Federal Practitioner

The novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARSCoV- 2), which causes the respiratory disease coronavirus disease-19 (COVID- 19), was first identified as a cluster of cases of pneumonia in Wuhan, Hubei Province of China on December 31, 2019.1 Within a month, the disease had spread significantly, leading the World Health Organization (WHO) to designate COVID-19 a public health emergency of international concern. On March 11, 2020, the WHO declared COVID-19 a global pandemic.² As of August 18, 2020, the virus has infected > 21 million people, with > 750,000 deaths worldwide.3 The spread of COVID-19 has had a dramatic impact on social, economic, and health care issues throughout the world, which has been discussed elsewhere.⁴

Prior to the this century, members of the coronavirus family had minimal impact on human health.5 However, in the past 20 years, outbreaks have highlighted an emerging importance of coronaviruses in morbidity and mortality on a global scale. Although less prevalent than COVID-19, severe acute respiratory syndrome (SARS) in 2002 to 2003 and Middle East respiratory syndrome (MERS) in 2012 likely had higher mortality rates than the current pandemic.⁵ Based on this recent history, it is reasonable to assume that we will continue to see novel diseases with similar significant health and societal implications. The challenges presented to health care providers (HCPs) by such novel viral pathogens are numerous, including methods for rapid diagnosis, prevention, and treatment. In the current study, we focus on diagnosis issues, which were evident with COVID-19 with the time required to develop rapid and effective diagnostic modalities.

We have previously reported the utility of using artificial intelligence (AI) in the histopathologic diagnosis of cancer.^6-8 AI was first described in 1956 and involves the field of computer science in which machines are trained to learn from experience.⁹ Machine learning (ML) is a subset of AI and is achieved by using mathematic models to compute sample datasets.¹⁰ Current ML employs deep learning with neural network algorithms, which can recognize patterns and achieve complex computational tasks often far quicker and with increased precision than can humans.^11-13 In addition to applications in pathology, ML algorithms have both prognostic and diagnostic applications in multiple medical specialties, such as radiology, dermatology, ophthalmology, and cardiology.6 It is predicted that AI will impact almost every aspect of health care in the future.¹⁴

In this article, we examine the potential for AI to diagnose patients with COVID-19 pneumonia using chest radiographs (CXR) alone. This is done using Microsoft CustomVision (www.customvision.ai), a readily available, automated ML platform. Employing AI to both screen and diagnose emerging health emergencies such as COVID-19 has the potential to dramatically change how we approach medical care in the future. In addition, we describe the creation of a publicly available website (interknowlogy-covid-19 .azurewebsites.net) that could augment COVID-19 pneumonia CXR diagnosis.

Methods

For the training dataset, 103 CXR images of COVID-19 were downloaded from GitHub covid-chest-xray dataset^.15 Five hundred images of non-COVID-19 pneumonia and 500 images of the normal lung were downloaded from the Kaggle RSNA Pneumonia Detection Challenge dataset.¹⁶ To balance the dataset, we expanded the COVID-19 dataset to 500 images by slight rotation (probability = 1, max rotation = 5) and zooming (probability = 0.5, percentage area = 0.9) of the original images using the Augmentor Python package.¹⁷

Validation Dataset

For the validation dataset 30 random CXR images were obtained from the US Department of Veterans Affairs (VA) PACS (picture archiving and communication system). This dataset included 10 CXR images from hospitalized patients with COVID-19, 10 CXR pneumonia images from patients without COVID-19, and 10 normal CXRs. COVID-19 diagnoses were confirmed with a positive test result from the Xpert Xpress SARS-CoV-2 polymerase chain reaction (PCR) platform.¹⁸

Microsoft Custom

Vision Microsoft CustomVision is an automated image classification and object detection system that is a part of Microsoft Azure Cognitive Services (azure.microsoft.com). It has a pay-as-you-go model with fees depending on the computing needs and usage. It offers a free trial to users for 2 initial projects. The service is online with an easy-to-follow graphical user interface. No coding skills are necessary.

We created a new classification project in CustomVision and chose a compact general domain for small size and easy export to TensorFlow. js model format. TensorFlow.js is a JavaScript library that enables dynamic download and execution of ML models. After the project was created, we proceeded to upload our image dataset. Each class was uploaded separately and tagged with the appropriate label (covid pneumonia, non-covid pneumonia, or normal lung). The system rejected 16 COVID-19 images as duplicates. The final CustomVision training dataset consisted of 484 images of COVID-19 pneumonia, 500 images of non-COVID-19 pneumonia, and 500 images of normal lungs. Once uploaded, CustomVision self-trains using the dataset upon initiating the program (Figure 1).

Website Creation

CustomVision was used to train the model. It can be used to execute the model continuously, or the model can be compacted and decoupled from CustomVision. In this case, the model was compacted and decoupled for use in an online application. An Angular online application was created with TensorFlow.js. Within a user’s web browser, the model is executed when an image of a CXR is submitted. Confidence values for each classification are returned. In this design, after the initial webpage and model is downloaded, the webpage no longer needs to access any server components and performs all operations in the browser. Although the solution works well on mobile phone browsers and in low bandwidth situations, the quality of predictions may depend on the browser and device used. At no time does an image get submitted to the cloud.

Result

Overall, our trained model showed 92.9% precision and recall. Precision and recall results for each label were 98.9% and 94.8%, respectively for COVID-19 pneumonia; 91.8% and 89%, respectively, for non- COVID-19 pneumonia; and 88.8% and 95%, respectively, for normal lung (Figure 2). Next, we proceeded to validate the training model on the VA data by making individual predictions on 30 images from the VA dataset. Our model performed well with 100% sensitivity (recall), 95% specificity, 97% accuracy, 91% positive predictive value (precision), and 100% negative predictive value (Table).

Discussion

We successfully demonstrated the potential of using AI algorithms in assessing CXRs for COVID-19. We first trained the CustomVision automated image classification and object detection system to differentiate cases of COVID-19 from pneumonia from other etiologies as well as normal lung CXRs. We then tested our model against known patients from the James A. Haley Veterans’ Hospital in Tampa, Florida. The program achieved 100% sensitivity (recall), 95% specificity, 97% accuracy, 91% positive predictive value (precision), and 100% negative predictive value in differentiating the 3 scenarios. Using the trained ML model, we proceeded to create a website that could augment COVID-19 CXR diagnosis.¹⁹ The website works on mobile as well as desktop platforms. A health care provider can take a CXR photo with a mobile phone or upload the image file. The ML algorithm would provide the probability of COVID-19 pneumonia, non-COVID-19 pneumonia, or normal lung diagnosis (Figure 3).

Emerging diseases such as COVID-19 present numerous challenges to HCPs, governments, and businesses, as well as to individual members of society. As evidenced with COVID-19, the time from first recognition of an emerging pathogen to the development of methods for reliable diagnosis and treatment can be months, even with a concerted international effort. The gold standard for diagnosis of COVID-19 is by reverse transcriptase PCR (RT-PCR) technologies; however, early RT-PCR testing produced less than optimal results.^20-22 Even after the development of reliable tests for detection, making test kits readily available to health care providers on an adequate scale presents an additional challenge as evident with COVID-19.

Use of X-ray vs Computed Tomography

The lack of availability of diagnostic RTPCR with COVID-19 initially placed increased reliability on presumptive diagnoses via imaging in some situations.²³ Most of the literature evaluating radiographs of patients with COVID-19 focuses on chest computed tomography (CT) findings, with initial results suggesting CT was more accurate than early RT-PCR methodologies.21,22,24 The Radiological Society of North America Expert consensus statement on chest CT for COVID-19 states that CT findings can even precede positivity on RT-PCR in some cases.²² However, currently it does not recommend the use of CT scanning as a screening tool. Furthermore, the actual sensitivity and specificity of CT interpretation by radiologists for COVID-19 are unknown.²²

Characteristic CT findings include ground-glass opacities (GGOs) and consolidation most commonly in the lung periphery, though a diffuse distribution was found in a minority of patients.^21,23,25-27 Lomoro and colleagues recently summarized the CT findings from several reports that described abnormalities as most often bilateral and peripheral, subpleural, and affecting the lower lobes.26 Not surprisingly, CT appears more sensitive at detecting changes with COVID-19 than does CXR, with reports that a minority of patients exhibited CT changes before changes were visible on CXR.^23,26

We focused our study on the potential of AI in the examination of CXRs in patients with COVID-19, as there are several limitations to the routine use of CT scans with conditions such as COVID-19. Aside from the more considerable time required to obtain CTs, there are issues with contamination of CT suites, sometimes requiring a dedicated COVID-19 CT scanner.^23,28 The time constraints of decontamination or limited utilization of CT suites can delay or disrupt services for patients with and without COVID-19. Because of these factors, CXR may be a better resource to minimize the risk of infection to other patients. Also, accurate assessment of abnormalities on CXR for COVID-19 may identify patients in whom the CXR was performed for other purposes.²³ CXR is more readily available than CT, especially in more remote or underdeveloped areas.²⁸ Finally, as with CT, CXR abnormalities are reported to have appeared before RT-PCR tests became positive for a minority of patients.²³

CXR findings described in patients with COVID-19 are similar to those of CT and include GGOs, consolidation, and hazy increased opacities.^{23,25,26,28,29} Like CT, the majority of patients who received CXR demonstrated greater involvement in the lower zones and peripherally.^{23,25,26,28,29} Most patients showed bilateral involvement. However, while these findings are common in patients with COVID-19, they are not specific and can be seen in other conditions, such as other viral pneumonia, bacterial pneumonia, injury from drug toxicity, inhalation injury, connective tissue disease, and idiopathic conditions.

