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Autoantibody against enteric nervous system protein linked to GI dysfunction in systemic sclerosis
(SSc), new research suggests. Researchers also found that gephyrin is expressed in the patient’s enteric nervous system (ENS), which regulates gut motility.
“While there are many antibodies that are helpful in identifying patients at risk for extraintestinal complications of this disease, markers that identify patients at higher risk for gastrointestinal complications are limited. Furthermore, the biological mechanisms that cause and perpetuate the progression of gastrointestinal disease in scleroderma are not well understood, making it challenging to distinguish between patients whose gastrointestinal disease will progress from those whose GI disease will remain stable/mild,” Zsuzsanna H. McMahan, MD, MHS, told this news organization in an email. Dr. McMahan is co–first author on the study along with Subhash Kulkarni, PhD. They conducted the research with colleagues when they both worked at Johns Hopkins University in Baltimore, Md.
When asked for comment, Kimberly Lakin, MD, MS, assistant professor of medicine at Weill Cornell Medicine and a rheumatologist at Hospital for Special Surgery, New York, called the study “interesting and novel.”
“Not only did [antigephyrin antibodies] correlate with the presence of lower GI symptoms, but also higher levels of antibodies correlated with worse lower GI symptoms. This suggests that not only could this antibody be used to predict who may have constipation and potentially need more aggressive GI interventions, but it may also be useful in quantifying GI severity in systemic sclerosis, although more research is still needed,” said Dr. Lakin, who was not involved with the research.
The study was published online in Arthritis & Rheumatology.
In the cross-sectional study, researchers identified gephyrin as an autoantigen in sera from a single patient with SSc by isolating it from immunoprecipitations performed with murine myenteric plexus neuron lysates, and then characterizing it by mass spectrometry and validating it in further assays. That patient had GI dysfunction but no defined SSc-associated autoantibodies.
Dr. McMahan and colleagues then investigated the prevalence of the autoantibody by screening the sera of 188 patients with SSc who presented consecutively to the Johns Hopkins Scleroderma Center between April 2016 and August 2017, as well as 40 controls, and compared GI symptom severity between antibody-positive and antibody-negative patients with SSc.
A total of 16 (8.5%) of the 188 patients with SSc had antigephyrin antibodies, compared with none of the controls. Of these 16 patients, 4 had no other defined SSc antibodies. In the SSc cohort, severe constipation was more common in antigephyrin antibody–positive patients, compared with antibody-negative patients (46% vs. 15%). Antibody-positive patients also had higher constipation scores, and severe distension and bloating occurred in the antibody-positive group more than twice as often (54% vs. 25%).
Patients with severe constipation, distention, and bloating had higher antigephyrin antibody levels. After adjusting for confounders such as disease duration, patients with severe constipation were nearly five times as likely (odds ratio, 4.74; P = .010) to be antigephyrin antibody–positive, and patients with severe distention and bloating were nearly four times as likely (OR, 3.71; P = .027) to be antibody-positive.
Last, the authors showed via immunohistochemistry that gephyrin is expressed in the myenteric ganglia of human GI tissue.
“Gastrointestinal function is highly regulated by the ENS, so it is interesting that antibodies that target a protein expressed by ENS cells (gephyrin) were identified in patients with scleroderma who have severe lower bowel dysfunction,” said Dr. McMahan, who is associate professor in the division of rheumatology and codirector of the scleroderma program at the University of Texas Health Science Center at Houston. “Gephyrin is a key mediator of normal communications between nerves in the gut, so it is tantalizing to speculate that autoimmune-mediated disruption (e.g., an inhibitory or blocking antibody) in neural (ENS) communications in the gut might lead to impaired bowel transit and prominent constipation.”
The study was supported by grants from the National Institute of Arthritis and Musculoskeletal and Skin Diseases and other NIH grants, as well as the Scleroderma Research Foundation, Rheumatology Research Foundation, Jerome L. Greene Foundation, Martha McCrory Professorship, and Chresanthe Stauraluakis Memorial Discovery Fund. The study authors and Dr. Lakin report no relevant financial relationships.
A version of this article first appeared on Medscape.com.
(SSc), new research suggests. Researchers also found that gephyrin is expressed in the patient’s enteric nervous system (ENS), which regulates gut motility.
“While there are many antibodies that are helpful in identifying patients at risk for extraintestinal complications of this disease, markers that identify patients at higher risk for gastrointestinal complications are limited. Furthermore, the biological mechanisms that cause and perpetuate the progression of gastrointestinal disease in scleroderma are not well understood, making it challenging to distinguish between patients whose gastrointestinal disease will progress from those whose GI disease will remain stable/mild,” Zsuzsanna H. McMahan, MD, MHS, told this news organization in an email. Dr. McMahan is co–first author on the study along with Subhash Kulkarni, PhD. They conducted the research with colleagues when they both worked at Johns Hopkins University in Baltimore, Md.
When asked for comment, Kimberly Lakin, MD, MS, assistant professor of medicine at Weill Cornell Medicine and a rheumatologist at Hospital for Special Surgery, New York, called the study “interesting and novel.”
“Not only did [antigephyrin antibodies] correlate with the presence of lower GI symptoms, but also higher levels of antibodies correlated with worse lower GI symptoms. This suggests that not only could this antibody be used to predict who may have constipation and potentially need more aggressive GI interventions, but it may also be useful in quantifying GI severity in systemic sclerosis, although more research is still needed,” said Dr. Lakin, who was not involved with the research.
The study was published online in Arthritis & Rheumatology.
In the cross-sectional study, researchers identified gephyrin as an autoantigen in sera from a single patient with SSc by isolating it from immunoprecipitations performed with murine myenteric plexus neuron lysates, and then characterizing it by mass spectrometry and validating it in further assays. That patient had GI dysfunction but no defined SSc-associated autoantibodies.
Dr. McMahan and colleagues then investigated the prevalence of the autoantibody by screening the sera of 188 patients with SSc who presented consecutively to the Johns Hopkins Scleroderma Center between April 2016 and August 2017, as well as 40 controls, and compared GI symptom severity between antibody-positive and antibody-negative patients with SSc.
A total of 16 (8.5%) of the 188 patients with SSc had antigephyrin antibodies, compared with none of the controls. Of these 16 patients, 4 had no other defined SSc antibodies. In the SSc cohort, severe constipation was more common in antigephyrin antibody–positive patients, compared with antibody-negative patients (46% vs. 15%). Antibody-positive patients also had higher constipation scores, and severe distension and bloating occurred in the antibody-positive group more than twice as often (54% vs. 25%).
Patients with severe constipation, distention, and bloating had higher antigephyrin antibody levels. After adjusting for confounders such as disease duration, patients with severe constipation were nearly five times as likely (odds ratio, 4.74; P = .010) to be antigephyrin antibody–positive, and patients with severe distention and bloating were nearly four times as likely (OR, 3.71; P = .027) to be antibody-positive.
Last, the authors showed via immunohistochemistry that gephyrin is expressed in the myenteric ganglia of human GI tissue.
“Gastrointestinal function is highly regulated by the ENS, so it is interesting that antibodies that target a protein expressed by ENS cells (gephyrin) were identified in patients with scleroderma who have severe lower bowel dysfunction,” said Dr. McMahan, who is associate professor in the division of rheumatology and codirector of the scleroderma program at the University of Texas Health Science Center at Houston. “Gephyrin is a key mediator of normal communications between nerves in the gut, so it is tantalizing to speculate that autoimmune-mediated disruption (e.g., an inhibitory or blocking antibody) in neural (ENS) communications in the gut might lead to impaired bowel transit and prominent constipation.”
The study was supported by grants from the National Institute of Arthritis and Musculoskeletal and Skin Diseases and other NIH grants, as well as the Scleroderma Research Foundation, Rheumatology Research Foundation, Jerome L. Greene Foundation, Martha McCrory Professorship, and Chresanthe Stauraluakis Memorial Discovery Fund. The study authors and Dr. Lakin report no relevant financial relationships.
A version of this article first appeared on Medscape.com.
(SSc), new research suggests. Researchers also found that gephyrin is expressed in the patient’s enteric nervous system (ENS), which regulates gut motility.
“While there are many antibodies that are helpful in identifying patients at risk for extraintestinal complications of this disease, markers that identify patients at higher risk for gastrointestinal complications are limited. Furthermore, the biological mechanisms that cause and perpetuate the progression of gastrointestinal disease in scleroderma are not well understood, making it challenging to distinguish between patients whose gastrointestinal disease will progress from those whose GI disease will remain stable/mild,” Zsuzsanna H. McMahan, MD, MHS, told this news organization in an email. Dr. McMahan is co–first author on the study along with Subhash Kulkarni, PhD. They conducted the research with colleagues when they both worked at Johns Hopkins University in Baltimore, Md.
When asked for comment, Kimberly Lakin, MD, MS, assistant professor of medicine at Weill Cornell Medicine and a rheumatologist at Hospital for Special Surgery, New York, called the study “interesting and novel.”
“Not only did [antigephyrin antibodies] correlate with the presence of lower GI symptoms, but also higher levels of antibodies correlated with worse lower GI symptoms. This suggests that not only could this antibody be used to predict who may have constipation and potentially need more aggressive GI interventions, but it may also be useful in quantifying GI severity in systemic sclerosis, although more research is still needed,” said Dr. Lakin, who was not involved with the research.
The study was published online in Arthritis & Rheumatology.
In the cross-sectional study, researchers identified gephyrin as an autoantigen in sera from a single patient with SSc by isolating it from immunoprecipitations performed with murine myenteric plexus neuron lysates, and then characterizing it by mass spectrometry and validating it in further assays. That patient had GI dysfunction but no defined SSc-associated autoantibodies.
Dr. McMahan and colleagues then investigated the prevalence of the autoantibody by screening the sera of 188 patients with SSc who presented consecutively to the Johns Hopkins Scleroderma Center between April 2016 and August 2017, as well as 40 controls, and compared GI symptom severity between antibody-positive and antibody-negative patients with SSc.
A total of 16 (8.5%) of the 188 patients with SSc had antigephyrin antibodies, compared with none of the controls. Of these 16 patients, 4 had no other defined SSc antibodies. In the SSc cohort, severe constipation was more common in antigephyrin antibody–positive patients, compared with antibody-negative patients (46% vs. 15%). Antibody-positive patients also had higher constipation scores, and severe distension and bloating occurred in the antibody-positive group more than twice as often (54% vs. 25%).
Patients with severe constipation, distention, and bloating had higher antigephyrin antibody levels. After adjusting for confounders such as disease duration, patients with severe constipation were nearly five times as likely (odds ratio, 4.74; P = .010) to be antigephyrin antibody–positive, and patients with severe distention and bloating were nearly four times as likely (OR, 3.71; P = .027) to be antibody-positive.
Last, the authors showed via immunohistochemistry that gephyrin is expressed in the myenteric ganglia of human GI tissue.
“Gastrointestinal function is highly regulated by the ENS, so it is interesting that antibodies that target a protein expressed by ENS cells (gephyrin) were identified in patients with scleroderma who have severe lower bowel dysfunction,” said Dr. McMahan, who is associate professor in the division of rheumatology and codirector of the scleroderma program at the University of Texas Health Science Center at Houston. “Gephyrin is a key mediator of normal communications between nerves in the gut, so it is tantalizing to speculate that autoimmune-mediated disruption (e.g., an inhibitory or blocking antibody) in neural (ENS) communications in the gut might lead to impaired bowel transit and prominent constipation.”
The study was supported by grants from the National Institute of Arthritis and Musculoskeletal and Skin Diseases and other NIH grants, as well as the Scleroderma Research Foundation, Rheumatology Research Foundation, Jerome L. Greene Foundation, Martha McCrory Professorship, and Chresanthe Stauraluakis Memorial Discovery Fund. The study authors and Dr. Lakin report no relevant financial relationships.
A version of this article first appeared on Medscape.com.
FROM ARTHRITIS & RHEUMATOLOGY
Classification of COPD exacerbation predicts prognosis
Adults with exacerbations of chronic obstructive pulmonary disease (ECOPD) whose condition was classified as severe using the Rome criteria had a higher risk of death at 1 year than those who were classified as having moderate or mild disease, as determined from data from more than 300 individuals.
