Cancer Center of Basilicata, Rionero in Vulture, Italy. He reported receiving honoraria from Celgene, Janssen-Cilag, Novartis, Sanofi, and Bristol-Myers Squibb. These comments are from an editorial (J Clin Oncol. 2016 Apr 25. doi: 10.1200/JCO.2016.66.6115) that accompanied the published study.
The study by Dr. Royer and associates is the first prospective trial to confirm that bortezomib-based regimens combined with a transplantation program may be effective and feasible in a significant proportion of patients with primary plasma cell leukemia. Response to induction therapy, however, was not remarkable; thus, although both cyclophosphamide and doxorubicin have demonstrated efficacy in primary plasma cell leukemia, the introduction of lenalidomide and/or incorporation of newer agents such as pomalidomide, carfilzomib, or daratumumab could hopefully optimize the induction phase and increase the rate and quality of response in future studies.
Hopefully, sequential phases of induction therapy, multiple transplantations (if applicable), further consolidation, and maintenance should ensure rapid disease control and reduction of early deaths from initial complications, a contrasting of clonal evolution that may induce drug resistance, and activity on residual disease by decreasing the risk of relapse. Feasibility of these approaches, however, may be limited, especially for older and frail patients who are unable to tolerate intensive induction or prolonged treatments. Personalized therapies with acceptable toxicities should be considered for these patients.
Dr. Pellegrino Musto is at Referral Cancer Center of Basilicata, Rionero in Vulture, Italy. He reported receiving honoraria from Celgene, Janssen-Cilag, Novartis, Sanofi, and Bristol-Myers Squibb. These comments are from an editorial (J Clin Oncol. 2016 Apr 25. doi: 10.1200/JCO.2016.66.6115) that accompanied the published study.
The study by Dr. Royer and associates is the first prospective trial to confirm that bortezomib-based regimens combined with a transplantation program may be effective and feasible in a significant proportion of patients with primary plasma cell leukemia. Response to induction therapy, however, was not remarkable; thus, although both cyclophosphamide and doxorubicin have demonstrated efficacy in primary plasma cell leukemia, the introduction of lenalidomide and/or incorporation of newer agents such as pomalidomide, carfilzomib, or daratumumab could hopefully optimize the induction phase and increase the rate and quality of response in future studies.
Hopefully, sequential phases of induction therapy, multiple transplantations (if applicable), further consolidation, and maintenance should ensure rapid disease control and reduction of early deaths from initial complications, a contrasting of clonal evolution that may induce drug resistance, and activity on residual disease by decreasing the risk of relapse. Feasibility of these approaches, however, may be limited, especially for older and frail patients who are unable to tolerate intensive induction or prolonged treatments. Personalized therapies with acceptable toxicities should be considered for these patients.
Dr. Pellegrino Musto is at Referral Cancer Center of Basilicata, Rionero in Vulture, Italy. He reported receiving honoraria from Celgene, Janssen-Cilag, Novartis, Sanofi, and Bristol-Myers Squibb. These comments are from an editorial (J Clin Oncol. 2016 Apr 25. doi: 10.1200/JCO.2016.66.6115) that accompanied the published study.
In a prospective study of 40 patients with primary plasma cell leukemia, upfront autotransplantation followed by allotransplant for younger patients and by consolidation/maintenance for older patients was associated with a median overall survival of 36.3 months and a median progression-free survival of 15.1 months.
Patients with this aggressive form of multiple myeloma received a regimen that combined standard chemotherapy, a proteasome inhibitor, high-dose melphalan followed by autologous stem cell transplantation, and allogeneic transplantation or immunomodulatory drugs, reported Dr. Bruno Royer of University Hospital in Amiens, France, and his associates.