Application of AI for COVID-19

Applications of AI in interpreting radiographs of various types are numerous, and extensive literature has been written on the topic.³⁰ Using deep learning algorithms, AI has multiple possible roles to augment traditional radiograph interpretation. These include the potential for screening, triaging, and increasing the speed to render diagnoses. It also can provide a rapid “second opinion” to the radiologist to support the final interpretation. In areas with critical shortages of radiologists, AI potentially can be used to render the definitive diagnosis. In COVID- 19, imaging studies have been shown to correlate with disease severity and mortality, and AI could assist in monitoring the course of the disease as it progresses and potentially identify patients at greatest risk.²⁷ Furthermore, early results from PCR have been considered suboptimal, and it is known that patients with COVID-19 can test negative initially even by reliable testing methodologies. As AI technology progresses, interpretation can detect and guide triage and treatment of patients with high suspicions of COVID-19 but negative initial PCR results, or in situations where test availability is limited or results are delayed. There are numerous potential benefits should a rapid diagnostic test as simple as a CXR be able to reliably impact containment and prevention of the spread of contagions such as COVID- 19 early in its course.

Few studies have assessed using AI in the radiologic diagnosis of COVID-19, most of which use CT scanning. Bai and colleagues demonstrated increased accuracy, sensitivity, and specificity in distinguishing chest CTs of COVID-19 patients from other types of pneumonia.^21,31 A separate study demonstrated the utility of using AI to differentiate COVID-19 from community-acquired pneumonia with CT.32 However, the effective utility of AI for CXR interpretation also has been demonstrated.^14,33 Implementation of convolutional neural network layers has allowed for reliable differentiation of viral and bacterial pneumonia with CXR imaging.³⁴ Evidence suggests that there is great potential in the application of AI in the interpretation of radiographs of all types.

Finally, we have developed a publicly available website based on our studies.¹⁸ This website is for research use only as it is based on data from our preliminary investigation. To appear within the website, images must have protected health information removed before uploading. The information on the website, including text, graphics, images, or other material, is for research and may not be appropriate for all circumstances. The website does not provide medical, professional, or licensed advice and is not a substitute for consultation with a HCP. Medical advice should be sought from a qualified HCP for any questions, and the website should not be used for medical diagnosis or treatment.

Limitations

In our preliminary study, we have demonstrated the potential impact AI can have in multiple aspects of patient care for emerging pathogens such as COVID-19 using a test as readily available as a CXR. However, several limitations to this investigation should be mentioned. The study is retrospective in nature with limited sample size and with X-rays from patients with various stages of COVID-19 pneumonia. Also, cases of non-COVID-19 pneumonia are not stratified into different types or etiologies. We intend to demonstrate the potential of AI in differentiating COVID-19 pneumonia from non-COVID-19 pneumonia of any etiology, though future studies should address comparison of COVID-19 cases to more specific types of pneumonias, such as of bacterial or viral origin. Furthermore, the present study does not address any potential effects of additional radiographic findings from coexistent conditions, such as pulmonary edema as seen in congestive heart failure, pleural effusions (which can be seen with COVID-19 pneumonia, though rarely), interstitial lung disease, etc. Future studies are required to address these issues. Ultimately, prospective studies to assess AI-assisted radiographic interpretation in conditions such as COVID-19 are required to demonstrate the impact on diagnosis, treatment, outcome, and patient safety as these technologies are implemented.

Conclusions

We have used a readily available, commercial platform to demonstrate the potential of AI to assist in the successful diagnosis of COVID-19 pneumonia on CXR images. While this technology has numerous applications in radiology, we have focused on the potential impact on future world health crises such as COVID-19. The findings have implications for screening and triage, initial diagnosis, monitoring disease progression, and identifying patients at increased risk of morbidity and mortality. Based on the data, a website was created to demonstrate how such technologies could be shared and distributed to others to combat entities such as COVID-19 moving forward. Our study offers a small window into the potential for how AI will likely dramatically change the practice of medicine in the future.

The novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARSCoV- 2), which causes the respiratory disease coronavirus disease-19 (COVID- 19), was first identified as a cluster of cases of pneumonia in Wuhan, Hubei Province of China on December 31, 2019.1 Within a month, the disease had spread significantly, leading the World Health Organization (WHO) to designate COVID-19 a public health emergency of international concern. On March 11, 2020, the WHO declared COVID-19 a global pandemic.² As of August 18, 2020, the virus has infected > 21 million people, with > 750,000 deaths worldwide.3 The spread of COVID-19 has had a dramatic impact on social, economic, and health care issues throughout the world, which has been discussed elsewhere.⁴

Prior to the this century, members of the coronavirus family had minimal impact on human health.5 However, in the past 20 years, outbreaks have highlighted an emerging importance of coronaviruses in morbidity and mortality on a global scale. Although less prevalent than COVID-19, severe acute respiratory syndrome (SARS) in 2002 to 2003 and Middle East respiratory syndrome (MERS) in 2012 likely had higher mortality rates than the current pandemic.⁵ Based on this recent history, it is reasonable to assume that we will continue to see novel diseases with similar significant health and societal implications. The challenges presented to health care providers (HCPs) by such novel viral pathogens are numerous, including methods for rapid diagnosis, prevention, and treatment. In the current study, we focus on diagnosis issues, which were evident with COVID-19 with the time required to develop rapid and effective diagnostic modalities.

We have previously reported the utility of using artificial intelligence (AI) in the histopathologic diagnosis of cancer.^6-8 AI was first described in 1956 and involves the field of computer science in which machines are trained to learn from experience.⁹ Machine learning (ML) is a subset of AI and is achieved by using mathematic models to compute sample datasets.¹⁰ Current ML employs deep learning with neural network algorithms, which can recognize patterns and achieve complex computational tasks often far quicker and with increased precision than can humans.^11-13 In addition to applications in pathology, ML algorithms have both prognostic and diagnostic applications in multiple medical specialties, such as radiology, dermatology, ophthalmology, and cardiology.6 It is predicted that AI will impact almost every aspect of health care in the future.¹⁴

In this article, we examine the potential for AI to diagnose patients with COVID-19 pneumonia using chest radiographs (CXR) alone. This is done using Microsoft CustomVision (www.customvision.ai), a readily available, automated ML platform. Employing AI to both screen and diagnose emerging health emergencies such as COVID-19 has the potential to dramatically change how we approach medical care in the future. In addition, we describe the creation of a publicly available website (interknowlogy-covid-19 .azurewebsites.net) that could augment COVID-19 pneumonia CXR diagnosis.

Methods

For the training dataset, 103 CXR images of COVID-19 were downloaded from GitHub covid-chest-xray dataset^.15 Five hundred images of non-COVID-19 pneumonia and 500 images of the normal lung were downloaded from the Kaggle RSNA Pneumonia Detection Challenge dataset.¹⁶ To balance the dataset, we expanded the COVID-19 dataset to 500 images by slight rotation (probability = 1, max rotation = 5) and zooming (probability = 0.5, percentage area = 0.9) of the original images using the Augmentor Python package.¹⁷

Validation Dataset

For the validation dataset 30 random CXR images were obtained from the US Department of Veterans Affairs (VA) PACS (picture archiving and communication system). This dataset included 10 CXR images from hospitalized patients with COVID-19, 10 CXR pneumonia images from patients without COVID-19, and 10 normal CXRs. COVID-19 diagnoses were confirmed with a positive test result from the Xpert Xpress SARS-CoV-2 polymerase chain reaction (PCR) platform.¹⁸

Microsoft Custom

Vision Microsoft CustomVision is an automated image classification and object detection system that is a part of Microsoft Azure Cognitive Services (azure.microsoft.com). It has a pay-as-you-go model with fees depending on the computing needs and usage. It offers a free trial to users for 2 initial projects. The service is online with an easy-to-follow graphical user interface. No coding skills are necessary.

We created a new classification project in CustomVision and chose a compact general domain for small size and easy export to TensorFlow. js model format. TensorFlow.js is a JavaScript library that enables dynamic download and execution of ML models. After the project was created, we proceeded to upload our image dataset. Each class was uploaded separately and tagged with the appropriate label (covid pneumonia, non-covid pneumonia, or normal lung). The system rejected 16 COVID-19 images as duplicates. The final CustomVision training dataset consisted of 484 images of COVID-19 pneumonia, 500 images of non-COVID-19 pneumonia, and 500 images of normal lungs. Once uploaded, CustomVision self-trains using the dataset upon initiating the program (Figure 1).

Website Creation

CustomVision was used to train the model. It can be used to execute the model continuously, or the model can be compacted and decoupled from CustomVision. In this case, the model was compacted and decoupled for use in an online application. An Angular online application was created with TensorFlow.js. Within a user’s web browser, the model is executed when an image of a CXR is submitted. Confidence values for each classification are returned. In this design, after the initial webpage and model is downloaded, the webpage no longer needs to access any server components and performs all operations in the browser. Although the solution works well on mobile phone browsers and in low bandwidth situations, the quality of predictions may depend on the browser and device used. At no time does an image get submitted to the cloud.

Result

Overall, our trained model showed 92.9% precision and recall. Precision and recall results for each label were 98.9% and 94.8%, respectively for COVID-19 pneumonia; 91.8% and 89%, respectively, for non- COVID-19 pneumonia; and 88.8% and 95%, respectively, for normal lung (Figure 2). Next, we proceeded to validate the training model on the VA data by making individual predictions on 30 images from the VA dataset. Our model performed well with 100% sensitivity (recall), 95% specificity, 97% accuracy, 91% positive predictive value (precision), and 100% negative predictive value (Table).