Patients hospitalized with severe exacerbations of ECOPD are at increased risk for worse clinical outcomes and death, so early identification is important, Ernesto Crisafulli, MD, of the University of Verona (Italy) and Azienda Ospedaliera Universitaria Integrata of Verona, and colleagues wrote.
which grades ECOPD as mild, moderate, or severe on the basis of more objective and disease-related aspects. However, data on the clinical usefulness of the Rome criteria are limited.
In a study published in the journal Chest, the researchers retrospectively categorized 347 adults hospitalized with ECOPD using the Rome severity classifications of mild, moderate, and severe.
Classifications were made using baseline, clinical and microbiological factors, as well as gas analysis and laboratory variables. The researchers also reviewed data on the length of hospital stay and mortality (in-hospital and over a follow-up of 6 months to 3 years).
Approximately one-third of the patients (39%) were classified as having mild disease, 31% as having moderate disease, and 30% as having severe illness. Overall, hospital stay was significantly longer for the patients with severe disease, although in-hospital mortality was similar across all three groups.
Patients classified as having severe disease also had a worse prognosis at all follow-up time points, and severe classification was significantly associated with worse cumulative survival at 1 year and 3 years (Gehan-Breslow-Wilson test, P = .032 and P = .004, respectively).
In a multivariate analysis, the risk of death at 1 year was significantly higher among patients classified as severe or moderate (hazard ratio, 1.99 and 1.47, respectively), compared with those classified as mild.
Mortality risk also was higher among patients aged 80 years and older and among those requiring long-term oxygen therapy or with a history of ECOPD episodes, the researchers noted. Body mass index in the range of 25-29 kg/m2 was associated with lower risk.
The study was limited by several factors, including the replacement of dyspnea perception in the Rome classification with other objective measures, the researchers wrote. Other limitations include the retrospective design, small sample size, use of data from a single center, and lack of data on causes of mortality. Women were underrepresented in the study, and so additional research involving women is needed.
The results suggest that the Rome classification allows for the effective identification of patients with ECOPD who have a worse prognosis. The Rome classification may help guide disease management through targeted interventions and personalized care programs for this population, the researchers concluded.
The study received no outside funding. The researchers disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.
Adults with exacerbations of chronic obstructive pulmonary disease (ECOPD) whose condition was classified as severe using the Rome criteria had a higher risk of death at 1 year than those who were classified as having moderate or mild disease, as determined from data from more than 300 individuals.
Patients hospitalized with severe exacerbations of ECOPD are at increased risk for worse clinical outcomes and death, so early identification is important, Ernesto Crisafulli, MD, of the University of Verona (Italy) and Azienda Ospedaliera Universitaria Integrata of Verona, and colleagues wrote.
which grades ECOPD as mild, moderate, or severe on the basis of more objective and disease-related aspects. However, data on the clinical usefulness of the Rome criteria are limited.
In a study published in the journal Chest, the researchers retrospectively categorized 347 adults hospitalized with ECOPD using the Rome severity classifications of mild, moderate, and severe.
Classifications were made using baseline, clinical and microbiological factors, as well as gas analysis and laboratory variables. The researchers also reviewed data on the length of hospital stay and mortality (in-hospital and over a follow-up of 6 months to 3 years).
Approximately one-third of the patients (39%) were classified as having mild disease, 31% as having moderate disease, and 30% as having severe illness. Overall, hospital stay was significantly longer for the patients with severe disease, although in-hospital mortality was similar across all three groups.
Patients classified as having severe disease also had a worse prognosis at all follow-up time points, and severe classification was significantly associated with worse cumulative survival at 1 year and 3 years (Gehan-Breslow-Wilson test, P = .032 and P = .004, respectively).
In a multivariate analysis, the risk of death at 1 year was significantly higher among patients classified as severe or moderate (hazard ratio, 1.99 and 1.47, respectively), compared with those classified as mild.
Mortality risk also was higher among patients aged 80 years and older and among those requiring long-term oxygen therapy or with a history of ECOPD episodes, the researchers noted. Body mass index in the range of 25-29 kg/m2 was associated with lower risk.
The study was limited by several factors, including the replacement of dyspnea perception in the Rome classification with other objective measures, the researchers wrote. Other limitations include the retrospective design, small sample size, use of data from a single center, and lack of data on causes of mortality. Women were underrepresented in the study, and so additional research involving women is needed.
The results suggest that the Rome classification allows for the effective identification of patients with ECOPD who have a worse prognosis. The Rome classification may help guide disease management through targeted interventions and personalized care programs for this population, the researchers concluded.
The study received no outside funding. The researchers disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.
Adults with exacerbations of chronic obstructive pulmonary disease (ECOPD) whose condition was classified as severe using the Rome criteria had a higher risk of death at 1 year than those who were classified as having moderate or mild disease, as determined from data from more than 300 individuals.
Patients hospitalized with severe exacerbations of ECOPD are at increased risk for worse clinical outcomes and death, so early identification is important, Ernesto Crisafulli, MD, of the University of Verona (Italy) and Azienda Ospedaliera Universitaria Integrata of Verona, and colleagues wrote.
which grades ECOPD as mild, moderate, or severe on the basis of more objective and disease-related aspects. However, data on the clinical usefulness of the Rome criteria are limited.
In a study published in the journal Chest, the researchers retrospectively categorized 347 adults hospitalized with ECOPD using the Rome severity classifications of mild, moderate, and severe.
Classifications were made using baseline, clinical and microbiological factors, as well as gas analysis and laboratory variables. The researchers also reviewed data on the length of hospital stay and mortality (in-hospital and over a follow-up of 6 months to 3 years).
Approximately one-third of the patients (39%) were classified as having mild disease, 31% as having moderate disease, and 30% as having severe illness. Overall, hospital stay was significantly longer for the patients with severe disease, although in-hospital mortality was similar across all three groups.
Patients classified as having severe disease also had a worse prognosis at all follow-up time points, and severe classification was significantly associated with worse cumulative survival at 1 year and 3 years (Gehan-Breslow-Wilson test, P = .032 and P = .004, respectively).
In a multivariate analysis, the risk of death at 1 year was significantly higher among patients classified as severe or moderate (hazard ratio, 1.99 and 1.47, respectively), compared with those classified as mild.
Mortality risk also was higher among patients aged 80 years and older and among those requiring long-term oxygen therapy or with a history of ECOPD episodes, the researchers noted. Body mass index in the range of 25-29 kg/m2 was associated with lower risk.
The study was limited by several factors, including the replacement of dyspnea perception in the Rome classification with other objective measures, the researchers wrote. Other limitations include the retrospective design, small sample size, use of data from a single center, and lack of data on causes of mortality. Women were underrepresented in the study, and so additional research involving women is needed.
The results suggest that the Rome classification allows for the effective identification of patients with ECOPD who have a worse prognosis. The Rome classification may help guide disease management through targeted interventions and personalized care programs for this population, the researchers concluded.
The study received no outside funding. The researchers disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.
FROM THE JOURNAL CHEST
Drug name confusion: More than 80 new drug pairs added to the list
Zolpidem (Ambien) is a well-known sedative for sleep. Letairis (Ambrisentan) is a vasodilator for the treatment of pulmonary arterial hypertension. Citalopram (Celexa) is an antidepressant; escitalopram (Lexapro) is prescribed for anxiety and depression.
The aim is to increase awareness about the potential for a serious medication mistake when the wrong drug is given because of drug names that look and sound similar.
Awareness of these drug names, however, is just the first step in preventing medication mistakes. Health care providers should take a number of other steps as well, experts said.
ISMP launched its confusing drug names list, previously called look-alike, sound-alike (LASA) drugs, in 2008. The new list is an update of the 2019 version, said Michael J. Gaunt, PharmD, senior manager of error reporting programs for the ISMP, which focuses on the prevention of medication mistakes. The new entries were chosen on the basis of a number of factors, including ISMP’s analysis of recent medication mishap reports that were submitted to it.
The ISMP list now includes about 528 drug pairs, Dr. Gaunt said. The list is long, he said, partly because each pair is listed twice, so readers can cross reference. For instance, hydralazine and hydroxyzine are listed in one entry in the list, and hydroxyzine and hydralazine are listed in another.
Brand Institute in Miami has named, among other drugs, Entresto, Rybelsus, and Lunesta. The regulatory arm of the company, the Drug Safety Institute, “considers drug names that have been confused as an important part of our comprehensive drug name assessments,” Todd Bridges, global president of the institute, said in an emailed statement. Information on the confusing drug names are incorporated into the company’s proprietary algorithm and is used when developing brand names for drugs. “We continually update this algorithm as new drug names that are often confused are identified,” Mr. Bridges said.
Confusing drug names: Ongoing issue
The length of the list, as well as the latest additions, are not surprising, said Mary Ann Kliethermes, PharmD, director of medication safety and quality for the American Society of Health-System Pharmacists, a membership organization of about 60,000 pharmacists who practice in inpatient and outpatient settings.
“I’ve been in practice over 45 years,” she said, “and this has been a problem ever since I have been in practice.” The sheer volume of new drugs is one reason, she said. From 2013 through 2022, the U.S. Food and Drug Administration approved an average of 43 novel drugs per year, according to a report from its Center for Drug Evaluation and Research. “Since the 90s, this [confusion about similar drug names] has happened,” Dr. Kliethermes said.
According to a 2023 report, about 7,000-9,000 people die each year in the United States as the result of a medication error. However, it’s impossible to say for sure what percentage of those errors involve name confusion, Dr. Gaunt said.
Not all the mistakes are reported. Some that are reported are dramatic and deadly. In 2022, a Tennessee nurse was convicted of gross neglect and negligent homicide. She was sentenced to 3 years’ probation after she mistakenly gave vercuronium, an anesthetic agent, instead of the sedative Versed to a patient, and the woman died.
Updated list: A closer look
Many of the new drug pairs that are listed in the update are cephalosporins, said Dr. Kliethermes, who reviewed the new list for this news organization. In all, 20 of the latest 82 additions are cephalosporins. These include drugs such as cefazolin, which can be confused with cefotetan, and vice versa. These drugs have been around since the 1980s, she said, but “they needed to be on there.” Even in the 1980s, it was becoming difficult to differentiate them, and there were fewer drugs in that class then, she said.
Influenza vaccines made the new list, too. Fluzone High-Dose Quadrivalent can be confused with fluzone quadrivalent. Other new additions: hydrochlorothiazide and hydroxychloroquine, Lasik and Wakix, Pitressin and Pitocin, Remeron and Rozerem.
Beyond the list
While it’s not possible to pinpoint how big a problem name confusion is in causing medication mistakes, “it is certainly still an issue,” Dr. Gaunt said. A variety of practices can reduce that risk substantially, Dr. Gaunt and Dr. Kliethermes agreed.
Tall-man lettering. Both the FDA and the ISMP recommend the use of so-called tall-man lettering (TML), which involves the use of uppercase letters, sometimes in boldface, to distinguish similar names on product labels and elsewhere. Examples include vinBLAStine and vinCRIStine.
Electronic prescribing. “It eliminates the risk of handwriting confusion,” Dr. Gaunt said. However, electronic prescribing can have a downside, Dr. Kliethermes said. When ordering medication, a person may type in a few letters and may then be presented with a prompt that lists several drug names, and it can be easy to click the wrong one. For that reason, ISMP and other experts recommend typing at least five letters when searching for a medication in an electronic system.
Use both brand and generic names on labels and prescriptions.
Write the indication. That can serve as a double check. If a prescription for Ambien says “For sleep,” there’s probably less risk of filling a prescription for ambrisentan, the vasodilator.
Smart formulary additions. When hospitals add medications to their formularies, “part of that formulary assessment should include looking at the potential risk for errors,” Dr. Gaunt said. This involves keeping an eye out for confusing names and similar packaging. “Do that analysis up front and put in strategies to minimize that. Maybe you look for a different drug [for the same use] that has a different name.” Or choose a different manufacturer, so the medication would at least have a different container.
Use bar code scanning. Suppose a pharmacist goes to the shelf and pulls the wrong drug. “Bar code scanning provides the opportunity to catch the error,” Dr. Gaunt said. Many community pharmacies now have bar code scanning. ISMP just issued best practices for community pharmacies, Dr. Gaunt said, and these include the use of bar code scanning and other measures.
Educate consumers. Health care providers can educate consumers on how to minimize the risk of getting the wrong drug, Dr. Gaunt said. When patients are picking up a prescription, suggest they look at the container label; if it looks different from previous prescriptions of the same medicine, ask the pharmacist for an explanation. Some patients just pass it off, Dr. Gaunt said, figuring the pharmacist or health plan switched manufacturers of their medication.