Induction therapy consisted of four 21-day cycles: Cycles 1 and 3 included subcutaneous bortezomib, intravenous pegylated doxorubicin, and oral dexamethasone; cycles 2 and 4 included subcutaneous bortezomib, oral cyclophosphamide, and oral dexamethasone. Of 39 patients – one patient died 24 hours after study inclusion – 35 completed the four cycles. The overall response rate to induction was 69%: 10% of patients had a complete response and 26% had a very good partial response. Of 27 responding patients, 25 underwent high-dose melphalan followed by autologous stem cell transplantation.
The high response rates allowed 16 patients who were younger than 66 years and had an HLA-matched donor to then receive high-dose melphalan followed by autologous stem cell transplantation followed by consolidation with either an reduced-intensity conditioning allograft or a second high-dose melphalan followed by autologous stem cell transplantation and subsequent maintenance with lenalidomide, bortezomib, and dexamethasone for 1 year, the researchers said (J Clin Oncol. 2016 Apr 25. doi: 10.1200/JCO.2015.63.1929).
A total of 20% of patients had a complete response to the entire treatment protocol, 13% had a stringent complete response, 26% had a very good partial response, 5% had stable disease, and 5% had progressive disease. Thirteen patients died of progressive disease and four died of infections, including three that occurred during induction or after allograft.
This is only the second prospective trial in patients with primary plasma cell leukemia, an aggressive form of multiple myeloma that accounts for 2%-4% of cases, the researchers said. Future prospective trials should seek to optimize induction with newer combinations, such as carfilzomib, lenalidomide, dexamethasone, or monoclonal anti-CD38 antibodies. Also, optimizing the stem cell conditioning procedure and the postallograft immunomodulation may further benefit younger patients.
Dr. Royer reported receiving honoraria from Amgen and having served as a consultant or advisor for Octapharma Plasma. Fifteen coinvestigators also reported financial relationships with a number of pharmaceutical companies.
In a prospective study of 40 patients with primary plasma cell leukemia, upfront autotransplantation followed by allotransplant for younger patients and by consolidation/maintenance for older patients was associated with a median overall survival of 36.3 months and a median progression-free survival of 15.1 months.
Patients with this aggressive form of multiple myeloma received a regimen that combined standard chemotherapy, a proteasome inhibitor, high-dose melphalan followed by autologous stem cell transplantation, and allogeneic transplantation or immunomodulatory drugs, reported Dr. Bruno Royer of University Hospital in Amiens, France, and his associates.
Induction therapy consisted of four 21-day cycles: Cycles 1 and 3 included subcutaneous bortezomib, intravenous pegylated doxorubicin, and oral dexamethasone; cycles 2 and 4 included subcutaneous bortezomib, oral cyclophosphamide, and oral dexamethasone. Of 39 patients – one patient died 24 hours after study inclusion – 35 completed the four cycles. The overall response rate to induction was 69%: 10% of patients had a complete response and 26% had a very good partial response. Of 27 responding patients, 25 underwent high-dose melphalan followed by autologous stem cell transplantation.
The high response rates allowed 16 patients who were younger than 66 years and had an HLA-matched donor to then receive high-dose melphalan followed by autologous stem cell transplantation followed by consolidation with either an reduced-intensity conditioning allograft or a second high-dose melphalan followed by autologous stem cell transplantation and subsequent maintenance with lenalidomide, bortezomib, and dexamethasone for 1 year, the researchers said (J Clin Oncol. 2016 Apr 25. doi: 10.1200/JCO.2015.63.1929).
A total of 20% of patients had a complete response to the entire treatment protocol, 13% had a stringent complete response, 26% had a very good partial response, 5% had stable disease, and 5% had progressive disease. Thirteen patients died of progressive disease and four died of infections, including three that occurred during induction or after allograft.
This is only the second prospective trial in patients with primary plasma cell leukemia, an aggressive form of multiple myeloma that accounts for 2%-4% of cases, the researchers said. Future prospective trials should seek to optimize induction with newer combinations, such as carfilzomib, lenalidomide, dexamethasone, or monoclonal anti-CD38 antibodies. Also, optimizing the stem cell conditioning procedure and the postallograft immunomodulation may further benefit younger patients.