Discussion

We successfully demonstrated the potential of using AI algorithms in assessing CXRs for COVID-19. We first trained the CustomVision automated image classification and object detection system to differentiate cases of COVID-19 from pneumonia from other etiologies as well as normal lung CXRs. We then tested our model against known patients from the James A. Haley Veterans’ Hospital in Tampa, Florida. The program achieved 100% sensitivity (recall), 95% specificity, 97% accuracy, 91% positive predictive value (precision), and 100% negative predictive value in differentiating the 3 scenarios. Using the trained ML model, we proceeded to create a website that could augment COVID-19 CXR diagnosis.¹⁹ The website works on mobile as well as desktop platforms. A health care provider can take a CXR photo with a mobile phone or upload the image file. The ML algorithm would provide the probability of COVID-19 pneumonia, non-COVID-19 pneumonia, or normal lung diagnosis (Figure 3).

Emerging diseases such as COVID-19 present numerous challenges to HCPs, governments, and businesses, as well as to individual members of society. As evidenced with COVID-19, the time from first recognition of an emerging pathogen to the development of methods for reliable diagnosis and treatment can be months, even with a concerted international effort. The gold standard for diagnosis of COVID-19 is by reverse transcriptase PCR (RT-PCR) technologies; however, early RT-PCR testing produced less than optimal results.^20-22 Even after the development of reliable tests for detection, making test kits readily available to health care providers on an adequate scale presents an additional challenge as evident with COVID-19.

Use of X-ray vs Computed Tomography

The lack of availability of diagnostic RTPCR with COVID-19 initially placed increased reliability on presumptive diagnoses via imaging in some situations.²³ Most of the literature evaluating radiographs of patients with COVID-19 focuses on chest computed tomography (CT) findings, with initial results suggesting CT was more accurate than early RT-PCR methodologies.21,22,24 The Radiological Society of North America Expert consensus statement on chest CT for COVID-19 states that CT findings can even precede positivity on RT-PCR in some cases.²² However, currently it does not recommend the use of CT scanning as a screening tool. Furthermore, the actual sensitivity and specificity of CT interpretation by radiologists for COVID-19 are unknown.²²

Characteristic CT findings include ground-glass opacities (GGOs) and consolidation most commonly in the lung periphery, though a diffuse distribution was found in a minority of patients.^21,23,25-27 Lomoro and colleagues recently summarized the CT findings from several reports that described abnormalities as most often bilateral and peripheral, subpleural, and affecting the lower lobes.26 Not surprisingly, CT appears more sensitive at detecting changes with COVID-19 than does CXR, with reports that a minority of patients exhibited CT changes before changes were visible on CXR.^23,26

We focused our study on the potential of AI in the examination of CXRs in patients with COVID-19, as there are several limitations to the routine use of CT scans with conditions such as COVID-19. Aside from the more considerable time required to obtain CTs, there are issues with contamination of CT suites, sometimes requiring a dedicated COVID-19 CT scanner.^23,28 The time constraints of decontamination or limited utilization of CT suites can delay or disrupt services for patients with and without COVID-19. Because of these factors, CXR may be a better resource to minimize the risk of infection to other patients. Also, accurate assessment of abnormalities on CXR for COVID-19 may identify patients in whom the CXR was performed for other purposes.²³ CXR is more readily available than CT, especially in more remote or underdeveloped areas.²⁸ Finally, as with CT, CXR abnormalities are reported to have appeared before RT-PCR tests became positive for a minority of patients.²³

CXR findings described in patients with COVID-19 are similar to those of CT and include GGOs, consolidation, and hazy increased opacities.^{23,25,26,28,29} Like CT, the majority of patients who received CXR demonstrated greater involvement in the lower zones and peripherally.^{23,25,26,28,29} Most patients showed bilateral involvement. However, while these findings are common in patients with COVID-19, they are not specific and can be seen in other conditions, such as other viral pneumonia, bacterial pneumonia, injury from drug toxicity, inhalation injury, connective tissue disease, and idiopathic conditions.

Application of AI for COVID-19

Applications of AI in interpreting radiographs of various types are numerous, and extensive literature has been written on the topic.³⁰ Using deep learning algorithms, AI has multiple possible roles to augment traditional radiograph interpretation. These include the potential for screening, triaging, and increasing the speed to render diagnoses. It also can provide a rapid “second opinion” to the radiologist to support the final interpretation. In areas with critical shortages of radiologists, AI potentially can be used to render the definitive diagnosis. In COVID- 19, imaging studies have been shown to correlate with disease severity and mortality, and AI could assist in monitoring the course of the disease as it progresses and potentially identify patients at greatest risk.²⁷ Furthermore, early results from PCR have been considered suboptimal, and it is known that patients with COVID-19 can test negative initially even by reliable testing methodologies. As AI technology progresses, interpretation can detect and guide triage and treatment of patients with high suspicions of COVID-19 but negative initial PCR results, or in situations where test availability is limited or results are delayed. There are numerous potential benefits should a rapid diagnostic test as simple as a CXR be able to reliably impact containment and prevention of the spread of contagions such as COVID- 19 early in its course.

Few studies have assessed using AI in the radiologic diagnosis of COVID-19, most of which use CT scanning. Bai and colleagues demonstrated increased accuracy, sensitivity, and specificity in distinguishing chest CTs of COVID-19 patients from other types of pneumonia.^21,31 A separate study demonstrated the utility of using AI to differentiate COVID-19 from community-acquired pneumonia with CT.32 However, the effective utility of AI for CXR interpretation also has been demonstrated.^14,33 Implementation of convolutional neural network layers has allowed for reliable differentiation of viral and bacterial pneumonia with CXR imaging.³⁴ Evidence suggests that there is great potential in the application of AI in the interpretation of radiographs of all types.

Finally, we have developed a publicly available website based on our studies.¹⁸ This website is for research use only as it is based on data from our preliminary investigation. To appear within the website, images must have protected health information removed before uploading. The information on the website, including text, graphics, images, or other material, is for research and may not be appropriate for all circumstances. The website does not provide medical, professional, or licensed advice and is not a substitute for consultation with a HCP. Medical advice should be sought from a qualified HCP for any questions, and the website should not be used for medical diagnosis or treatment.

Limitations

In our preliminary study, we have demonstrated the potential impact AI can have in multiple aspects of patient care for emerging pathogens such as COVID-19 using a test as readily available as a CXR. However, several limitations to this investigation should be mentioned. The study is retrospective in nature with limited sample size and with X-rays from patients with various stages of COVID-19 pneumonia. Also, cases of non-COVID-19 pneumonia are not stratified into different types or etiologies. We intend to demonstrate the potential of AI in differentiating COVID-19 pneumonia from non-COVID-19 pneumonia of any etiology, though future studies should address comparison of COVID-19 cases to more specific types of pneumonias, such as of bacterial or viral origin. Furthermore, the present study does not address any potential effects of additional radiographic findings from coexistent conditions, such as pulmonary edema as seen in congestive heart failure, pleural effusions (which can be seen with COVID-19 pneumonia, though rarely), interstitial lung disease, etc. Future studies are required to address these issues. Ultimately, prospective studies to assess AI-assisted radiographic interpretation in conditions such as COVID-19 are required to demonstrate the impact on diagnosis, treatment, outcome, and patient safety as these technologies are implemented.

Conclusions

We have used a readily available, commercial platform to demonstrate the potential of AI to assist in the successful diagnosis of COVID-19 pneumonia on CXR images. While this technology has numerous applications in radiology, we have focused on the potential impact on future world health crises such as COVID-19. The findings have implications for screening and triage, initial diagnosis, monitoring disease progression, and identifying patients at increased risk of morbidity and mortality. Based on the data, a website was created to demonstrate how such technologies could be shared and distributed to others to combat entities such as COVID-19 moving forward. Our study offers a small window into the potential for how AI will likely dramatically change the practice of medicine in the future.

The novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARSCoV- 2), which causes the respiratory disease coronavirus disease-19 (COVID- 19), was first identified as a cluster of cases of pneumonia in Wuhan, Hubei Province of China on December 31, 2019.1 Within a month, the disease had spread significantly, leading the World Health Organization (WHO) to designate COVID-19 a public health emergency of international concern. On March 11, 2020, the WHO declared COVID-19 a global pandemic.² As of August 18, 2020, the virus has infected > 21 million people, with > 750,000 deaths worldwide.3 The spread of COVID-19 has had a dramatic impact on social, economic, and health care issues throughout the world, which has been discussed elsewhere.⁴

Prior to the this century, members of the coronavirus family had minimal impact on human health.5 However, in the past 20 years, outbreaks have highlighted an emerging importance of coronaviruses in morbidity and mortality on a global scale. Although less prevalent than COVID-19, severe acute respiratory syndrome (SARS) in 2002 to 2003 and Middle East respiratory syndrome (MERS) in 2012 likely had higher mortality rates than the current pandemic.⁵ Based on this recent history, it is reasonable to assume that we will continue to see novel diseases with similar significant health and societal implications. The challenges presented to health care providers (HCPs) by such novel viral pathogens are numerous, including methods for rapid diagnosis, prevention, and treatment. In the current study, we focus on diagnosis issues, which were evident with COVID-19 with the time required to develop rapid and effective diagnostic modalities.