Access the list. The entire list is on the ISMP site and is accessible after free registration.
Goal: Preventing confusion
The FDA has provided guidance for industry on naming drugs not yet approved so that the proposed names are not too similar in sound or appearance to those already on the market. Included in the lengthy document are checklists, such as, “Across a range of dialects, are the names consistently pronounced differently?” and “Are the lengths of the names dissimilar when scripted?” (Lengths are considered different if they differ by two or more letters.)
The FDA also offers the phonetic and orthographic computer analysis (POCA) program, a software tool that employs an advanced algorithm to evaluate similarities between two drug names. The data sources are updated regularly as new drugs are approved.
Liability update
The problem may be decreasing. In a 2020 report, researchers used pharmacists’ professional liability claim data from the Healthcare Providers Service Organization. They compared 2018 data on claims with 2013 data. The percentage of claims associated with wrong drug dispensing errors declined from 43.8% in 2013 to 36.8% in 2018. Wrong dose claims also declined, from 31.5% to 15.3%.
These researchers concluded that technology and automation have contributed to the prevention of medication errors caused by the use of the wrong drug and the wrong dose, but mistakes continue, owing to system and human errors.
A version of this article first appeared on Medscape.com.
Zolpidem (Ambien) is a well-known sedative for sleep. Letairis (Ambrisentan) is a vasodilator for the treatment of pulmonary arterial hypertension. Citalopram (Celexa) is an antidepressant; escitalopram (Lexapro) is prescribed for anxiety and depression.
The aim is to increase awareness about the potential for a serious medication mistake when the wrong drug is given because of drug names that look and sound similar.
Awareness of these drug names, however, is just the first step in preventing medication mistakes. Health care providers should take a number of other steps as well, experts said.
ISMP launched its confusing drug names list, previously called look-alike, sound-alike (LASA) drugs, in 2008. The new list is an update of the 2019 version, said Michael J. Gaunt, PharmD, senior manager of error reporting programs for the ISMP, which focuses on the prevention of medication mistakes. The new entries were chosen on the basis of a number of factors, including ISMP’s analysis of recent medication mishap reports that were submitted to it.
The ISMP list now includes about 528 drug pairs, Dr. Gaunt said. The list is long, he said, partly because each pair is listed twice, so readers can cross reference. For instance, hydralazine and hydroxyzine are listed in one entry in the list, and hydroxyzine and hydralazine are listed in another.
Brand Institute in Miami has named, among other drugs, Entresto, Rybelsus, and Lunesta. The regulatory arm of the company, the Drug Safety Institute, “considers drug names that have been confused as an important part of our comprehensive drug name assessments,” Todd Bridges, global president of the institute, said in an emailed statement. Information on the confusing drug names are incorporated into the company’s proprietary algorithm and is used when developing brand names for drugs. “We continually update this algorithm as new drug names that are often confused are identified,” Mr. Bridges said.
Confusing drug names: Ongoing issue
The length of the list, as well as the latest additions, are not surprising, said Mary Ann Kliethermes, PharmD, director of medication safety and quality for the American Society of Health-System Pharmacists, a membership organization of about 60,000 pharmacists who practice in inpatient and outpatient settings.
“I’ve been in practice over 45 years,” she said, “and this has been a problem ever since I have been in practice.” The sheer volume of new drugs is one reason, she said. From 2013 through 2022, the U.S. Food and Drug Administration approved an average of 43 novel drugs per year, according to a report from its Center for Drug Evaluation and Research. “Since the 90s, this [confusion about similar drug names] has happened,” Dr. Kliethermes said.
According to a 2023 report, about 7,000-9,000 people die each year in the United States as the result of a medication error. However, it’s impossible to say for sure what percentage of those errors involve name confusion, Dr. Gaunt said.
Not all the mistakes are reported. Some that are reported are dramatic and deadly. In 2022, a Tennessee nurse was convicted of gross neglect and negligent homicide. She was sentenced to 3 years’ probation after she mistakenly gave vercuronium, an anesthetic agent, instead of the sedative Versed to a patient, and the woman died.
Updated list: A closer look
Many of the new drug pairs that are listed in the update are cephalosporins, said Dr. Kliethermes, who reviewed the new list for this news organization. In all, 20 of the latest 82 additions are cephalosporins. These include drugs such as cefazolin, which can be confused with cefotetan, and vice versa. These drugs have been around since the 1980s, she said, but “they needed to be on there.” Even in the 1980s, it was becoming difficult to differentiate them, and there were fewer drugs in that class then, she said.
Influenza vaccines made the new list, too. Fluzone High-Dose Quadrivalent can be confused with fluzone quadrivalent. Other new additions: hydrochlorothiazide and hydroxychloroquine, Lasik and Wakix, Pitressin and Pitocin, Remeron and Rozerem.
Beyond the list
While it’s not possible to pinpoint how big a problem name confusion is in causing medication mistakes, “it is certainly still an issue,” Dr. Gaunt said. A variety of practices can reduce that risk substantially, Dr. Gaunt and Dr. Kliethermes agreed.
Tall-man lettering. Both the FDA and the ISMP recommend the use of so-called tall-man lettering (TML), which involves the use of uppercase letters, sometimes in boldface, to distinguish similar names on product labels and elsewhere. Examples include vinBLAStine and vinCRIStine.
Electronic prescribing. “It eliminates the risk of handwriting confusion,” Dr. Gaunt said. However, electronic prescribing can have a downside, Dr. Kliethermes said. When ordering medication, a person may type in a few letters and may then be presented with a prompt that lists several drug names, and it can be easy to click the wrong one. For that reason, ISMP and other experts recommend typing at least five letters when searching for a medication in an electronic system.
Use both brand and generic names on labels and prescriptions.
Write the indication. That can serve as a double check. If a prescription for Ambien says “For sleep,” there’s probably less risk of filling a prescription for ambrisentan, the vasodilator.
Smart formulary additions. When hospitals add medications to their formularies, “part of that formulary assessment should include looking at the potential risk for errors,” Dr. Gaunt said. This involves keeping an eye out for confusing names and similar packaging. “Do that analysis up front and put in strategies to minimize that. Maybe you look for a different drug [for the same use] that has a different name.” Or choose a different manufacturer, so the medication would at least have a different container.
Use bar code scanning. Suppose a pharmacist goes to the shelf and pulls the wrong drug. “Bar code scanning provides the opportunity to catch the error,” Dr. Gaunt said. Many community pharmacies now have bar code scanning. ISMP just issued best practices for community pharmacies, Dr. Gaunt said, and these include the use of bar code scanning and other measures.
Educate consumers. Health care providers can educate consumers on how to minimize the risk of getting the wrong drug, Dr. Gaunt said. When patients are picking up a prescription, suggest they look at the container label; if it looks different from previous prescriptions of the same medicine, ask the pharmacist for an explanation. Some patients just pass it off, Dr. Gaunt said, figuring the pharmacist or health plan switched manufacturers of their medication.
Access the list. The entire list is on the ISMP site and is accessible after free registration.
Goal: Preventing confusion
The FDA has provided guidance for industry on naming drugs not yet approved so that the proposed names are not too similar in sound or appearance to those already on the market. Included in the lengthy document are checklists, such as, “Across a range of dialects, are the names consistently pronounced differently?” and “Are the lengths of the names dissimilar when scripted?” (Lengths are considered different if they differ by two or more letters.)
The FDA also offers the phonetic and orthographic computer analysis (POCA) program, a software tool that employs an advanced algorithm to evaluate similarities between two drug names. The data sources are updated regularly as new drugs are approved.
Liability update
The problem may be decreasing. In a 2020 report, researchers used pharmacists’ professional liability claim data from the Healthcare Providers Service Organization. They compared 2018 data on claims with 2013 data. The percentage of claims associated with wrong drug dispensing errors declined from 43.8% in 2013 to 36.8% in 2018. Wrong dose claims also declined, from 31.5% to 15.3%.
These researchers concluded that technology and automation have contributed to the prevention of medication errors caused by the use of the wrong drug and the wrong dose, but mistakes continue, owing to system and human errors.
A version of this article first appeared on Medscape.com.
Zolpidem (Ambien) is a well-known sedative for sleep. Letairis (Ambrisentan) is a vasodilator for the treatment of pulmonary arterial hypertension. Citalopram (Celexa) is an antidepressant; escitalopram (Lexapro) is prescribed for anxiety and depression.
The aim is to increase awareness about the potential for a serious medication mistake when the wrong drug is given because of drug names that look and sound similar.
Awareness of these drug names, however, is just the first step in preventing medication mistakes. Health care providers should take a number of other steps as well, experts said.
ISMP launched its confusing drug names list, previously called look-alike, sound-alike (LASA) drugs, in 2008. The new list is an update of the 2019 version, said Michael J. Gaunt, PharmD, senior manager of error reporting programs for the ISMP, which focuses on the prevention of medication mistakes. The new entries were chosen on the basis of a number of factors, including ISMP’s analysis of recent medication mishap reports that were submitted to it.
The ISMP list now includes about 528 drug pairs, Dr. Gaunt said. The list is long, he said, partly because each pair is listed twice, so readers can cross reference. For instance, hydralazine and hydroxyzine are listed in one entry in the list, and hydroxyzine and hydralazine are listed in another.
Brand Institute in Miami has named, among other drugs, Entresto, Rybelsus, and Lunesta. The regulatory arm of the company, the Drug Safety Institute, “considers drug names that have been confused as an important part of our comprehensive drug name assessments,” Todd Bridges, global president of the institute, said in an emailed statement. Information on the confusing drug names are incorporated into the company’s proprietary algorithm and is used when developing brand names for drugs. “We continually update this algorithm as new drug names that are often confused are identified,” Mr. Bridges said.
Confusing drug names: Ongoing issue
The length of the list, as well as the latest additions, are not surprising, said Mary Ann Kliethermes, PharmD, director of medication safety and quality for the American Society of Health-System Pharmacists, a membership organization of about 60,000 pharmacists who practice in inpatient and outpatient settings.
“I’ve been in practice over 45 years,” she said, “and this has been a problem ever since I have been in practice.” The sheer volume of new drugs is one reason, she said. From 2013 through 2022, the U.S. Food and Drug Administration approved an average of 43 novel drugs per year, according to a report from its Center for Drug Evaluation and Research. “Since the 90s, this [confusion about similar drug names] has happened,” Dr. Kliethermes said.
According to a 2023 report, about 7,000-9,000 people die each year in the United States as the result of a medication error. However, it’s impossible to say for sure what percentage of those errors involve name confusion, Dr. Gaunt said.
Not all the mistakes are reported. Some that are reported are dramatic and deadly. In 2022, a Tennessee nurse was convicted of gross neglect and negligent homicide. She was sentenced to 3 years’ probation after she mistakenly gave vercuronium, an anesthetic agent, instead of the sedative Versed to a patient, and the woman died.
Updated list: A closer look
Many of the new drug pairs that are listed in the update are cephalosporins, said Dr. Kliethermes, who reviewed the new list for this news organization. In all, 20 of the latest 82 additions are cephalosporins. These include drugs such as cefazolin, which can be confused with cefotetan, and vice versa. These drugs have been around since the 1980s, she said, but “they needed to be on there.” Even in the 1980s, it was becoming difficult to differentiate them, and there were fewer drugs in that class then, she said.
Influenza vaccines made the new list, too. Fluzone High-Dose Quadrivalent can be confused with fluzone quadrivalent. Other new additions: hydrochlorothiazide and hydroxychloroquine, Lasik and Wakix, Pitressin and Pitocin, Remeron and Rozerem.
Beyond the list
While it’s not possible to pinpoint how big a problem name confusion is in causing medication mistakes, “it is certainly still an issue,” Dr. Gaunt said. A variety of practices can reduce that risk substantially, Dr. Gaunt and Dr. Kliethermes agreed.
Tall-man lettering. Both the FDA and the ISMP recommend the use of so-called tall-man lettering (TML), which involves the use of uppercase letters, sometimes in boldface, to distinguish similar names on product labels and elsewhere. Examples include vinBLAStine and vinCRIStine.
Electronic prescribing. “It eliminates the risk of handwriting confusion,” Dr. Gaunt said. However, electronic prescribing can have a downside, Dr. Kliethermes said. When ordering medication, a person may type in a few letters and may then be presented with a prompt that lists several drug names, and it can be easy to click the wrong one. For that reason, ISMP and other experts recommend typing at least five letters when searching for a medication in an electronic system.