Dr. Royer reported receiving honoraria from Amgen and having served as a consultant or advisor for Octapharma Plasma. Fifteen coinvestigators also reported financial relationships with a number of pharmaceutical companies.
FROM THE JOURNAL OF CLINICAL ONCOLOGY
Key clinical point: Progression-free survival was improved in patients who had primary plasma cell leukemia and underwent four cycles of induction; high-dose melphalan followed by autologous stem cell transplantation; consolidation with either a reduced-intensity conditioning allograft or a second high-dose melphalan followed by autologous stem cell transplantation; and subsequent maintenance with lenalidomide, bortezomib, and dexamethasone for 1 year.
Major finding: Median overall survival was 36.3 months and median progression-free survival was 15.1 months.
Data source: A prospective phase II study of 40 adults with newly diagnosed primary plasma cell leukemia.
Disclosures: Dr. Royer reported receiving honoraria from Amgen and having served as a consultant or advisor for Octapharma Plasma. Fifteen coinvestigators also reported financial relationships with various drug companies.
Engaging Your Patients in Decision-Making Processes Yields Better Outcomes
Editor’s note: “Everything We Say and Do” is an informational series developed by SHM’s Patient Experience Committee to provide readers with thoughtful and actionable communication tactics that have great potential to positively impact patients’ experience of care. Each column will focus on how the contributor applies one of the “Key Communication” areas in practice.
View a chart outlining key communication tactics
What I Say and Do
I counsel and deliver the diagnosis or give recommendations through a dialogue, instead of a monologue, using active listening.
Why I Do It
The monologue, or lecture, is among the least effective ways to instill behavior change. Research studies have demonstrated that, after a monologue, only around 20% to 60% of medical information is remembered by the end of a visit. Out of what is remembered, less than 50% is accurate. Furthermore, 47% of Americans have health literacy levels below the intermediate range, defined as the ability to determine when to take a medication with food from reading the label.
Lecturing the patient without first understanding what the patient knows and finds important, and understanding the barriers to plan implementation, runs the risk of decreased comprehension, a lack of understanding, or a lack of personal relevance—all leading to decreased adherence. Doing the opposite, by involving the patient in decision making, inspires change that comes from within in the context of the patient’s own needs. This approach is more enduring, emphasizes self-accountability, and ultimately leads to better outcomes.
How I Do It
I open up a dialogue using the Cleveland Clinic’s ARIA approach as adapted from the REDE model of healthcare communication.1
- First, assess: What does the patient know about diagnosis and treatment? How much and what type of education does the patient desire/need? What are the patient’s treatment preferences and health literacy?
- Second, reflect on what the patient just said. Validate meaning and emotion.
- Third, inform the patient within the context of the patient’s perspectives and preferences. Speak slowly and provide small chunks of information at a time. Use understandable language and visual aids. (This will increase recall by 60%.)
- Finally, assess the patient’s understanding and emotional reaction to information provided.
- Repeat the cycle to introduce other chunks of information.
Dr. Velez is director of faculty development in the Center for Excellence in Healthcare Communication at the Cleveland Clinic.
Reference
- Windover A, Boissy A, Rice T, Gilligan T, Velez V, Merlino J. The REDE model of healthcare communication: optimizing relationship as a therapeutic agent. J Patient Exp. 2014;1(1):8-13.
Editor’s note: “Everything We Say and Do” is an informational series developed by SHM’s Patient Experience Committee to provide readers with thoughtful and actionable communication tactics that have great potential to positively impact patients’ experience of care. Each column will focus on how the contributor applies one of the “Key Communication” areas in practice.
View a chart outlining key communication tactics
What I Say and Do
I counsel and deliver the diagnosis or give recommendations through a dialogue, instead of a monologue, using active listening.