We have previously reported the utility of using artificial intelligence (AI) in the histopathologic diagnosis of cancer.^6-8 AI was first described in 1956 and involves the field of computer science in which machines are trained to learn from experience.⁹ Machine learning (ML) is a subset of AI and is achieved by using mathematic models to compute sample datasets.¹⁰ Current ML employs deep learning with neural network algorithms, which can recognize patterns and achieve complex computational tasks often far quicker and with increased precision than can humans.^11-13 In addition to applications in pathology, ML algorithms have both prognostic and diagnostic applications in multiple medical specialties, such as radiology, dermatology, ophthalmology, and cardiology.6 It is predicted that AI will impact almost every aspect of health care in the future.¹⁴

In this article, we examine the potential for AI to diagnose patients with COVID-19 pneumonia using chest radiographs (CXR) alone. This is done using Microsoft CustomVision (www.customvision.ai), a readily available, automated ML platform. Employing AI to both screen and diagnose emerging health emergencies such as COVID-19 has the potential to dramatically change how we approach medical care in the future. In addition, we describe the creation of a publicly available website (interknowlogy-covid-19 .azurewebsites.net) that could augment COVID-19 pneumonia CXR diagnosis.

Methods

For the training dataset, 103 CXR images of COVID-19 were downloaded from GitHub covid-chest-xray dataset^.15 Five hundred images of non-COVID-19 pneumonia and 500 images of the normal lung were downloaded from the Kaggle RSNA Pneumonia Detection Challenge dataset.¹⁶ To balance the dataset, we expanded the COVID-19 dataset to 500 images by slight rotation (probability = 1, max rotation = 5) and zooming (probability = 0.5, percentage area = 0.9) of the original images using the Augmentor Python package.¹⁷

Validation Dataset

For the validation dataset 30 random CXR images were obtained from the US Department of Veterans Affairs (VA) PACS (picture archiving and communication system). This dataset included 10 CXR images from hospitalized patients with COVID-19, 10 CXR pneumonia images from patients without COVID-19, and 10 normal CXRs. COVID-19 diagnoses were confirmed with a positive test result from the Xpert Xpress SARS-CoV-2 polymerase chain reaction (PCR) platform.¹⁸

Microsoft Custom

Vision Microsoft CustomVision is an automated image classification and object detection system that is a part of Microsoft Azure Cognitive Services (azure.microsoft.com). It has a pay-as-you-go model with fees depending on the computing needs and usage. It offers a free trial to users for 2 initial projects. The service is online with an easy-to-follow graphical user interface. No coding skills are necessary.

We created a new classification project in CustomVision and chose a compact general domain for small size and easy export to TensorFlow. js model format. TensorFlow.js is a JavaScript library that enables dynamic download and execution of ML models. After the project was created, we proceeded to upload our image dataset. Each class was uploaded separately and tagged with the appropriate label (covid pneumonia, non-covid pneumonia, or normal lung). The system rejected 16 COVID-19 images as duplicates. The final CustomVision training dataset consisted of 484 images of COVID-19 pneumonia, 500 images of non-COVID-19 pneumonia, and 500 images of normal lungs. Once uploaded, CustomVision self-trains using the dataset upon initiating the program (Figure 1).

Website Creation

CustomVision was used to train the model. It can be used to execute the model continuously, or the model can be compacted and decoupled from CustomVision. In this case, the model was compacted and decoupled for use in an online application. An Angular online application was created with TensorFlow.js. Within a user’s web browser, the model is executed when an image of a CXR is submitted. Confidence values for each classification are returned. In this design, after the initial webpage and model is downloaded, the webpage no longer needs to access any server components and performs all operations in the browser. Although the solution works well on mobile phone browsers and in low bandwidth situations, the quality of predictions may depend on the browser and device used. At no time does an image get submitted to the cloud.

Result

Overall, our trained model showed 92.9% precision and recall. Precision and recall results for each label were 98.9% and 94.8%, respectively for COVID-19 pneumonia; 91.8% and 89%, respectively, for non- COVID-19 pneumonia; and 88.8% and 95%, respectively, for normal lung (Figure 2). Next, we proceeded to validate the training model on the VA data by making individual predictions on 30 images from the VA dataset. Our model performed well with 100% sensitivity (recall), 95% specificity, 97% accuracy, 91% positive predictive value (precision), and 100% negative predictive value (Table).

Discussion

We successfully demonstrated the potential of using AI algorithms in assessing CXRs for COVID-19. We first trained the CustomVision automated image classification and object detection system to differentiate cases of COVID-19 from pneumonia from other etiologies as well as normal lung CXRs. We then tested our model against known patients from the James A. Haley Veterans’ Hospital in Tampa, Florida. The program achieved 100% sensitivity (recall), 95% specificity, 97% accuracy, 91% positive predictive value (precision), and 100% negative predictive value in differentiating the 3 scenarios. Using the trained ML model, we proceeded to create a website that could augment COVID-19 CXR diagnosis.¹⁹ The website works on mobile as well as desktop platforms. A health care provider can take a CXR photo with a mobile phone or upload the image file. The ML algorithm would provide the probability of COVID-19 pneumonia, non-COVID-19 pneumonia, or normal lung diagnosis (Figure 3).

Emerging diseases such as COVID-19 present numerous challenges to HCPs, governments, and businesses, as well as to individual members of society. As evidenced with COVID-19, the time from first recognition of an emerging pathogen to the development of methods for reliable diagnosis and treatment can be months, even with a concerted international effort. The gold standard for diagnosis of COVID-19 is by reverse transcriptase PCR (RT-PCR) technologies; however, early RT-PCR testing produced less than optimal results.^20-22 Even after the development of reliable tests for detection, making test kits readily available to health care providers on an adequate scale presents an additional challenge as evident with COVID-19.

Use of X-ray vs Computed Tomography

The lack of availability of diagnostic RTPCR with COVID-19 initially placed increased reliability on presumptive diagnoses via imaging in some situations.²³ Most of the literature evaluating radiographs of patients with COVID-19 focuses on chest computed tomography (CT) findings, with initial results suggesting CT was more accurate than early RT-PCR methodologies.21,22,24 The Radiological Society of North America Expert consensus statement on chest CT for COVID-19 states that CT findings can even precede positivity on RT-PCR in some cases.²² However, currently it does not recommend the use of CT scanning as a screening tool. Furthermore, the actual sensitivity and specificity of CT interpretation by radiologists for COVID-19 are unknown.²²

Characteristic CT findings include ground-glass opacities (GGOs) and consolidation most commonly in the lung periphery, though a diffuse distribution was found in a minority of patients.^21,23,25-27 Lomoro and colleagues recently summarized the CT findings from several reports that described abnormalities as most often bilateral and peripheral, subpleural, and affecting the lower lobes.26 Not surprisingly, CT appears more sensitive at detecting changes with COVID-19 than does CXR, with reports that a minority of patients exhibited CT changes before changes were visible on CXR.^23,26

We focused our study on the potential of AI in the examination of CXRs in patients with COVID-19, as there are several limitations to the routine use of CT scans with conditions such as COVID-19. Aside from the more considerable time required to obtain CTs, there are issues with contamination of CT suites, sometimes requiring a dedicated COVID-19 CT scanner.^23,28 The time constraints of decontamination or limited utilization of CT suites can delay or disrupt services for patients with and without COVID-19. Because of these factors, CXR may be a better resource to minimize the risk of infection to other patients. Also, accurate assessment of abnormalities on CXR for COVID-19 may identify patients in whom the CXR was performed for other purposes.²³ CXR is more readily available than CT, especially in more remote or underdeveloped areas.²⁸ Finally, as with CT, CXR abnormalities are reported to have appeared before RT-PCR tests became positive for a minority of patients.²³

CXR findings described in patients with COVID-19 are similar to those of CT and include GGOs, consolidation, and hazy increased opacities.^{23,25,26,28,29} Like CT, the majority of patients who received CXR demonstrated greater involvement in the lower zones and peripherally.^{23,25,26,28,29} Most patients showed bilateral involvement. However, while these findings are common in patients with COVID-19, they are not specific and can be seen in other conditions, such as other viral pneumonia, bacterial pneumonia, injury from drug toxicity, inhalation injury, connective tissue disease, and idiopathic conditions.

Application of AI for COVID-19

Applications of AI in interpreting radiographs of various types are numerous, and extensive literature has been written on the topic.³⁰ Using deep learning algorithms, AI has multiple possible roles to augment traditional radiograph interpretation. These include the potential for screening, triaging, and increasing the speed to render diagnoses. It also can provide a rapid “second opinion” to the radiologist to support the final interpretation. In areas with critical shortages of radiologists, AI potentially can be used to render the definitive diagnosis. In COVID- 19, imaging studies have been shown to correlate with disease severity and mortality, and AI could assist in monitoring the course of the disease as it progresses and potentially identify patients at greatest risk.²⁷ Furthermore, early results from PCR have been considered suboptimal, and it is known that patients with COVID-19 can test negative initially even by reliable testing methodologies. As AI technology progresses, interpretation can detect and guide triage and treatment of patients with high suspicions of COVID-19 but negative initial PCR results, or in situations where test availability is limited or results are delayed. There are numerous potential benefits should a rapid diagnostic test as simple as a CXR be able to reliably impact containment and prevention of the spread of contagions such as COVID- 19 early in its course.

Few studies have assessed using AI in the radiologic diagnosis of COVID-19, most of which use CT scanning. Bai and colleagues demonstrated increased accuracy, sensitivity, and specificity in distinguishing chest CTs of COVID-19 patients from other types of pneumonia.^21,31 A separate study demonstrated the utility of using AI to differentiate COVID-19 from community-acquired pneumonia with CT.32 However, the effective utility of AI for CXR interpretation also has been demonstrated.^14,33 Implementation of convolutional neural network layers has allowed for reliable differentiation of viral and bacterial pneumonia with CXR imaging.³⁴ Evidence suggests that there is great potential in the application of AI in the interpretation of radiographs of all types.