Use both brand and generic names on labels and prescriptions.
Write the indication. That can serve as a double check. If a prescription for Ambien says “For sleep,” there’s probably less risk of filling a prescription for ambrisentan, the vasodilator.
Smart formulary additions. When hospitals add medications to their formularies, “part of that formulary assessment should include looking at the potential risk for errors,” Dr. Gaunt said. This involves keeping an eye out for confusing names and similar packaging. “Do that analysis up front and put in strategies to minimize that. Maybe you look for a different drug [for the same use] that has a different name.” Or choose a different manufacturer, so the medication would at least have a different container.
Use bar code scanning. Suppose a pharmacist goes to the shelf and pulls the wrong drug. “Bar code scanning provides the opportunity to catch the error,” Dr. Gaunt said. Many community pharmacies now have bar code scanning. ISMP just issued best practices for community pharmacies, Dr. Gaunt said, and these include the use of bar code scanning and other measures.
Educate consumers. Health care providers can educate consumers on how to minimize the risk of getting the wrong drug, Dr. Gaunt said. When patients are picking up a prescription, suggest they look at the container label; if it looks different from previous prescriptions of the same medicine, ask the pharmacist for an explanation. Some patients just pass it off, Dr. Gaunt said, figuring the pharmacist or health plan switched manufacturers of their medication.
Access the list. The entire list is on the ISMP site and is accessible after free registration.
Goal: Preventing confusion
The FDA has provided guidance for industry on naming drugs not yet approved so that the proposed names are not too similar in sound or appearance to those already on the market. Included in the lengthy document are checklists, such as, “Across a range of dialects, are the names consistently pronounced differently?” and “Are the lengths of the names dissimilar when scripted?” (Lengths are considered different if they differ by two or more letters.)
The FDA also offers the phonetic and orthographic computer analysis (POCA) program, a software tool that employs an advanced algorithm to evaluate similarities between two drug names. The data sources are updated regularly as new drugs are approved.
Liability update
The problem may be decreasing. In a 2020 report, researchers used pharmacists’ professional liability claim data from the Healthcare Providers Service Organization. They compared 2018 data on claims with 2013 data. The percentage of claims associated with wrong drug dispensing errors declined from 43.8% in 2013 to 36.8% in 2018. Wrong dose claims also declined, from 31.5% to 15.3%.
These researchers concluded that technology and automation have contributed to the prevention of medication errors caused by the use of the wrong drug and the wrong dose, but mistakes continue, owing to system and human errors.
A version of this article first appeared on Medscape.com.
One size doesn’t fit all in blood pressure measurement
As with porridge, so with blood pressure: Just right makes all the difference.
according to research published in JAMA Internal Medicine.
People whose mid-upper arm circumference exceeds 32 cm require larger cuffs than the standard size, but in many cases the regular-sized cuff is used on everyone. As a result, patients with larger arms may be falsely diagnosed with high blood pressure because of a too-small cuff, leading to overprescribing of medications that could make their health worse, according to the researchers.
“A person whose blood pressure is 120/80, which is normal – if they’re using the wrong cuff, they could get a measurement that says 140/90, let’s say,” said study author Tammy M. Brady, MD, PhD, vice chair for clinical research in the department of pediatrics at Johns Hopkins University, Baltimore. “They might think they not only have hypertension, but stage 2 hypertension. Providers might give one or even two medicines to lower this, which could lead to hypotension,” Dr. Brady said.
Conversely, someone with smaller arms whose cuff is too big may present with an artificially low blood pressure. The implications of using ill-fitting cuffs are well known. Dr. Brady, among others, has studied the topic extensively. Even so, she said the measurement errors in the latest study were larger than expected.
The Goldilocks test
People with an arm circumference of 20-25 cm should use a smaller cuff than the regular size, Dr. Brady and colleagues reported. Circumferences of 25.1-32 cm require a regular-sized cuff; large cuffs are for circumferences of 32.1-40 cm; and extra-large cuffs should be used at 40.1-55 cm.
The study included 195 residents of Baltimore (128 women, 67 men; 132 Black, 58 White, 5 Hispanic) with an average age of 54 years. The researchers measured every participant’s blood pressure using an automated device on four occasions, taking three measurements each time.
The first three sets of measurements used, respectively, an appropriate cuff size for each person’s arm circumference; a cuff that was too big; and a cuff that was too small. This study design ensured that a regular-sized cuff would be used during one of the three measurements – sometimes that cuff was too small, sometimes it was appropriate, and other times it was too big.
The final set of three measurements used the appropriate cuff size for a person’s arm every time. Dr. Brady and colleagues then compared people’s blood pressure measurements when using the right-sized cuff to measurements with a regular-sized cuff that was not suited for them.
They found that using a cuff that was too large for the patient’s arm (i.e., using a regular cuff when a small cuff was the right choice) led to understating systolic blood pressure by –3.6 mm Hg (95% confidence interval [CI], –5.6 to –1.7). A cuff that was one size too small – using regular instead of a large – overestimated systolic blood pressure by 4.8 (3.0-6.6) mm Hg. And a cuff that was two sizes too small – someone who should have received an extra-large cuff but received the regular size – overestimated systolic blood pressure by 19.5 (16.1-22.9) mm Hg. All differences were statistically significant, the researchers reported.
“To our knowledge, this is the first randomized cross-over trial to examine the effect of miscuffing on automated blood pressure readings,” Mathias Lalika, MD, MPH, of the Mayo Clinic in Rochester, Minn.; Stephen P. Juraschek, MD, PhD, of Beth Israel Deaconess Medical Center in Boston; and LaPrincess C. Brewer, MD, MPH, of the Mayo Clinic, wrote in an editorial accompanying the journal article.
“Interestingly, the degree of underestimation or overestimation increased as the appropriate cuff size progressed from the regular to extra-large BP cuff. More importantly, the effect of miscuffing did not vary with BP or obesity status,” they wrote.
“This was more of a pragmatic trial to see real world, all comers,” Dr. Brady said, when regular-sized cuffs are used whether or not that made sense.
“This study reaffirms findings of previous studies and highlights a major source of error in blood pressure measurement,” Raj Padwal, MD, director of the University of Alberta Hypertension Clinic, Edmonton, Alta., said in an interview. Dr. Padwal, who was not involved in the study, said the findings highlight the importance of ensuring that technicians who typically measure blood pressure understand the value of using the right-sized cuff.
Dr. Brady noted that measuring arm circumference takes about 15 seconds. He advised health organizations and clinics to carry multiple cuffs sizes to avoid a scramble to find a right-sized cuff. In the editorial, Dr. Lalika, Dr. Juraschek, and Dr. Brewer call for particular attention to providing the right-sized cuffs to facilities that work with underserved populations, such as federally qualified health centers.
Dr. Padwal added that even a perfectly measured blood pressure test at a clinic indicates pressure at a moment in time. Ten minutes later the story could be different. For this reason, he and other clinicians recommend frequent home blood pressure measurements rather than relying solely on the sparse number of readings collected in the clinic setting.
“A properly educated patient can give many readings that are separated in space and time and, when averaged, can give a much better picture of overall blood pressure and future risk,” Dr. Padwal said.
Dr. Brady agreed with the value of home readings but said home-based readings also can be erroneous if the patient uses a cuff that is the wrong size. She cochairs a committee for the American Medical Association that recommends validated home blood pressure measurement devices on a periodically updated website called Validate BP. The details for each device listing show the cuff sizes available per device. Many devices provide only the standard cuff, Dr. Brady noted, but some offer multiple cuff sizes.
“One of the things that would be great if it came out of this paper is if patients were empowered to ask physicians to measure their arm” and then use that information to select the appropriate cuff for their home device, she said.
Dr. Brady and Dr. Padwal reported no relevant financial relationships. This study was supported by Resolve to Save Lives, which is funded by Bloomberg Philanthropies, the Bill & Melinda Gates Foundation, and Gates Philanthropy Partners, which is funded with support from the Chan Zuckerberg Foundation.
A version of this article appeared on Medscape.com.
As with porridge, so with blood pressure: Just right makes all the difference.
according to research published in JAMA Internal Medicine.
People whose mid-upper arm circumference exceeds 32 cm require larger cuffs than the standard size, but in many cases the regular-sized cuff is used on everyone. As a result, patients with larger arms may be falsely diagnosed with high blood pressure because of a too-small cuff, leading to overprescribing of medications that could make their health worse, according to the researchers.
“A person whose blood pressure is 120/80, which is normal – if they’re using the wrong cuff, they could get a measurement that says 140/90, let’s say,” said study author Tammy M. Brady, MD, PhD, vice chair for clinical research in the department of pediatrics at Johns Hopkins University, Baltimore. “They might think they not only have hypertension, but stage 2 hypertension. Providers might give one or even two medicines to lower this, which could lead to hypotension,” Dr. Brady said.
Conversely, someone with smaller arms whose cuff is too big may present with an artificially low blood pressure. The implications of using ill-fitting cuffs are well known. Dr. Brady, among others, has studied the topic extensively. Even so, she said the measurement errors in the latest study were larger than expected.
The Goldilocks test
People with an arm circumference of 20-25 cm should use a smaller cuff than the regular size, Dr. Brady and colleagues reported. Circumferences of 25.1-32 cm require a regular-sized cuff; large cuffs are for circumferences of 32.1-40 cm; and extra-large cuffs should be used at 40.1-55 cm.
The study included 195 residents of Baltimore (128 women, 67 men; 132 Black, 58 White, 5 Hispanic) with an average age of 54 years. The researchers measured every participant’s blood pressure using an automated device on four occasions, taking three measurements each time.
The first three sets of measurements used, respectively, an appropriate cuff size for each person’s arm circumference; a cuff that was too big; and a cuff that was too small. This study design ensured that a regular-sized cuff would be used during one of the three measurements – sometimes that cuff was too small, sometimes it was appropriate, and other times it was too big.
The final set of three measurements used the appropriate cuff size for a person’s arm every time. Dr. Brady and colleagues then compared people’s blood pressure measurements when using the right-sized cuff to measurements with a regular-sized cuff that was not suited for them.
They found that using a cuff that was too large for the patient’s arm (i.e., using a regular cuff when a small cuff was the right choice) led to understating systolic blood pressure by –3.6 mm Hg (95% confidence interval [CI], –5.6 to –1.7). A cuff that was one size too small – using regular instead of a large – overestimated systolic blood pressure by 4.8 (3.0-6.6) mm Hg. And a cuff that was two sizes too small – someone who should have received an extra-large cuff but received the regular size – overestimated systolic blood pressure by 19.5 (16.1-22.9) mm Hg. All differences were statistically significant, the researchers reported.
“To our knowledge, this is the first randomized cross-over trial to examine the effect of miscuffing on automated blood pressure readings,” Mathias Lalika, MD, MPH, of the Mayo Clinic in Rochester, Minn.; Stephen P. Juraschek, MD, PhD, of Beth Israel Deaconess Medical Center in Boston; and LaPrincess C. Brewer, MD, MPH, of the Mayo Clinic, wrote in an editorial accompanying the journal article.
“Interestingly, the degree of underestimation or overestimation increased as the appropriate cuff size progressed from the regular to extra-large BP cuff. More importantly, the effect of miscuffing did not vary with BP or obesity status,” they wrote.
“This was more of a pragmatic trial to see real world, all comers,” Dr. Brady said, when regular-sized cuffs are used whether or not that made sense.
“This study reaffirms findings of previous studies and highlights a major source of error in blood pressure measurement,” Raj Padwal, MD, director of the University of Alberta Hypertension Clinic, Edmonton, Alta., said in an interview. Dr. Padwal, who was not involved in the study, said the findings highlight the importance of ensuring that technicians who typically measure blood pressure understand the value of using the right-sized cuff.
Dr. Brady noted that measuring arm circumference takes about 15 seconds. He advised health organizations and clinics to carry multiple cuffs sizes to avoid a scramble to find a right-sized cuff. In the editorial, Dr. Lalika, Dr. Juraschek, and Dr. Brewer call for particular attention to providing the right-sized cuffs to facilities that work with underserved populations, such as federally qualified health centers.