Why I Do It
The monologue, or lecture, is among the least effective ways to instill behavior change. Research studies have demonstrated that, after a monologue, only around 20% to 60% of medical information is remembered by the end of a visit. Out of what is remembered, less than 50% is accurate. Furthermore, 47% of Americans have health literacy levels below the intermediate range, defined as the ability to determine when to take a medication with food from reading the label.
Lecturing the patient without first understanding what the patient knows and finds important, and understanding the barriers to plan implementation, runs the risk of decreased comprehension, a lack of understanding, or a lack of personal relevance—all leading to decreased adherence. Doing the opposite, by involving the patient in decision making, inspires change that comes from within in the context of the patient’s own needs. This approach is more enduring, emphasizes self-accountability, and ultimately leads to better outcomes.
How I Do It
I open up a dialogue using the Cleveland Clinic’s ARIA approach as adapted from the REDE model of healthcare communication.1
- First, assess: What does the patient know about diagnosis and treatment? How much and what type of education does the patient desire/need? What are the patient’s treatment preferences and health literacy?
- Second, reflect on what the patient just said. Validate meaning and emotion.
- Third, inform the patient within the context of the patient’s perspectives and preferences. Speak slowly and provide small chunks of information at a time. Use understandable language and visual aids. (This will increase recall by 60%.)
- Finally, assess the patient’s understanding and emotional reaction to information provided.
- Repeat the cycle to introduce other chunks of information.
Dr. Velez is director of faculty development in the Center for Excellence in Healthcare Communication at the Cleveland Clinic.
Reference
- Windover A, Boissy A, Rice T, Gilligan T, Velez V, Merlino J. The REDE model of healthcare communication: optimizing relationship as a therapeutic agent. J Patient Exp. 2014;1(1):8-13.
Editor’s note: “Everything We Say and Do” is an informational series developed by SHM’s Patient Experience Committee to provide readers with thoughtful and actionable communication tactics that have great potential to positively impact patients’ experience of care. Each column will focus on how the contributor applies one of the “Key Communication” areas in practice.
View a chart outlining key communication tactics
What I Say and Do
I counsel and deliver the diagnosis or give recommendations through a dialogue, instead of a monologue, using active listening.
Why I Do It
The monologue, or lecture, is among the least effective ways to instill behavior change. Research studies have demonstrated that, after a monologue, only around 20% to 60% of medical information is remembered by the end of a visit. Out of what is remembered, less than 50% is accurate. Furthermore, 47% of Americans have health literacy levels below the intermediate range, defined as the ability to determine when to take a medication with food from reading the label.
Lecturing the patient without first understanding what the patient knows and finds important, and understanding the barriers to plan implementation, runs the risk of decreased comprehension, a lack of understanding, or a lack of personal relevance—all leading to decreased adherence. Doing the opposite, by involving the patient in decision making, inspires change that comes from within in the context of the patient’s own needs. This approach is more enduring, emphasizes self-accountability, and ultimately leads to better outcomes.
How I Do It
I open up a dialogue using the Cleveland Clinic’s ARIA approach as adapted from the REDE model of healthcare communication.1
- First, assess: What does the patient know about diagnosis and treatment? How much and what type of education does the patient desire/need? What are the patient’s treatment preferences and health literacy?
- Second, reflect on what the patient just said. Validate meaning and emotion.
- Third, inform the patient within the context of the patient’s perspectives and preferences. Speak slowly and provide small chunks of information at a time. Use understandable language and visual aids. (This will increase recall by 60%.)
- Finally, assess the patient’s understanding and emotional reaction to information provided.
- Repeat the cycle to introduce other chunks of information.
Dr. Velez is director of faculty development in the Center for Excellence in Healthcare Communication at the Cleveland Clinic.
Reference
- Windover A, Boissy A, Rice T, Gilligan T, Velez V, Merlino J. The REDE model of healthcare communication: optimizing relationship as a therapeutic agent. J Patient Exp. 2014;1(1):8-13.