Finally, we have developed a publicly available website based on our studies.¹⁸ This website is for research use only as it is based on data from our preliminary investigation. To appear within the website, images must have protected health information removed before uploading. The information on the website, including text, graphics, images, or other material, is for research and may not be appropriate for all circumstances. The website does not provide medical, professional, or licensed advice and is not a substitute for consultation with a HCP. Medical advice should be sought from a qualified HCP for any questions, and the website should not be used for medical diagnosis or treatment.

Limitations

In our preliminary study, we have demonstrated the potential impact AI can have in multiple aspects of patient care for emerging pathogens such as COVID-19 using a test as readily available as a CXR. However, several limitations to this investigation should be mentioned. The study is retrospective in nature with limited sample size and with X-rays from patients with various stages of COVID-19 pneumonia. Also, cases of non-COVID-19 pneumonia are not stratified into different types or etiologies. We intend to demonstrate the potential of AI in differentiating COVID-19 pneumonia from non-COVID-19 pneumonia of any etiology, though future studies should address comparison of COVID-19 cases to more specific types of pneumonias, such as of bacterial or viral origin. Furthermore, the present study does not address any potential effects of additional radiographic findings from coexistent conditions, such as pulmonary edema as seen in congestive heart failure, pleural effusions (which can be seen with COVID-19 pneumonia, though rarely), interstitial lung disease, etc. Future studies are required to address these issues. Ultimately, prospective studies to assess AI-assisted radiographic interpretation in conditions such as COVID-19 are required to demonstrate the impact on diagnosis, treatment, outcome, and patient safety as these technologies are implemented.

Conclusions

We have used a readily available, commercial platform to demonstrate the potential of AI to assist in the successful diagnosis of COVID-19 pneumonia on CXR images. While this technology has numerous applications in radiology, we have focused on the potential impact on future world health crises such as COVID-19. The findings have implications for screening and triage, initial diagnosis, monitoring disease progression, and identifying patients at increased risk of morbidity and mortality. Based on the data, a website was created to demonstrate how such technologies could be shared and distributed to others to combat entities such as COVID-19 moving forward. Our study offers a small window into the potential for how AI will likely dramatically change the practice of medicine in the future.

The first targeted therapy for patients with advanced non–small cell lung cancer (NSCLC) harboring MET mutations, capmatinib (Tabrecta), has shown deep and durable responses, conclude investigators of the pivotal trial that led to the drug’s approval.

Responses were seen in all patients regardless of how many previous drugs they had been treated with, although responses were particularly pronounced among patients who were treatment naive.

Capmatinib and a companion assay received FDA approval in May 2020 for the treatment of adults with metastatic NSCLC harboring MET exon 14–skipping mutations.

These MET mutations occur in 3%-4% of NSCLC patients. MET amplifications occur in 1%-6% of NSCLC patients. They have been associated with poor response to chemotherapy and immunotherapy.

“Prior to this approval, there weren’t any approved therapies for this group of patients,” noted Edward Garon, MD, associate professor of hematology and oncology at the University of California, Los Angeles, who led the pivotal trial.

“There are several drugs that have been used off label for MET exon 14 skipping mutations, but none with an indication for it,” he said in an interview.

Garon emphasized that capmatinib was particularly robust for patients who had not received prior therapy, although he added that it was also very effective for those who had been previously treated.

“The drug has been approved and it is available, and we have already written prescriptions for it at our clinic,” said Dr. Garon, “although, at our clinic, the majority of patients using it were part of the [pivotal] clinical trial.”

That trial is the phase 2 GEOMETRY mono-1 study. Results from the study were presented at a meeting earlier this year and have now been published in the New England Journal of Medicine.

It was conducted in a cohort of 364 patients with advanced NSCLC. Patients were stratified into five cohorts and two expansion cohorts, which were assigned according to MET status and previous lines of therapy. Across cohorts 1 through 5, a total of 97 patients had a MET exon 14–skipping mutation, and 210 had MET amplification. All patients were treated with capmatinib 400 mg twice daily.

Among patients with a MET exon 14 skipping mutation, an overall response was observed in 41% of previously treated patients and in 68% of those who had not previously been treated.

“That is a very high response rate, and clearly this drug is targeting this mutation,” said Fred Hirsch, MD, PhD, executive director, Center for Thoracic Oncology, Mount Sinai Health System, New York, who was approached for comment. “It’s very active, and you don’t get those responses with chemotherapy.”

The median duration of response was 9.7 months among previously treated patients and 12.6 months among those who were treatment naive. Median progression-free survival (PFS) was 5.4 months and 12.4 months, respectively.

In the cohort of patients with MET amplification, the overall response was 12% among those whose tumor tissue had a gene copy number of 6-9. The overall response rate was 9% among those with a gene copy number of 4 or 5, and it was 7% among those with a gene copy number of less than 4.

Median PFS was 2.7 months for patients whose tumor tissue had a gene copy number of 6-9 and in those with a gene copy number of 4 or 5. PFS rose to 3.6 months for patients with a gene copy number of less than 4.

The most frequently reported adverse events were peripheral edema (in 51%) and nausea (in 45%). These events were mostly of grade 1 or 2. Treatment-related serious adverse events occurred in 13% of patients. The incidence was lower in the groups with shorter duration of exposure. Treatment was discontinued in 11% of patients (consistent across cohorts) because of adverse events.

Dr. Hirsch commented that the results for patients with NSCLC and brain metastases were particularly noteworthy. “Brain metastases are, unfortunately, a common problem in patients with lung cancer,” he said. “Now, we have a drug that is effective for MET mutation and CNS involvement and can penetrate the blood-brain barrier, and this is a very encouraging situation.”

He pointed out that 7 of 13 patients with brain metastases responded to treatment with capmatinib. “Four patients have a complete response, and that is very encouraging,” said Dr. Hirsch. “This is clearly a deal-breaker in my opinion.”
 

The future is bright

Dr. Hirsch noted that the evidence supporting capmatinib is strong, even though a larger prospective study with a control group is lacking. “If we have a patient with this mutation, and knowing that there is a drug with a response rate of 68%, that is a good reason to try the drug up front. The data are sufficient that it should be offered to the patient, even without a control group.”

Capmatinib is the latest of many targeted drugs that have been launched in recent years, and several immunotherapies are also now available for treatment of this disease. These new therapies are making this a “very encouraging time in lung cancer,” Dr. Hirsch commented.

“We are seeing long-term survival, and, eventually, we may start seeing potential cures for some patients,” he said. “But at the very least, we are seeing very good long-term results with many of these targeted therapies, and we are continuing to learn more about resistant mechanisms. I can’t wait to see future in the field.”

The study was funded by Novartis Pharmaceuticals. Dr. Garon reports consulting or advisory roles with Dracen and research funding (institutional) from Merck, Genentech, AstraZeneca, Novartis, Lilly, Bristol-Myers Squibb, Mirati Therapeutics, Dynavax, Iovance Biotherapeutics, and Neon Therapeutics. His coauthors have disclosed numerous relationships with industry, as listed in the original article. Dr. Hirsch has disclosed no relevant financial relationships.

This article first appeared on Medscape.com.

The first targeted therapy for patients with advanced non–small cell lung cancer (NSCLC) harboring MET mutations, capmatinib (Tabrecta), has shown deep and durable responses, conclude investigators of the pivotal trial that led to the drug’s approval.

Responses were seen in all patients regardless of how many previous drugs they had been treated with, although responses were particularly pronounced among patients who were treatment naive.

Capmatinib and a companion assay received FDA approval in May 2020 for the treatment of adults with metastatic NSCLC harboring MET exon 14–skipping mutations.

These MET mutations occur in 3%-4% of NSCLC patients. MET amplifications occur in 1%-6% of NSCLC patients. They have been associated with poor response to chemotherapy and immunotherapy.

“Prior to this approval, there weren’t any approved therapies for this group of patients,” noted Edward Garon, MD, associate professor of hematology and oncology at the University of California, Los Angeles, who led the pivotal trial.

“There are several drugs that have been used off label for MET exon 14 skipping mutations, but none with an indication for it,” he said in an interview.

Garon emphasized that capmatinib was particularly robust for patients who had not received prior therapy, although he added that it was also very effective for those who had been previously treated.

“The drug has been approved and it is available, and we have already written prescriptions for it at our clinic,” said Dr. Garon, “although, at our clinic, the majority of patients using it were part of the [pivotal] clinical trial.”

That trial is the phase 2 GEOMETRY mono-1 study. Results from the study were presented at a meeting earlier this year and have now been published in the New England Journal of Medicine.

It was conducted in a cohort of 364 patients with advanced NSCLC. Patients were stratified into five cohorts and two expansion cohorts, which were assigned according to MET status and previous lines of therapy. Across cohorts 1 through 5, a total of 97 patients had a MET exon 14–skipping mutation, and 210 had MET amplification. All patients were treated with capmatinib 400 mg twice daily.

Among patients with a MET exon 14 skipping mutation, an overall response was observed in 41% of previously treated patients and in 68% of those who had not previously been treated.

“That is a very high response rate, and clearly this drug is targeting this mutation,” said Fred Hirsch, MD, PhD, executive director, Center for Thoracic Oncology, Mount Sinai Health System, New York, who was approached for comment. “It’s very active, and you don’t get those responses with chemotherapy.”