Dr. Padwal added that even a perfectly measured blood pressure test at a clinic indicates pressure at a moment in time. Ten minutes later the story could be different. For this reason, he and other clinicians recommend frequent home blood pressure measurements rather than relying solely on the sparse number of readings collected in the clinic setting.
“A properly educated patient can give many readings that are separated in space and time and, when averaged, can give a much better picture of overall blood pressure and future risk,” Dr. Padwal said.
Dr. Brady agreed with the value of home readings but said home-based readings also can be erroneous if the patient uses a cuff that is the wrong size. She cochairs a committee for the American Medical Association that recommends validated home blood pressure measurement devices on a periodically updated website called Validate BP. The details for each device listing show the cuff sizes available per device. Many devices provide only the standard cuff, Dr. Brady noted, but some offer multiple cuff sizes.
“One of the things that would be great if it came out of this paper is if patients were empowered to ask physicians to measure their arm” and then use that information to select the appropriate cuff for their home device, she said.
Dr. Brady and Dr. Padwal reported no relevant financial relationships. This study was supported by Resolve to Save Lives, which is funded by Bloomberg Philanthropies, the Bill & Melinda Gates Foundation, and Gates Philanthropy Partners, which is funded with support from the Chan Zuckerberg Foundation.
A version of this article appeared on Medscape.com.
As with porridge, so with blood pressure: Just right makes all the difference.
according to research published in JAMA Internal Medicine.
People whose mid-upper arm circumference exceeds 32 cm require larger cuffs than the standard size, but in many cases the regular-sized cuff is used on everyone. As a result, patients with larger arms may be falsely diagnosed with high blood pressure because of a too-small cuff, leading to overprescribing of medications that could make their health worse, according to the researchers.
“A person whose blood pressure is 120/80, which is normal – if they’re using the wrong cuff, they could get a measurement that says 140/90, let’s say,” said study author Tammy M. Brady, MD, PhD, vice chair for clinical research in the department of pediatrics at Johns Hopkins University, Baltimore. “They might think they not only have hypertension, but stage 2 hypertension. Providers might give one or even two medicines to lower this, which could lead to hypotension,” Dr. Brady said.
Conversely, someone with smaller arms whose cuff is too big may present with an artificially low blood pressure. The implications of using ill-fitting cuffs are well known. Dr. Brady, among others, has studied the topic extensively. Even so, she said the measurement errors in the latest study were larger than expected.
The Goldilocks test
People with an arm circumference of 20-25 cm should use a smaller cuff than the regular size, Dr. Brady and colleagues reported. Circumferences of 25.1-32 cm require a regular-sized cuff; large cuffs are for circumferences of 32.1-40 cm; and extra-large cuffs should be used at 40.1-55 cm.
The study included 195 residents of Baltimore (128 women, 67 men; 132 Black, 58 White, 5 Hispanic) with an average age of 54 years. The researchers measured every participant’s blood pressure using an automated device on four occasions, taking three measurements each time.
The first three sets of measurements used, respectively, an appropriate cuff size for each person’s arm circumference; a cuff that was too big; and a cuff that was too small. This study design ensured that a regular-sized cuff would be used during one of the three measurements – sometimes that cuff was too small, sometimes it was appropriate, and other times it was too big.
The final set of three measurements used the appropriate cuff size for a person’s arm every time. Dr. Brady and colleagues then compared people’s blood pressure measurements when using the right-sized cuff to measurements with a regular-sized cuff that was not suited for them.
They found that using a cuff that was too large for the patient’s arm (i.e., using a regular cuff when a small cuff was the right choice) led to understating systolic blood pressure by –3.6 mm Hg (95% confidence interval [CI], –5.6 to –1.7). A cuff that was one size too small – using regular instead of a large – overestimated systolic blood pressure by 4.8 (3.0-6.6) mm Hg. And a cuff that was two sizes too small – someone who should have received an extra-large cuff but received the regular size – overestimated systolic blood pressure by 19.5 (16.1-22.9) mm Hg. All differences were statistically significant, the researchers reported.
“To our knowledge, this is the first randomized cross-over trial to examine the effect of miscuffing on automated blood pressure readings,” Mathias Lalika, MD, MPH, of the Mayo Clinic in Rochester, Minn.; Stephen P. Juraschek, MD, PhD, of Beth Israel Deaconess Medical Center in Boston; and LaPrincess C. Brewer, MD, MPH, of the Mayo Clinic, wrote in an editorial accompanying the journal article.
“Interestingly, the degree of underestimation or overestimation increased as the appropriate cuff size progressed from the regular to extra-large BP cuff. More importantly, the effect of miscuffing did not vary with BP or obesity status,” they wrote.
“This was more of a pragmatic trial to see real world, all comers,” Dr. Brady said, when regular-sized cuffs are used whether or not that made sense.
“This study reaffirms findings of previous studies and highlights a major source of error in blood pressure measurement,” Raj Padwal, MD, director of the University of Alberta Hypertension Clinic, Edmonton, Alta., said in an interview. Dr. Padwal, who was not involved in the study, said the findings highlight the importance of ensuring that technicians who typically measure blood pressure understand the value of using the right-sized cuff.
Dr. Brady noted that measuring arm circumference takes about 15 seconds. He advised health organizations and clinics to carry multiple cuffs sizes to avoid a scramble to find a right-sized cuff. In the editorial, Dr. Lalika, Dr. Juraschek, and Dr. Brewer call for particular attention to providing the right-sized cuffs to facilities that work with underserved populations, such as federally qualified health centers.
Dr. Padwal added that even a perfectly measured blood pressure test at a clinic indicates pressure at a moment in time. Ten minutes later the story could be different. For this reason, he and other clinicians recommend frequent home blood pressure measurements rather than relying solely on the sparse number of readings collected in the clinic setting.
“A properly educated patient can give many readings that are separated in space and time and, when averaged, can give a much better picture of overall blood pressure and future risk,” Dr. Padwal said.
Dr. Brady agreed with the value of home readings but said home-based readings also can be erroneous if the patient uses a cuff that is the wrong size. She cochairs a committee for the American Medical Association that recommends validated home blood pressure measurement devices on a periodically updated website called Validate BP. The details for each device listing show the cuff sizes available per device. Many devices provide only the standard cuff, Dr. Brady noted, but some offer multiple cuff sizes.
“One of the things that would be great if it came out of this paper is if patients were empowered to ask physicians to measure their arm” and then use that information to select the appropriate cuff for their home device, she said.
Dr. Brady and Dr. Padwal reported no relevant financial relationships. This study was supported by Resolve to Save Lives, which is funded by Bloomberg Philanthropies, the Bill & Melinda Gates Foundation, and Gates Philanthropy Partners, which is funded with support from the Chan Zuckerberg Foundation.
A version of this article appeared on Medscape.com.
FROM JAMA INTERNAL MEDICINE
The best CRC screening test is still this one
I’m Dr. Kenny Lin. I am a family physician and associate director of the Lancaster General Hospital Family Medicine Residency, and I blog at Common Sense Family Doctor.
I’m 47 years old. Two years ago, when the U.S. Preventive Services Task Force (USPSTF) followed the American Cancer Society and lowered the starting age for colorectal cancer (CRC) screening from 50 to 45, my family physician brought up screening options at a health maintenance visit. Although I had expressed some skepticism about this change when the ACS updated its screening guideline in 2018, I generally follow the USPSTF recommendations in my own clinical practice, so I dutifully selected a test that, fortunately, came out negative.
Not everyone in the primary care community, however, is on board with screening average-risk adults in their late 40s for colorectal cancer. The American Academy of Family Physicians (AAFP) published a notable dissent, arguing that the evidence from modeling studies cited by the USPSTF to support lowering the starting age was insufficient. The AAFP also expressed concern that devoting screening resources to younger adults could come at the expense of improving screening rates in older adults who are at higher risk for CRC and increase health care costs without corresponding benefit.
Now, the American College of Physicians has joined the AAFP by releasing an updated guidance statement for CRC screening that discourages screening asymptomatic, average-risk adults between the ages of 45 and 49. In addition to the uncertainty surrounding benefits of screening adults in this age range, the ACP pointed out that starting screening at age 45, compared with age 50, would increase the number of colonoscopies and colonoscopy complications. My colleagues and I recently published a systematic review estimating that for every 10,000 screening colonoscopies performed, 8 people suffer a bowel perforation and 16 to 36 have severe bleeding requiring hospitalization. One in 3 patients undergoing colonoscopies report minor adverse events such as abdominal pain, bloating, and abdominal discomfort in the first 2 weeks following the procedure.
Other aspects of the ACP guidance differ from other colorectal cancer screening guidelines. Unlike the USPSTF, which made no distinctions between various recommended screening tests, the ACP preferentially endorsed fecal immunochemical or high-sensitivity fecal occult blood testing every 2 years, colonoscopy every 10 years, or flexible sigmoidoscopy every 10 years plus a fecal immunochemical test every 2 years. That leaves out stool DNA testing, which my patients increasingly request because they have seen television or online advertisements, and newer blood tests that detect methylation sequences in circulating tumor DNA.
Perhaps most controversial is the ACP’s suggestion that it is probably reasonable for some adults to start screening later than age 50 or undergo screening at longer intervals than currently recommended (for example, colonoscopy every 15 years). Recent data support extending the interval to repeat screening colonoscopy in selected populations; a large cross-sectional study found a low prevalence of advanced adenomas and colorectal cancers in colonoscopies performed 10 or more years after an initial negative colonoscopy, particularly in women and younger patients without gastrointestinal symptoms. A prominent BMJ guideline suggests that patients need not be screened until their estimated 15-year CRC risk is greater than 3% (which most people do not reach until their 60s) and then only need a single sigmoidoscopy or colonoscopy.
Despite some departures from other guidelines, it’s worth emphasizing that the ACP guideline agrees that screening for CRC is generally worthwhile between the ages of 50 and 75 years. On that front, we in primary care have more work to do; the Centers for Disease Control and Prevention estimates that 28% of American adults older than 50 are not up-to-date on CRC screening. And despite some recent debate about the relative benefits and harms of screening colonoscopy, compared with less invasive fecal tests, gastroenterologists and family physicians can agree that the best screening test is the test that gets done.
A version of this article first appeared on Medscape.com.
I’m Dr. Kenny Lin. I am a family physician and associate director of the Lancaster General Hospital Family Medicine Residency, and I blog at Common Sense Family Doctor.
I’m 47 years old. Two years ago, when the U.S. Preventive Services Task Force (USPSTF) followed the American Cancer Society and lowered the starting age for colorectal cancer (CRC) screening from 50 to 45, my family physician brought up screening options at a health maintenance visit. Although I had expressed some skepticism about this change when the ACS updated its screening guideline in 2018, I generally follow the USPSTF recommendations in my own clinical practice, so I dutifully selected a test that, fortunately, came out negative.
Not everyone in the primary care community, however, is on board with screening average-risk adults in their late 40s for colorectal cancer. The American Academy of Family Physicians (AAFP) published a notable dissent, arguing that the evidence from modeling studies cited by the USPSTF to support lowering the starting age was insufficient. The AAFP also expressed concern that devoting screening resources to younger adults could come at the expense of improving screening rates in older adults who are at higher risk for CRC and increase health care costs without corresponding benefit.
Now, the American College of Physicians has joined the AAFP by releasing an updated guidance statement for CRC screening that discourages screening asymptomatic, average-risk adults between the ages of 45 and 49. In addition to the uncertainty surrounding benefits of screening adults in this age range, the ACP pointed out that starting screening at age 45, compared with age 50, would increase the number of colonoscopies and colonoscopy complications. My colleagues and I recently published a systematic review estimating that for every 10,000 screening colonoscopies performed, 8 people suffer a bowel perforation and 16 to 36 have severe bleeding requiring hospitalization. One in 3 patients undergoing colonoscopies report minor adverse events such as abdominal pain, bloating, and abdominal discomfort in the first 2 weeks following the procedure.
Other aspects of the ACP guidance differ from other colorectal cancer screening guidelines. Unlike the USPSTF, which made no distinctions between various recommended screening tests, the ACP preferentially endorsed fecal immunochemical or high-sensitivity fecal occult blood testing every 2 years, colonoscopy every 10 years, or flexible sigmoidoscopy every 10 years plus a fecal immunochemical test every 2 years. That leaves out stool DNA testing, which my patients increasingly request because they have seen television or online advertisements, and newer blood tests that detect methylation sequences in circulating tumor DNA.
Perhaps most controversial is the ACP’s suggestion that it is probably reasonable for some adults to start screening later than age 50 or undergo screening at longer intervals than currently recommended (for example, colonoscopy every 15 years). Recent data support extending the interval to repeat screening colonoscopy in selected populations; a large cross-sectional study found a low prevalence of advanced adenomas and colorectal cancers in colonoscopies performed 10 or more years after an initial negative colonoscopy, particularly in women and younger patients without gastrointestinal symptoms. A prominent BMJ guideline suggests that patients need not be screened until their estimated 15-year CRC risk is greater than 3% (which most people do not reach until their 60s) and then only need a single sigmoidoscopy or colonoscopy.
Despite some departures from other guidelines, it’s worth emphasizing that the ACP guideline agrees that screening for CRC is generally worthwhile between the ages of 50 and 75 years. On that front, we in primary care have more work to do; the Centers for Disease Control and Prevention estimates that 28% of American adults older than 50 are not up-to-date on CRC screening. And despite some recent debate about the relative benefits and harms of screening colonoscopy, compared with less invasive fecal tests, gastroenterologists and family physicians can agree that the best screening test is the test that gets done.
A version of this article first appeared on Medscape.com.
I’m Dr. Kenny Lin. I am a family physician and associate director of the Lancaster General Hospital Family Medicine Residency, and I blog at Common Sense Family Doctor.
I’m 47 years old. Two years ago, when the U.S. Preventive Services Task Force (USPSTF) followed the American Cancer Society and lowered the starting age for colorectal cancer (CRC) screening from 50 to 45, my family physician brought up screening options at a health maintenance visit. Although I had expressed some skepticism about this change when the ACS updated its screening guideline in 2018, I generally follow the USPSTF recommendations in my own clinical practice, so I dutifully selected a test that, fortunately, came out negative.
Not everyone in the primary care community, however, is on board with screening average-risk adults in their late 40s for colorectal cancer. The American Academy of Family Physicians (AAFP) published a notable dissent, arguing that the evidence from modeling studies cited by the USPSTF to support lowering the starting age was insufficient. The AAFP also expressed concern that devoting screening resources to younger adults could come at the expense of improving screening rates in older adults who are at higher risk for CRC and increase health care costs without corresponding benefit.
Now, the American College of Physicians has joined the AAFP by releasing an updated guidance statement for CRC screening that discourages screening asymptomatic, average-risk adults between the ages of 45 and 49. In addition to the uncertainty surrounding benefits of screening adults in this age range, the ACP pointed out that starting screening at age 45, compared with age 50, would increase the number of colonoscopies and colonoscopy complications. My colleagues and I recently published a systematic review estimating that for every 10,000 screening colonoscopies performed, 8 people suffer a bowel perforation and 16 to 36 have severe bleeding requiring hospitalization. One in 3 patients undergoing colonoscopies report minor adverse events such as abdominal pain, bloating, and abdominal discomfort in the first 2 weeks following the procedure.
Other aspects of the ACP guidance differ from other colorectal cancer screening guidelines. Unlike the USPSTF, which made no distinctions between various recommended screening tests, the ACP preferentially endorsed fecal immunochemical or high-sensitivity fecal occult blood testing every 2 years, colonoscopy every 10 years, or flexible sigmoidoscopy every 10 years plus a fecal immunochemical test every 2 years. That leaves out stool DNA testing, which my patients increasingly request because they have seen television or online advertisements, and newer blood tests that detect methylation sequences in circulating tumor DNA.
Perhaps most controversial is the ACP’s suggestion that it is probably reasonable for some adults to start screening later than age 50 or undergo screening at longer intervals than currently recommended (for example, colonoscopy every 15 years). Recent data support extending the interval to repeat screening colonoscopy in selected populations; a large cross-sectional study found a low prevalence of advanced adenomas and colorectal cancers in colonoscopies performed 10 or more years after an initial negative colonoscopy, particularly in women and younger patients without gastrointestinal symptoms. A prominent BMJ guideline suggests that patients need not be screened until their estimated 15-year CRC risk is greater than 3% (which most people do not reach until their 60s) and then only need a single sigmoidoscopy or colonoscopy.
Despite some departures from other guidelines, it’s worth emphasizing that the ACP guideline agrees that screening for CRC is generally worthwhile between the ages of 50 and 75 years. On that front, we in primary care have more work to do; the Centers for Disease Control and Prevention estimates that 28% of American adults older than 50 are not up-to-date on CRC screening. And despite some recent debate about the relative benefits and harms of screening colonoscopy, compared with less invasive fecal tests, gastroenterologists and family physicians can agree that the best screening test is the test that gets done.
A version of this article first appeared on Medscape.com.
U.S. has new dominant COVID variant called EG.5
Called “Eris” among avid COVID trackers, the strain EG.5 now accounts for 17% of all U.S. COVID infections, according to the latest Centers for Disease Control and Prevention estimates. That’s up from 12% the week prior.
EG.5 has been rising worldwide, just weeks after the World Health Organization added the strain to its official monitoring list. In the United Kingdom, it now accounts for 1 in 10 COVID cases, The Independent reported.
EG.5 is a descendant of the XBB strains that have dominated tracking lists in recent months. It has the same makeup as XBB.1.9.2 but carries an extra spike mutation, according to a summary published by the Center for Infectious Disease Research and Policy at the University of Minnesota. The spike protein is the part of the virus that allows it to enter human cells. But there’s no indication so far that EG.5 is more contagious or severe than other recent variants, according to the CIDRAP summary and a recent podcast from the American Medical Association. The CDC said that current vaccines protect against the variant.
U.S. hospitals saw a 12% increase in COVID admissions during the week ending on July 22, with 8,047 people being admitted because of the virus, up from an all-time low of 6,306 the week of June 24. In 17 states, the past-week increase in hospitalizations was 20% or greater. In Minnesota, the rate jumped by 50%, and in West Virginia, it jumped by 63%. Meanwhile, deaths reached their lowest weekly rate ever for the week of data ending July 29, with just 176 deaths reported by the CDC.
A version of this article first appeared on WebMD.com.
Called “Eris” among avid COVID trackers, the strain EG.5 now accounts for 17% of all U.S. COVID infections, according to the latest Centers for Disease Control and Prevention estimates. That’s up from 12% the week prior.
EG.5 has been rising worldwide, just weeks after the World Health Organization added the strain to its official monitoring list. In the United Kingdom, it now accounts for 1 in 10 COVID cases, The Independent reported.
EG.5 is a descendant of the XBB strains that have dominated tracking lists in recent months. It has the same makeup as XBB.1.9.2 but carries an extra spike mutation, according to a summary published by the Center for Infectious Disease Research and Policy at the University of Minnesota. The spike protein is the part of the virus that allows it to enter human cells. But there’s no indication so far that EG.5 is more contagious or severe than other recent variants, according to the CIDRAP summary and a recent podcast from the American Medical Association. The CDC said that current vaccines protect against the variant.
U.S. hospitals saw a 12% increase in COVID admissions during the week ending on July 22, with 8,047 people being admitted because of the virus, up from an all-time low of 6,306 the week of June 24. In 17 states, the past-week increase in hospitalizations was 20% or greater. In Minnesota, the rate jumped by 50%, and in West Virginia, it jumped by 63%. Meanwhile, deaths reached their lowest weekly rate ever for the week of data ending July 29, with just 176 deaths reported by the CDC.
A version of this article first appeared on WebMD.com.
Called “Eris” among avid COVID trackers, the strain EG.5 now accounts for 17% of all U.S. COVID infections, according to the latest Centers for Disease Control and Prevention estimates. That’s up from 12% the week prior.
EG.5 has been rising worldwide, just weeks after the World Health Organization added the strain to its official monitoring list. In the United Kingdom, it now accounts for 1 in 10 COVID cases, The Independent reported.
EG.5 is a descendant of the XBB strains that have dominated tracking lists in recent months. It has the same makeup as XBB.1.9.2 but carries an extra spike mutation, according to a summary published by the Center for Infectious Disease Research and Policy at the University of Minnesota. The spike protein is the part of the virus that allows it to enter human cells. But there’s no indication so far that EG.5 is more contagious or severe than other recent variants, according to the CIDRAP summary and a recent podcast from the American Medical Association. The CDC said that current vaccines protect against the variant.
U.S. hospitals saw a 12% increase in COVID admissions during the week ending on July 22, with 8,047 people being admitted because of the virus, up from an all-time low of 6,306 the week of June 24. In 17 states, the past-week increase in hospitalizations was 20% or greater. In Minnesota, the rate jumped by 50%, and in West Virginia, it jumped by 63%. Meanwhile, deaths reached their lowest weekly rate ever for the week of data ending July 29, with just 176 deaths reported by the CDC.
A version of this article first appeared on WebMD.com.
Unveiling the potential of prediction models in obstetrics
In the dawn of artificial intelligence’s potential to inform clinical practice, the importance of understanding the intent and interpretation of prediction tools is vital. In medicine, informed decision-making promotes patient autonomy and can lead to improved patient satisfaction and engagement in their own care.
This shared understanding enables patients to make informed choices about their care, reducing anxiety and increasing confidence in medical decision-making.
In obstetric clinical practice, prediction tools have been created to assess risk of primary cesarean delivery in gestational diabetes,1 cesarean delivery in hypertensive disorders of pregnancy,2 and failed induction of labor in nulliparous patients with an unfavorable cervix.3 By assessing a patient’s risk profile, clinicians can identify high-risk individuals who may require closer monitoring, early interventions, or specialized care. This allows for more timely interventions to optimize maternal and fetal health outcomes.
Other prediction tools are created to better elucidate to patients their individual risk of an outcome that may be modifiable, aiding physician counseling on mitigating factors to improve overall results. A relevant example is the American Diabetes Association’s risk of type 2 diabetes calculator used for counseling patients on risk reduction. This model includes both preexisting (ethnicity, family history, age, sex assigned at birth) and modifiable risk factors (body mass index, hypertension, physical activity) to predict risk of type 2 diabetes and is widely used in clinical practice to encourage integration of lifestyle changes to decrease risk.4 This model highlights the utility of prediction tools in counseling, providing quantitative data to clinicians to discuss a patient’s individual risk and how to mitigate that risk.
While predictive models clearly have many advantages and potential to improve personalized medicine, concerns have been raised that their interpretation and application can sometimes have unintended consequences as the complexity of these models can lead to variation in understanding among clinicians that impact decision-making. Different clinicians may assign different levels of importance to the predicted risks, resulting in differences in treatment plans and interventions. This variability can lead to disparities in care and outcomes, as patients with similar risk profiles may receive different management approaches based on the interpreting clinician.
Providers may either overly rely on prediction models or completely disregard them, depending on their level of trust or skepticism. Overreliance on prediction models may lead to the neglect of important clinical information or intuition, while disregarding the models may result in missed opportunities for early intervention or appropriate risk stratification. Achieving a balance between clinical judgment and the use of prediction models is crucial for optimal decision-making.
An example of how misinterpretation of the role of prediction tools in patient counseling can have far reaching consequences is the vaginal birth after cesarean (VBAC) calculator where race and ethnicity naturalized racial differences and likely contributed to cesarean overuse in Black pregnant people as non-White race was associated with a decreased chance of successful VBAC. Although the authors of the study that created the VBAC calculator intended it to be used as an adjunct to counseling, institutions and providers used low calculator scores to discourage or prohibit pregnant people from attempting a trial of labor after cesarean (TOLAC). This highlighted the importance of contextualizing the intent of prediction models within the broader clinical setting and individual patient circumstances and preferences.
This gap between intent and interpretation and subsequent application is influenced by individual clinician experience, training, personal biases, and subjective judgment. These subjective elements can introduce inconsistencies and variability in the utilization of prediction tools, leading to potential discrepancies in patient care. Inadequate understanding of prediction models and their statistical concepts can contribute to misinterpretation. It is this bias that prevents prediction models from serving their true purpose: to inform clinical decision-making, improve patient outcomes, and optimize resource allocation.
Clinicians may struggle with concepts such as predictive accuracy, overfitting, calibration, and external validation. Educational initiatives and enhanced training in statistical literacy can empower clinicians to better comprehend and apply prediction models in their practice. Researchers should make it clear that models should not be used in isolation, but rather integrated with clinical expertise and patient preferences. Understanding the limitations of prediction models and incorporating additional clinical information is essential.