The median duration of response was 9.7 months among previously treated patients and 12.6 months among those who were treatment naive. Median progression-free survival (PFS) was 5.4 months and 12.4 months, respectively.

In the cohort of patients with MET amplification, the overall response was 12% among those whose tumor tissue had a gene copy number of 6-9. The overall response rate was 9% among those with a gene copy number of 4 or 5, and it was 7% among those with a gene copy number of less than 4.

Median PFS was 2.7 months for patients whose tumor tissue had a gene copy number of 6-9 and in those with a gene copy number of 4 or 5. PFS rose to 3.6 months for patients with a gene copy number of less than 4.

The most frequently reported adverse events were peripheral edema (in 51%) and nausea (in 45%). These events were mostly of grade 1 or 2. Treatment-related serious adverse events occurred in 13% of patients. The incidence was lower in the groups with shorter duration of exposure. Treatment was discontinued in 11% of patients (consistent across cohorts) because of adverse events.

Dr. Hirsch commented that the results for patients with NSCLC and brain metastases were particularly noteworthy. “Brain metastases are, unfortunately, a common problem in patients with lung cancer,” he said. “Now, we have a drug that is effective for MET mutation and CNS involvement and can penetrate the blood-brain barrier, and this is a very encouraging situation.”

He pointed out that 7 of 13 patients with brain metastases responded to treatment with capmatinib. “Four patients have a complete response, and that is very encouraging,” said Dr. Hirsch. “This is clearly a deal-breaker in my opinion.”
 

The future is bright

Dr. Hirsch noted that the evidence supporting capmatinib is strong, even though a larger prospective study with a control group is lacking. “If we have a patient with this mutation, and knowing that there is a drug with a response rate of 68%, that is a good reason to try the drug up front. The data are sufficient that it should be offered to the patient, even without a control group.”

Capmatinib is the latest of many targeted drugs that have been launched in recent years, and several immunotherapies are also now available for treatment of this disease. These new therapies are making this a “very encouraging time in lung cancer,” Dr. Hirsch commented.

“We are seeing long-term survival, and, eventually, we may start seeing potential cures for some patients,” he said. “But at the very least, we are seeing very good long-term results with many of these targeted therapies, and we are continuing to learn more about resistant mechanisms. I can’t wait to see future in the field.”

The study was funded by Novartis Pharmaceuticals. Dr. Garon reports consulting or advisory roles with Dracen and research funding (institutional) from Merck, Genentech, AstraZeneca, Novartis, Lilly, Bristol-Myers Squibb, Mirati Therapeutics, Dynavax, Iovance Biotherapeutics, and Neon Therapeutics. His coauthors have disclosed numerous relationships with industry, as listed in the original article. Dr. Hirsch has disclosed no relevant financial relationships.

This article first appeared on Medscape.com.

The first targeted therapy for patients with advanced non–small cell lung cancer (NSCLC) harboring MET mutations, capmatinib (Tabrecta), has shown deep and durable responses, conclude investigators of the pivotal trial that led to the drug’s approval.

Responses were seen in all patients regardless of how many previous drugs they had been treated with, although responses were particularly pronounced among patients who were treatment naive.

Capmatinib and a companion assay received FDA approval in May 2020 for the treatment of adults with metastatic NSCLC harboring MET exon 14–skipping mutations.

These MET mutations occur in 3%-4% of NSCLC patients. MET amplifications occur in 1%-6% of NSCLC patients. They have been associated with poor response to chemotherapy and immunotherapy.

“Prior to this approval, there weren’t any approved therapies for this group of patients,” noted Edward Garon, MD, associate professor of hematology and oncology at the University of California, Los Angeles, who led the pivotal trial.

“There are several drugs that have been used off label for MET exon 14 skipping mutations, but none with an indication for it,” he said in an interview.

Garon emphasized that capmatinib was particularly robust for patients who had not received prior therapy, although he added that it was also very effective for those who had been previously treated.

“The drug has been approved and it is available, and we have already written prescriptions for it at our clinic,” said Dr. Garon, “although, at our clinic, the majority of patients using it were part of the [pivotal] clinical trial.”

That trial is the phase 2 GEOMETRY mono-1 study. Results from the study were presented at a meeting earlier this year and have now been published in the New England Journal of Medicine.

It was conducted in a cohort of 364 patients with advanced NSCLC. Patients were stratified into five cohorts and two expansion cohorts, which were assigned according to MET status and previous lines of therapy. Across cohorts 1 through 5, a total of 97 patients had a MET exon 14–skipping mutation, and 210 had MET amplification. All patients were treated with capmatinib 400 mg twice daily.

Among patients with a MET exon 14 skipping mutation, an overall response was observed in 41% of previously treated patients and in 68% of those who had not previously been treated.

“That is a very high response rate, and clearly this drug is targeting this mutation,” said Fred Hirsch, MD, PhD, executive director, Center for Thoracic Oncology, Mount Sinai Health System, New York, who was approached for comment. “It’s very active, and you don’t get those responses with chemotherapy.”

The median duration of response was 9.7 months among previously treated patients and 12.6 months among those who were treatment naive. Median progression-free survival (PFS) was 5.4 months and 12.4 months, respectively.

In the cohort of patients with MET amplification, the overall response was 12% among those whose tumor tissue had a gene copy number of 6-9. The overall response rate was 9% among those with a gene copy number of 4 or 5, and it was 7% among those with a gene copy number of less than 4.

Median PFS was 2.7 months for patients whose tumor tissue had a gene copy number of 6-9 and in those with a gene copy number of 4 or 5. PFS rose to 3.6 months for patients with a gene copy number of less than 4.

The most frequently reported adverse events were peripheral edema (in 51%) and nausea (in 45%). These events were mostly of grade 1 or 2. Treatment-related serious adverse events occurred in 13% of patients. The incidence was lower in the groups with shorter duration of exposure. Treatment was discontinued in 11% of patients (consistent across cohorts) because of adverse events.

Dr. Hirsch commented that the results for patients with NSCLC and brain metastases were particularly noteworthy. “Brain metastases are, unfortunately, a common problem in patients with lung cancer,” he said. “Now, we have a drug that is effective for MET mutation and CNS involvement and can penetrate the blood-brain barrier, and this is a very encouraging situation.”

He pointed out that 7 of 13 patients with brain metastases responded to treatment with capmatinib. “Four patients have a complete response, and that is very encouraging,” said Dr. Hirsch. “This is clearly a deal-breaker in my opinion.”
 

The future is bright

Dr. Hirsch noted that the evidence supporting capmatinib is strong, even though a larger prospective study with a control group is lacking. “If we have a patient with this mutation, and knowing that there is a drug with a response rate of 68%, that is a good reason to try the drug up front. The data are sufficient that it should be offered to the patient, even without a control group.”

Capmatinib is the latest of many targeted drugs that have been launched in recent years, and several immunotherapies are also now available for treatment of this disease. These new therapies are making this a “very encouraging time in lung cancer,” Dr. Hirsch commented.

“We are seeing long-term survival, and, eventually, we may start seeing potential cures for some patients,” he said. “But at the very least, we are seeing very good long-term results with many of these targeted therapies, and we are continuing to learn more about resistant mechanisms. I can’t wait to see future in the field.”

The study was funded by Novartis Pharmaceuticals. Dr. Garon reports consulting or advisory roles with Dracen and research funding (institutional) from Merck, Genentech, AstraZeneca, Novartis, Lilly, Bristol-Myers Squibb, Mirati Therapeutics, Dynavax, Iovance Biotherapeutics, and Neon Therapeutics. His coauthors have disclosed numerous relationships with industry, as listed in the original article. Dr. Hirsch has disclosed no relevant financial relationships.

This article first appeared on Medscape.com.

A renewed effort to vaccinate service members fighting the global war on terrorism has brought new diagnostic challenges. Vaccinations not generally given to the public are routinely given to service members when they deploy to various parts of the world. Examples include anthrax, yellow fever, Japanese encephalitis, rabies, polio, and smallpox. Every vaccination has potential for adverse effects (AEs), which can range from mild to severe life-threatening complications. These AEs often go unrecognized and untreated because physicians are not routinely screening for vaccination administration.

Background

Smallpox (Variola major) was successfully eradicated in 1977 due to worldwide vaccination efforts.¹ However, the threat of bioterrorism has renewed mandatory smallpox vaccinations for high-risk individuals, such as active-duty military personnel.^1,2 A notable increase in myopericarditis has been reported with the new generation of smallpox vaccination, ACAM2000.³ We present a case of a 27-year-old healthy male who presented with chest pain and diffuse ST segment elevations consistent with myopericarditis after vaccination with ACAM2000.

Case Presentation

A healthy 27-year-old soldier presented to the emergency department with sudden, new onset, sharp-stabbing, substernal chest pain, which was made worse with lying flat and better with leaning forward. Vital signs were unremarkable. He recently enlisted in the US Army and received the smallpox vaccination about 11 days before as part of a routine predeployment checklist. The patient reported he did not have any viral symptoms, such as fever, chills, nausea, vomiting, diarrhea, shortness of breath, sore throat, rhinorrhea, or sputum production. He also reported having no prior illness for the past 3 months, sick contacts at home or work, or recent travel outside the US. He reported no tobacco use, alcohol use, or illicit drug use. The patient’s family history was negative for significant cardiac disease.