Prediction models in obstetrics should undergo continuous evaluation and improvement to enhance their reliability and applicability. Regular updates, external validation, and recalibration are necessary to account for evolving clinical practices, changes in patient populations, and emerging evidence. Engaging clinicians in the evaluation process can foster ownership and promote a sense of trust in the models.
As machine learning and artificial intelligence improve the accuracy of prediction models, there is potential to revolutionize obstetric care by enabling more accurate individualized risk assessment and decision-making. Machine learning has the potential to significantly enhance prediction models in obstetrics by leveraging complex algorithms and advanced computational techniques. However, the unpredictable nature of clinician interpretation poses challenges to the effective utilization of these models.
By emphasizing communication, collaboration, education, and continuous evaluation, we can bridge the gap between prediction models and clinician interpretation that optimizes their use. This concerted effort will ultimately lead to improved patient care, enhanced clinical outcomes, and a more harmonious integration of these tools into obstetric practice.
Dr. Ramos is assistant professor of maternal fetal medicine and associate principal investigator at the Mother Infant Research Institute, Tufts University and Tufts Medical Center, Boston.
References
1. Ramos SZ et al. Predicting primary cesarean delivery in pregnancies complicated by gestational diabetes mellitus. Am J Obstet Gynecol. 2023 Jun 7;S0002-9378(23)00371-X. doi: 10.1016/j.ajog.2023.06.002.
2. Beninati MJ et al. Prediction model for vaginal birth after induction of labor in women with hypertensive disorders of pregnancy. Obstet Gynecol. 2020 Aug;136(2):402-410. doi: 10.1097/AOG.0000000000003938.
3. Levine LD et al. A validated calculator to estimate risk of cesarean after an induction of labor with an unfavorable cervix. Am J Obstet Gynecol. 2018 Feb;218(2):254.e1-254.e7. doi: 10.1016/j.ajog.2017.11.603.
4. American Diabetes Association. Our 60-Second Type 2 Diabetes Risk Test.
In the dawn of artificial intelligence’s potential to inform clinical practice, the importance of understanding the intent and interpretation of prediction tools is vital. In medicine, informed decision-making promotes patient autonomy and can lead to improved patient satisfaction and engagement in their own care.
This shared understanding enables patients to make informed choices about their care, reducing anxiety and increasing confidence in medical decision-making.
In obstetric clinical practice, prediction tools have been created to assess risk of primary cesarean delivery in gestational diabetes,1 cesarean delivery in hypertensive disorders of pregnancy,2 and failed induction of labor in nulliparous patients with an unfavorable cervix.3 By assessing a patient’s risk profile, clinicians can identify high-risk individuals who may require closer monitoring, early interventions, or specialized care. This allows for more timely interventions to optimize maternal and fetal health outcomes.
Other prediction tools are created to better elucidate to patients their individual risk of an outcome that may be modifiable, aiding physician counseling on mitigating factors to improve overall results. A relevant example is the American Diabetes Association’s risk of type 2 diabetes calculator used for counseling patients on risk reduction. This model includes both preexisting (ethnicity, family history, age, sex assigned at birth) and modifiable risk factors (body mass index, hypertension, physical activity) to predict risk of type 2 diabetes and is widely used in clinical practice to encourage integration of lifestyle changes to decrease risk.4 This model highlights the utility of prediction tools in counseling, providing quantitative data to clinicians to discuss a patient’s individual risk and how to mitigate that risk.
While predictive models clearly have many advantages and potential to improve personalized medicine, concerns have been raised that their interpretation and application can sometimes have unintended consequences as the complexity of these models can lead to variation in understanding among clinicians that impact decision-making. Different clinicians may assign different levels of importance to the predicted risks, resulting in differences in treatment plans and interventions. This variability can lead to disparities in care and outcomes, as patients with similar risk profiles may receive different management approaches based on the interpreting clinician.
Providers may either overly rely on prediction models or completely disregard them, depending on their level of trust or skepticism. Overreliance on prediction models may lead to the neglect of important clinical information or intuition, while disregarding the models may result in missed opportunities for early intervention or appropriate risk stratification. Achieving a balance between clinical judgment and the use of prediction models is crucial for optimal decision-making.
An example of how misinterpretation of the role of prediction tools in patient counseling can have far reaching consequences is the vaginal birth after cesarean (VBAC) calculator where race and ethnicity naturalized racial differences and likely contributed to cesarean overuse in Black pregnant people as non-White race was associated with a decreased chance of successful VBAC. Although the authors of the study that created the VBAC calculator intended it to be used as an adjunct to counseling, institutions and providers used low calculator scores to discourage or prohibit pregnant people from attempting a trial of labor after cesarean (TOLAC). This highlighted the importance of contextualizing the intent of prediction models within the broader clinical setting and individual patient circumstances and preferences.
This gap between intent and interpretation and subsequent application is influenced by individual clinician experience, training, personal biases, and subjective judgment. These subjective elements can introduce inconsistencies and variability in the utilization of prediction tools, leading to potential discrepancies in patient care. Inadequate understanding of prediction models and their statistical concepts can contribute to misinterpretation. It is this bias that prevents prediction models from serving their true purpose: to inform clinical decision-making, improve patient outcomes, and optimize resource allocation.
Clinicians may struggle with concepts such as predictive accuracy, overfitting, calibration, and external validation. Educational initiatives and enhanced training in statistical literacy can empower clinicians to better comprehend and apply prediction models in their practice. Researchers should make it clear that models should not be used in isolation, but rather integrated with clinical expertise and patient preferences. Understanding the limitations of prediction models and incorporating additional clinical information is essential.
Prediction models in obstetrics should undergo continuous evaluation and improvement to enhance their reliability and applicability. Regular updates, external validation, and recalibration are necessary to account for evolving clinical practices, changes in patient populations, and emerging evidence. Engaging clinicians in the evaluation process can foster ownership and promote a sense of trust in the models.
As machine learning and artificial intelligence improve the accuracy of prediction models, there is potential to revolutionize obstetric care by enabling more accurate individualized risk assessment and decision-making. Machine learning has the potential to significantly enhance prediction models in obstetrics by leveraging complex algorithms and advanced computational techniques. However, the unpredictable nature of clinician interpretation poses challenges to the effective utilization of these models.
By emphasizing communication, collaboration, education, and continuous evaluation, we can bridge the gap between prediction models and clinician interpretation that optimizes their use. This concerted effort will ultimately lead to improved patient care, enhanced clinical outcomes, and a more harmonious integration of these tools into obstetric practice.
Dr. Ramos is assistant professor of maternal fetal medicine and associate principal investigator at the Mother Infant Research Institute, Tufts University and Tufts Medical Center, Boston.
References
1. Ramos SZ et al. Predicting primary cesarean delivery in pregnancies complicated by gestational diabetes mellitus. Am J Obstet Gynecol. 2023 Jun 7;S0002-9378(23)00371-X. doi: 10.1016/j.ajog.2023.06.002.
2. Beninati MJ et al. Prediction model for vaginal birth after induction of labor in women with hypertensive disorders of pregnancy. Obstet Gynecol. 2020 Aug;136(2):402-410. doi: 10.1097/AOG.0000000000003938.
3. Levine LD et al. A validated calculator to estimate risk of cesarean after an induction of labor with an unfavorable cervix. Am J Obstet Gynecol. 2018 Feb;218(2):254.e1-254.e7. doi: 10.1016/j.ajog.2017.11.603.
4. American Diabetes Association. Our 60-Second Type 2 Diabetes Risk Test.
In the dawn of artificial intelligence’s potential to inform clinical practice, the importance of understanding the intent and interpretation of prediction tools is vital. In medicine, informed decision-making promotes patient autonomy and can lead to improved patient satisfaction and engagement in their own care.
This shared understanding enables patients to make informed choices about their care, reducing anxiety and increasing confidence in medical decision-making.
In obstetric clinical practice, prediction tools have been created to assess risk of primary cesarean delivery in gestational diabetes,1 cesarean delivery in hypertensive disorders of pregnancy,2 and failed induction of labor in nulliparous patients with an unfavorable cervix.3 By assessing a patient’s risk profile, clinicians can identify high-risk individuals who may require closer monitoring, early interventions, or specialized care. This allows for more timely interventions to optimize maternal and fetal health outcomes.
Other prediction tools are created to better elucidate to patients their individual risk of an outcome that may be modifiable, aiding physician counseling on mitigating factors to improve overall results. A relevant example is the American Diabetes Association’s risk of type 2 diabetes calculator used for counseling patients on risk reduction. This model includes both preexisting (ethnicity, family history, age, sex assigned at birth) and modifiable risk factors (body mass index, hypertension, physical activity) to predict risk of type 2 diabetes and is widely used in clinical practice to encourage integration of lifestyle changes to decrease risk.4 This model highlights the utility of prediction tools in counseling, providing quantitative data to clinicians to discuss a patient’s individual risk and how to mitigate that risk.
While predictive models clearly have many advantages and potential to improve personalized medicine, concerns have been raised that their interpretation and application can sometimes have unintended consequences as the complexity of these models can lead to variation in understanding among clinicians that impact decision-making. Different clinicians may assign different levels of importance to the predicted risks, resulting in differences in treatment plans and interventions. This variability can lead to disparities in care and outcomes, as patients with similar risk profiles may receive different management approaches based on the interpreting clinician.
Providers may either overly rely on prediction models or completely disregard them, depending on their level of trust or skepticism. Overreliance on prediction models may lead to the neglect of important clinical information or intuition, while disregarding the models may result in missed opportunities for early intervention or appropriate risk stratification. Achieving a balance between clinical judgment and the use of prediction models is crucial for optimal decision-making.
An example of how misinterpretation of the role of prediction tools in patient counseling can have far reaching consequences is the vaginal birth after cesarean (VBAC) calculator where race and ethnicity naturalized racial differences and likely contributed to cesarean overuse in Black pregnant people as non-White race was associated with a decreased chance of successful VBAC. Although the authors of the study that created the VBAC calculator intended it to be used as an adjunct to counseling, institutions and providers used low calculator scores to discourage or prohibit pregnant people from attempting a trial of labor after cesarean (TOLAC). This highlighted the importance of contextualizing the intent of prediction models within the broader clinical setting and individual patient circumstances and preferences.
This gap between intent and interpretation and subsequent application is influenced by individual clinician experience, training, personal biases, and subjective judgment. These subjective elements can introduce inconsistencies and variability in the utilization of prediction tools, leading to potential discrepancies in patient care. Inadequate understanding of prediction models and their statistical concepts can contribute to misinterpretation. It is this bias that prevents prediction models from serving their true purpose: to inform clinical decision-making, improve patient outcomes, and optimize resource allocation.
Clinicians may struggle with concepts such as predictive accuracy, overfitting, calibration, and external validation. Educational initiatives and enhanced training in statistical literacy can empower clinicians to better comprehend and apply prediction models in their practice. Researchers should make it clear that models should not be used in isolation, but rather integrated with clinical expertise and patient preferences. Understanding the limitations of prediction models and incorporating additional clinical information is essential.
Prediction models in obstetrics should undergo continuous evaluation and improvement to enhance their reliability and applicability. Regular updates, external validation, and recalibration are necessary to account for evolving clinical practices, changes in patient populations, and emerging evidence. Engaging clinicians in the evaluation process can foster ownership and promote a sense of trust in the models.
As machine learning and artificial intelligence improve the accuracy of prediction models, there is potential to revolutionize obstetric care by enabling more accurate individualized risk assessment and decision-making. Machine learning has the potential to significantly enhance prediction models in obstetrics by leveraging complex algorithms and advanced computational techniques. However, the unpredictable nature of clinician interpretation poses challenges to the effective utilization of these models.
By emphasizing communication, collaboration, education, and continuous evaluation, we can bridge the gap between prediction models and clinician interpretation that optimizes their use. This concerted effort will ultimately lead to improved patient care, enhanced clinical outcomes, and a more harmonious integration of these tools into obstetric practice.
Dr. Ramos is assistant professor of maternal fetal medicine and associate principal investigator at the Mother Infant Research Institute, Tufts University and Tufts Medical Center, Boston.
References
1. Ramos SZ et al. Predicting primary cesarean delivery in pregnancies complicated by gestational diabetes mellitus. Am J Obstet Gynecol. 2023 Jun 7;S0002-9378(23)00371-X. doi: 10.1016/j.ajog.2023.06.002.
2. Beninati MJ et al. Prediction model for vaginal birth after induction of labor in women with hypertensive disorders of pregnancy. Obstet Gynecol. 2020 Aug;136(2):402-410. doi: 10.1097/AOG.0000000000003938.
3. Levine LD et al. A validated calculator to estimate risk of cesarean after an induction of labor with an unfavorable cervix. Am J Obstet Gynecol. 2018 Feb;218(2):254.e1-254.e7. doi: 10.1016/j.ajog.2017.11.603.
4. American Diabetes Association. Our 60-Second Type 2 Diabetes Risk Test.
Top U.S. hospitals for psychiatric care ranked
McLean Hospital claimed the top spot in the 2022-2023 ranking as well.
Massachusetts General Hospital in Boston holds the No. 2 spot in the 2023-2024 U.S. News ranking for best psychiatry hospitals, up from No. 3 in 2022-2023.
New York–Presbyterian Hospital–Columbia and Cornell sits at No. 3 in 2023-2024, up from No. 4 in 2022-2023, while Johns Hopkins Hospital, Baltimore is ranked No. 4, down from No. 2.
Resnick Neuropsychiatric Hospital at the University of California, Los Angeles, is ranked No. 5 in 2023-2024 (up from No. 6 in 2022-2023), while UCSF Health–UCSF Medical Center, San Francisco, dropped to No. 6 in 2023-2024 (from No. 5 in 2022-2023).
No. 7 in 2023-2024 is Menninger Clinic, Houston, which held the No. 10 spot in 2022-2023.
According to U.S. News, the psychiatry rating is based on the expert opinion of surveyed psychiatrists. The seven ranked hospitals in psychiatry or psychiatric care were recommended by at least 5% of the psychiatric specialists responding to the magazine’s surveys in 2021, 2022, and 2023 as a facility where they would refer their patients.
“Consumers want useful resources to help them assess which hospital can best meet their specific care needs,” Ben Harder, chief of health analysis and managing editor at U.S. News, said in a statement.
“The 2023-2024 Best Hospitals rankings offer patients and the physicians with whom they consult a data-driven source for comparing performance in outcomes, patient satisfaction, and other metrics that matter to them,” Mr. Harder said.
Honor roll
This year, as in prior years, U.S. News also recognized “honor roll” hospitals that have excelled across multiple areas of care. However, in 2023-2024, for the first time, there is no ordinal ranking of hospitals making the honor roll. Instead, they are listed in alphabetical order.
In a letter to hospital leaders, U.S. News explained that the major change in format came after months of deliberation, feedback from health care organizations and professionals, and an analysis of how consumers navigate the magazine’s website.
Ordinal ranking of hospitals that make the honor roll “obscures the fact that all of the Honor Roll hospitals have attained the highest standard of care in the nation,” the letter reads.
With the new format, honor roll hospitals are listed in alphabetical order. In 2023-2024 there are 22.
2023-2024 Honor Roll Hospitals
- Barnes-Jewish Hospital, St. Louis
- Brigham and Women’s Hospital, Boston
- Cedars-Sinai Medical Center, Los Angeles
- Cleveland Clinic
- Hospitals of the University of Pennsylvania–Penn Medicine, Philadelphia
- Houston Methodist Hospital
- Johns Hopkins Hospital, Baltimore
- Massachusetts General Hospital, Boston
- Mayo Clinic, Rochester, Minn.
- Mount Sinai Hospital, New York
- New York–Presbyterian Hospital–Columbia and Cornell
- North Shore University Hospital at Northwell Health, Manhasset, N.Y.
- Northwestern Memorial Hospital, Chicago
- NYU Langone Hospitals, New York
- Rush University Medical Center, Chicago
- Stanford (Calif.) Health Care–Stanford Hospital
- UC San Diego Health–La Jolla and Hillcrest Hospitals
- UCLA Medical Center, Los Angeles
- UCSF Health–UCSF Medical Center, San Francisco
- University of Michigan Health–Ann Arbor
- UT Southwestern Medical Center, Dallas
- Vanderbilt University Medical Center, Nashville, Tenn.
According to U.S. News, to keep pace with consumers’ needs and the ever-evolving landscape of health care, “several refinements” are reflected in the latest best hospitals rankings.
These include the introduction of outpatient outcomes in key specialty rankings and surgical ratings, the expanded inclusion of other outpatient data, an increased weight on objective quality measures, and a reduced weight on expert opinion.
In addition, hospital profiles on USNews.com feature refined health equity measures, including a new measure of racial disparities in outcomes.
The full report for best hospitals, best specialty hospitals, and methodology is available online.
A version of this article first appeared on Medscape.com.
McLean Hospital claimed the top spot in the 2022-2023 ranking as well.
Massachusetts General Hospital in Boston holds the No. 2 spot in the 2023-2024 U.S. News ranking for best psychiatry hospitals, up from No. 3 in 2022-2023.
New York–Presbyterian Hospital–Columbia and Cornell sits at No. 3 in 2023-2024, up from No. 4 in 2022-2023, while Johns Hopkins Hospital, Baltimore is ranked No. 4, down from No. 2.
Resnick Neuropsychiatric Hospital at the University of California, Los Angeles, is ranked No. 5 in 2023-2024 (up from No. 6 in 2022-2023), while UCSF Health–UCSF Medical Center, San Francisco, dropped to No. 6 in 2023-2024 (from No. 5 in 2022-2023).
No. 7 in 2023-2024 is Menninger Clinic, Houston, which held the No. 10 spot in 2022-2023.
According to U.S. News, the psychiatry rating is based on the expert opinion of surveyed psychiatrists. The seven ranked hospitals in psychiatry or psychiatric care were recommended by at least 5% of the psychiatric specialists responding to the magazine’s surveys in 2021, 2022, and 2023 as a facility where they would refer their patients.
“Consumers want useful resources to help them assess which hospital can best meet their specific care needs,” Ben Harder, chief of health analysis and managing editor at U.S. News, said in a statement.
“The 2023-2024 Best Hospitals rankings offer patients and the physicians with whom they consult a data-driven source for comparing performance in outcomes, patient satisfaction, and other metrics that matter to them,” Mr. Harder said.
Honor roll
This year, as in prior years, U.S. News also recognized “honor roll” hospitals that have excelled across multiple areas of care. However, in 2023-2024, for the first time, there is no ordinal ranking of hospitals making the honor roll. Instead, they are listed in alphabetical order.
In a letter to hospital leaders, U.S. News explained that the major change in format came after months of deliberation, feedback from health care organizations and professionals, and an analysis of how consumers navigate the magazine’s website.
Ordinal ranking of hospitals that make the honor roll “obscures the fact that all of the Honor Roll hospitals have attained the highest standard of care in the nation,” the letter reads.
With the new format, honor roll hospitals are listed in alphabetical order. In 2023-2024 there are 22.
2023-2024 Honor Roll Hospitals
- Barnes-Jewish Hospital, St. Louis
- Brigham and Women’s Hospital, Boston
- Cedars-Sinai Medical Center, Los Angeles
- Cleveland Clinic
- Hospitals of the University of Pennsylvania–Penn Medicine, Philadelphia
- Houston Methodist Hospital
- Johns Hopkins Hospital, Baltimore
- Massachusetts General Hospital, Boston
- Mayo Clinic, Rochester, Minn.
- Mount Sinai Hospital, New York
- New York–Presbyterian Hospital–Columbia and Cornell
- North Shore University Hospital at Northwell Health, Manhasset, N.Y.
- Northwestern Memorial Hospital, Chicago
- NYU Langone Hospitals, New York
- Rush University Medical Center, Chicago
- Stanford (Calif.) Health Care–Stanford Hospital
- UC San Diego Health–La Jolla and Hillcrest Hospitals
- UCLA Medical Center, Los Angeles
- UCSF Health–UCSF Medical Center, San Francisco
- University of Michigan Health–Ann Arbor
- UT Southwestern Medical Center, Dallas
- Vanderbilt University Medical Center, Nashville, Tenn.
According to U.S. News, to keep pace with consumers’ needs and the ever-evolving landscape of health care, “several refinements” are reflected in the latest best hospitals rankings.
These include the introduction of outpatient outcomes in key specialty rankings and surgical ratings, the expanded inclusion of other outpatient data, an increased weight on objective quality measures, and a reduced weight on expert opinion.
In addition, hospital profiles on USNews.com feature refined health equity measures, including a new measure of racial disparities in outcomes.
The full report for best hospitals, best specialty hospitals, and methodology is available online.
A version of this article first appeared on Medscape.com.
McLean Hospital claimed the top spot in the 2022-2023 ranking as well.
Massachusetts General Hospital in Boston holds the No. 2 spot in the 2023-2024 U.S. News ranking for best psychiatry hospitals, up from No. 3 in 2022-2023.
New York–Presbyterian Hospital–Columbia and Cornell sits at No. 3 in 2023-2024, up from No. 4 in 2022-2023, while Johns Hopkins Hospital, Baltimore is ranked No. 4, down from No. 2.
Resnick Neuropsychiatric Hospital at the University of California, Los Angeles, is ranked No. 5 in 2023-2024 (up from No. 6 in 2022-2023), while UCSF Health–UCSF Medical Center, San Francisco, dropped to No. 6 in 2023-2024 (from No. 5 in 2022-2023).
No. 7 in 2023-2024 is Menninger Clinic, Houston, which held the No. 10 spot in 2022-2023.
According to U.S. News, the psychiatry rating is based on the expert opinion of surveyed psychiatrists. The seven ranked hospitals in psychiatry or psychiatric care were recommended by at least 5% of the psychiatric specialists responding to the magazine’s surveys in 2021, 2022, and 2023 as a facility where they would refer their patients.
“Consumers want useful resources to help them assess which hospital can best meet their specific care needs,” Ben Harder, chief of health analysis and managing editor at U.S. News, said in a statement.
“The 2023-2024 Best Hospitals rankings offer patients and the physicians with whom they consult a data-driven source for comparing performance in outcomes, patient satisfaction, and other metrics that matter to them,” Mr. Harder said.
Honor roll
This year, as in prior years, U.S. News also recognized “honor roll” hospitals that have excelled across multiple areas of care. However, in 2023-2024, for the first time, there is no ordinal ranking of hospitals making the honor roll. Instead, they are listed in alphabetical order.
In a letter to hospital leaders, U.S. News explained that the major change in format came after months of deliberation, feedback from health care organizations and professionals, and an analysis of how consumers navigate the magazine’s website.
Ordinal ranking of hospitals that make the honor roll “obscures the fact that all of the Honor Roll hospitals have attained the highest standard of care in the nation,” the letter reads.
With the new format, honor roll hospitals are listed in alphabetical order. In 2023-2024 there are 22.
2023-2024 Honor Roll Hospitals
- Barnes-Jewish Hospital, St. Louis
- Brigham and Women’s Hospital, Boston
- Cedars-Sinai Medical Center, Los Angeles
- Cleveland Clinic
- Hospitals of the University of Pennsylvania–Penn Medicine, Philadelphia
- Houston Methodist Hospital
- Johns Hopkins Hospital, Baltimore
- Massachusetts General Hospital, Boston
- Mayo Clinic, Rochester, Minn.
- Mount Sinai Hospital, New York
- New York–Presbyterian Hospital–Columbia and Cornell
- North Shore University Hospital at Northwell Health, Manhasset, N.Y.
- Northwestern Memorial Hospital, Chicago
- NYU Langone Hospitals, New York
- Rush University Medical Center, Chicago
- Stanford (Calif.) Health Care–Stanford Hospital
- UC San Diego Health–La Jolla and Hillcrest Hospitals
- UCLA Medical Center, Los Angeles
- UCSF Health–UCSF Medical Center, San Francisco
- University of Michigan Health–Ann Arbor
- UT Southwestern Medical Center, Dallas
- Vanderbilt University Medical Center, Nashville, Tenn.
According to U.S. News, to keep pace with consumers’ needs and the ever-evolving landscape of health care, “several refinements” are reflected in the latest best hospitals rankings.
These include the introduction of outpatient outcomes in key specialty rankings and surgical ratings, the expanded inclusion of other outpatient data, an increased weight on objective quality measures, and a reduced weight on expert opinion.
In addition, hospital profiles on USNews.com feature refined health equity measures, including a new measure of racial disparities in outcomes.
The full report for best hospitals, best specialty hospitals, and methodology is available online.
A version of this article first appeared on Medscape.com.