A physical examination was unremarkable. The initial laboratory report showed no leukocytosis, anemia, thrombocytopenia, electrolytes derangement, abnormal kidney function, or abnormal liver function tests. Initial troponin was 0.25 ng/mL, erythrocyte sedimentation rate (ESR) was 40 mmol/h and C-reactive protein (CRP) was 120.2 mg/L suggestive of acute inflammation. A urine drug screen was negative. D-dimer was < 0.27. An electrocardiogram (ECG) showed diffuse ST segment elevation (Figure 1). An echocardiogram showed normal left ventricle size, and function with ejection fraction 55 to 60%, normal diastolic dysfunction, and trivial pericardial effusion. Magnetic resonance imaging (MRI) showed increased T2 signal intensity of the myocardium suggestive of myopericarditis (Figure 2). A computed tomography (CT) angiogram of the coronary arteries showed no significant stenosis.

Discussion

Smallpox was a major worldwide cause of mortality; about 30% of those infected died because of smallpox.^2,4,5 Due to a worldwide vaccination effort, the World Health Organization declared smallpox was eradicated in 1977.^2,4,5 However, despite successful eradication, smallpox is considered a possible bioterrorism target, which prompted a resurgence of mandatory smallpox vaccinations for active-duty personnel.^2,5

Dryvax, a freeze-dried calf lymph smallpox vaccine was used extensively from the 1940s to the 1980s but was replaced in 2008 by ACAM2000, a smallpox vaccine cultured in kidney epithelial cells from African green monkeys.^3,5 Myopericarditis was rarely associated with the Dryvax, with only 5 cases reported from 1955 to 1986 after millions of doses of vaccines were administered; however, in 230,734 administered ACAM2000 doses, 18 cases of myopericarditis (incidence, 7.8 per 100,000) were reported during a surveillance study in 2002 and 2003.^3,5

Myopericarditis presents with a wide variety of symptoms, such as chest pain, palpitations, chills, shortness of breath, and fever.^6,7 Mainstay diagnostic criteria include ECG findings consistent with myopericarditis (such as diffuse ST segment elevations) and elevated cardiac biomarkers (elevated troponins).^5-7 An echocardiogram can be helpful in diagnosis, as most cases will not have regional wall motion abnormalities (to distinguish against coronary artery disease).^5-7 MRI with diffuse enhancement of the myocardium can be helpful in diagnosis.^5,6 The gold standard for diagnosis is an endomyocardial biopsy, which carries a significant risk of complications and is not routinely performed to diagnose myopericarditis.^5,6 US military smallpox vaccination data showed that the onset of vaccine-associated myopericarditis averaged (SD) 10.4 (3.6) days after vaccination.⁵

Vaccine-associated myopericarditis treatment is focused on decreasing inflammation.^5,6 Nonsteroidal anti-inflammatory drugs are advised for about 2 weeks with cessation of intensive cardiac activities for between 4 and 6 weeks due to risks of congestive heart failure and fatal cardiac arrhythmias.^5,6

Conclusions

Since the September 11 attacks, the US needs to be continually prepared for potential terrorism on American soil and abroad. The threat of bioterrorism has renewed efforts to vaccinate or revaccinate American service members deployed to high-risk regions. These vaccinations put them at risk for vaccination-induced complications that can range from mild fever to life-threatening complications.

A renewed effort to vaccinate service members fighting the global war on terrorism has brought new diagnostic challenges. Vaccinations not generally given to the public are routinely given to service members when they deploy to various parts of the world. Examples include anthrax, yellow fever, Japanese encephalitis, rabies, polio, and smallpox. Every vaccination has potential for adverse effects (AEs), which can range from mild to severe life-threatening complications. These AEs often go unrecognized and untreated because physicians are not routinely screening for vaccination administration.

Background

Smallpox (Variola major) was successfully eradicated in 1977 due to worldwide vaccination efforts.¹ However, the threat of bioterrorism has renewed mandatory smallpox vaccinations for high-risk individuals, such as active-duty military personnel.^1,2 A notable increase in myopericarditis has been reported with the new generation of smallpox vaccination, ACAM2000.³ We present a case of a 27-year-old healthy male who presented with chest pain and diffuse ST segment elevations consistent with myopericarditis after vaccination with ACAM2000.

Case Presentation

A healthy 27-year-old soldier presented to the emergency department with sudden, new onset, sharp-stabbing, substernal chest pain, which was made worse with lying flat and better with leaning forward. Vital signs were unremarkable. He recently enlisted in the US Army and received the smallpox vaccination about 11 days before as part of a routine predeployment checklist. The patient reported he did not have any viral symptoms, such as fever, chills, nausea, vomiting, diarrhea, shortness of breath, sore throat, rhinorrhea, or sputum production. He also reported having no prior illness for the past 3 months, sick contacts at home or work, or recent travel outside the US. He reported no tobacco use, alcohol use, or illicit drug use. The patient’s family history was negative for significant cardiac disease.

A physical examination was unremarkable. The initial laboratory report showed no leukocytosis, anemia, thrombocytopenia, electrolytes derangement, abnormal kidney function, or abnormal liver function tests. Initial troponin was 0.25 ng/mL, erythrocyte sedimentation rate (ESR) was 40 mmol/h and C-reactive protein (CRP) was 120.2 mg/L suggestive of acute inflammation. A urine drug screen was negative. D-dimer was < 0.27. An electrocardiogram (ECG) showed diffuse ST segment elevation (Figure 1). An echocardiogram showed normal left ventricle size, and function with ejection fraction 55 to 60%, normal diastolic dysfunction, and trivial pericardial effusion. Magnetic resonance imaging (MRI) showed increased T2 signal intensity of the myocardium suggestive of myopericarditis (Figure 2). A computed tomography (CT) angiogram of the coronary arteries showed no significant stenosis.

Discussion

Smallpox was a major worldwide cause of mortality; about 30% of those infected died because of smallpox.^2,4,5 Due to a worldwide vaccination effort, the World Health Organization declared smallpox was eradicated in 1977.^2,4,5 However, despite successful eradication, smallpox is considered a possible bioterrorism target, which prompted a resurgence of mandatory smallpox vaccinations for active-duty personnel.^2,5

Dryvax, a freeze-dried calf lymph smallpox vaccine was used extensively from the 1940s to the 1980s but was replaced in 2008 by ACAM2000, a smallpox vaccine cultured in kidney epithelial cells from African green monkeys.^3,5 Myopericarditis was rarely associated with the Dryvax, with only 5 cases reported from 1955 to 1986 after millions of doses of vaccines were administered; however, in 230,734 administered ACAM2000 doses, 18 cases of myopericarditis (incidence, 7.8 per 100,000) were reported during a surveillance study in 2002 and 2003.^3,5

Myopericarditis presents with a wide variety of symptoms, such as chest pain, palpitations, chills, shortness of breath, and fever.^6,7 Mainstay diagnostic criteria include ECG findings consistent with myopericarditis (such as diffuse ST segment elevations) and elevated cardiac biomarkers (elevated troponins).^5-7 An echocardiogram can be helpful in diagnosis, as most cases will not have regional wall motion abnormalities (to distinguish against coronary artery disease).^5-7 MRI with diffuse enhancement of the myocardium can be helpful in diagnosis.^5,6 The gold standard for diagnosis is an endomyocardial biopsy, which carries a significant risk of complications and is not routinely performed to diagnose myopericarditis.^5,6 US military smallpox vaccination data showed that the onset of vaccine-associated myopericarditis averaged (SD) 10.4 (3.6) days after vaccination.⁵

Vaccine-associated myopericarditis treatment is focused on decreasing inflammation.^5,6 Nonsteroidal anti-inflammatory drugs are advised for about 2 weeks with cessation of intensive cardiac activities for between 4 and 6 weeks due to risks of congestive heart failure and fatal cardiac arrhythmias.^5,6

Conclusions

Since the September 11 attacks, the US needs to be continually prepared for potential terrorism on American soil and abroad. The threat of bioterrorism has renewed efforts to vaccinate or revaccinate American service members deployed to high-risk regions. These vaccinations put them at risk for vaccination-induced complications that can range from mild fever to life-threatening complications.

A renewed effort to vaccinate service members fighting the global war on terrorism has brought new diagnostic challenges. Vaccinations not generally given to the public are routinely given to service members when they deploy to various parts of the world. Examples include anthrax, yellow fever, Japanese encephalitis, rabies, polio, and smallpox. Every vaccination has potential for adverse effects (AEs), which can range from mild to severe life-threatening complications. These AEs often go unrecognized and untreated because physicians are not routinely screening for vaccination administration.

Background

Smallpox (Variola major) was successfully eradicated in 1977 due to worldwide vaccination efforts.¹ However, the threat of bioterrorism has renewed mandatory smallpox vaccinations for high-risk individuals, such as active-duty military personnel.^1,2 A notable increase in myopericarditis has been reported with the new generation of smallpox vaccination, ACAM2000.³ We present a case of a 27-year-old healthy male who presented with chest pain and diffuse ST segment elevations consistent with myopericarditis after vaccination with ACAM2000.

Case Presentation

A healthy 27-year-old soldier presented to the emergency department with sudden, new onset, sharp-stabbing, substernal chest pain, which was made worse with lying flat and better with leaning forward. Vital signs were unremarkable. He recently enlisted in the US Army and received the smallpox vaccination about 11 days before as part of a routine predeployment checklist. The patient reported he did not have any viral symptoms, such as fever, chills, nausea, vomiting, diarrhea, shortness of breath, sore throat, rhinorrhea, or sputum production. He also reported having no prior illness for the past 3 months, sick contacts at home or work, or recent travel outside the US. He reported no tobacco use, alcohol use, or illicit drug use. The patient’s family history was negative for significant cardiac disease.

A physical examination was unremarkable. The initial laboratory report showed no leukocytosis, anemia, thrombocytopenia, electrolytes derangement, abnormal kidney function, or abnormal liver function tests. Initial troponin was 0.25 ng/mL, erythrocyte sedimentation rate (ESR) was 40 mmol/h and C-reactive protein (CRP) was 120.2 mg/L suggestive of acute inflammation. A urine drug screen was negative. D-dimer was < 0.27. An electrocardiogram (ECG) showed diffuse ST segment elevation (Figure 1). An echocardiogram showed normal left ventricle size, and function with ejection fraction 55 to 60%, normal diastolic dysfunction, and trivial pericardial effusion. Magnetic resonance imaging (MRI) showed increased T2 signal intensity of the myocardium suggestive of myopericarditis (Figure 2). A computed tomography (CT) angiogram of the coronary arteries showed no significant stenosis.

Discussion

Smallpox was a major worldwide cause of mortality; about 30% of those infected died because of smallpox.^2,4,5 Due to a worldwide vaccination effort, the World Health Organization declared smallpox was eradicated in 1977.^2,4,5 However, despite successful eradication, smallpox is considered a possible bioterrorism target, which prompted a resurgence of mandatory smallpox vaccinations for active-duty personnel.^2,5

Dryvax, a freeze-dried calf lymph smallpox vaccine was used extensively from the 1940s to the 1980s but was replaced in 2008 by ACAM2000, a smallpox vaccine cultured in kidney epithelial cells from African green monkeys.^3,5 Myopericarditis was rarely associated with the Dryvax, with only 5 cases reported from 1955 to 1986 after millions of doses of vaccines were administered; however, in 230,734 administered ACAM2000 doses, 18 cases of myopericarditis (incidence, 7.8 per 100,000) were reported during a surveillance study in 2002 and 2003.^3,5

Myopericarditis presents with a wide variety of symptoms, such as chest pain, palpitations, chills, shortness of breath, and fever.^6,7 Mainstay diagnostic criteria include ECG findings consistent with myopericarditis (such as diffuse ST segment elevations) and elevated cardiac biomarkers (elevated troponins).^5-7 An echocardiogram can be helpful in diagnosis, as most cases will not have regional wall motion abnormalities (to distinguish against coronary artery disease).^5-7 MRI with diffuse enhancement of the myocardium can be helpful in diagnosis.^5,6 The gold standard for diagnosis is an endomyocardial biopsy, which carries a significant risk of complications and is not routinely performed to diagnose myopericarditis.^5,6 US military smallpox vaccination data showed that the onset of vaccine-associated myopericarditis averaged (SD) 10.4 (3.6) days after vaccination.⁵

Vaccine-associated myopericarditis treatment is focused on decreasing inflammation.^5,6 Nonsteroidal anti-inflammatory drugs are advised for about 2 weeks with cessation of intensive cardiac activities for between 4 and 6 weeks due to risks of congestive heart failure and fatal cardiac arrhythmias.^5,6

Conclusions

Since the September 11 attacks, the US needs to be continually prepared for potential terrorism on American soil and abroad. The threat of bioterrorism has renewed efforts to vaccinate or revaccinate American service members deployed to high-risk regions. These vaccinations put them at risk for vaccination-induced complications that can range from mild fever to life-threatening complications.

Traumatic brain injury (TBI) is a major health concern that can cause significant disability as well as economic and social burden. The Centers for Disease Control and Prevention (CDC) reported a 58% increase in the number of TBI-related emergency department visits, hospitalizations, and deaths from 2006 to 2014.¹ In the CDC report, falls and motor vehicle accidents accounted for 52.3% and 20.4%, respectively, of all civilian TBI-related hospitalizations. In 2014, 56,800 TBIs in the US resulted in death. A large proportion of severe TBI survivors continue to experience long-term physical, cognitive, and psychologic disorders and require extensive rehabilitation, which may disrupt relationships and prevent return to work.² About 37% of people with mild TBI (mTBI) cases and 51% of severe cases were unable to return to previous jobs. A study examining psychosocial burden found that people with a history of TBI reported greater feelings of loneliness compared with individuals without TBI.³

Within the US military, the Defense and Veterans Brain Injury Center (DVBIC) indicates that > 417,503 service members (SMs) have been diagnosed with TBI since November 2000.⁴ Of these, 82.4% were classified as having a mTBI, or concussion (Tables 1 and 2). The nature of combat and military training to which SMs are routinely exposed may increase the risk for sustaining a TBI. Specifically, the increased use of improvised explosives devices by enemy combatants in the recent military conflicts (ie, Operation Enduring Freedom, Operation Iraqi Freedom and Operation New Dawn) resulted in TBI being recognized as the signature injury of these conflicts and brought attention to the prevalence of concussion within the US military.^5,6 In the military, the effects of concussion can decrease individual and unit effectiveness, emphasizing the importance of prompt diagnosis and proper management.⁷

Military Acute Concussion Evaluation 2

Early concussion identification and evaluation are important steps in the treatment process to ensure timely recovery and return to duty for SMs. As such, DVBIC assembled a working group of military and civilian brain injury experts to create an evidence-based clinical practice guideline for the assessment and management of concussion in a military operational setting that could be learned and effectively used by corpsmen and combat medics in the battlefield to screen for a possible concussion.⁷ This team created the first version of the MACE, a clinical tool that prompted a systematic assessment of concussion related symptoms, neurologic signs, and cognitive deficits. The cognitive assessment portion was based on the standardized assessment of concussion (SAC) that had been reported by McCrea and colleagues in 1998.¹¹ Soon after its creation, field utilization of the MACE for screening of concussion was mandated by the Army through an All Army Action (ALARACT 178/2008) and for all of the Services through the DoD Instruction (DoDI) 6490.11 published in 2014.¹²

The MACE has been updated several times since the original version. Most recently, the MACE was revised in 2018 to include a vestibular oculomotor assessment section, and red flags that immediately alert the HCP to the need for immediate triage referral and treatment of the patient possibly at a higher echelon of care or with more emergent evaluation.^13-15 Additionally, the neurologic examination was expanded to increase clarity and comprehensiveness, including speech and balance testing. Updates made to the tool were intended to provide a more thorough and informative evaluation of the SM with suspected concussion.

Description

The MACE 2 is a brief multimodal screening tool that assists medics, corpsman, and primary care managers (PCMs) in the assessment and identification of a potential concussion (Figure 1). Embedded in the MACE 2 is the Standardized Assessment of Concussion (SAC), a well-validated sports concussion tool, and the VOMS tool as portions of the 2-part cognitive examination. The entirety of the tool has 5 sections: (1) red flags; (2) acute concussion screening; (3) cognitive examination, part 1; (4) neurologic examination; and (5) cognitive examination, part 2. The end of the MACE 2 includes sections on the scoring, instructions for International Classification of Diseases, Tenth Revision, TBI coding, and next steps following completion of the MACE 2. The latest version of this screening tool impacts TBI care in several noteworthy ways. First, it broadens the scope of users by expanding use to all medically trained personnel, allowing any provider to treat SMs in the field. Second, it combines state-of-the-science advances from the research field and reflects feedback from end-users collected during the development. Last, the MACE 2 is updated as changes in the field occur, and is currently undergoing research to better identify end-user utility and usability.

Screening Tools

• Red Flags. The red flags section aids in identifying potentially serious underlying conditions in patients presenting with Glasgow Coma Scale (GCS) between 13 and 15. A positive red flag prompts the practitioner to stop administering the MACE 2 and immediately consult a higher level of care and consider urgent evacuation. While the red flags are completed first, and advancement to later sections of the MACE 2 is dependent upon the absence of red flags, the red flags should be monitored throughout the completion of the MACE 2. Upon completion of patient demographics and red flags, the remaining sections of the MACE 2 are dedicated to acute concussion screening.

• Acute Concussion Screening. The acute concussion screening portion consists of 4 sections: description of the incident; alteration of consciousness or memory; a “check all that apply” symptom inventory; and a patient history that includes concussions within the past 12 months, headache disorders, and/or behavioral health concerns. The final portion of the acute concussion screening section provides an algorithm to identify a positive or negative concussion screen. When a negative screen is identified, the user is prompted to prescribe a 24-hour rest period and follow up with the SM based on the guidance in the CMT. A positive screen warrants the user to continue administration of the MACE 2.

Neurologic and CognitiveExaminations

• Cognitive Exam Part 1. The initial cognitive examination is designed to assess orientation to time (eg, What is the day of the week, day of the month, the month, the year, and the timeof day?) as well as immediate recall of a short list of concrete words (5 words total, repeated for 3 trials). These tests are based on other neuropsychological measures designed to assess cognitive/mental status and short-term memory.

• The Neurological Exam. The neurological exam section of the MACE 2 includes brief neuropsychologic tests such as speech fluency and word finding. Other sections within the neurological exam assess the

following: grip strength, vestibular function/balance (eg, tandem gait and single leg stance), as well as motor function (eg, pronator drift), autonomic nervous system function (eg, pupil response), and vestibular function (eye-tracking).

• Cognitive Exam Part 2. After completion of the first cognitive examination and the neurologic examination, the second part of the cognitive examination is initiated. Part 2 includes measures of short-term and working memory (eg, digits-reverse tasks, listing the months in reverse order, and a delayed recall task of the short list of concrete words presented in the first part). The final assessment is the administration of the VOMS, a tool developed from the sports concussion field and designed to measure vestibular-ocular function.¹³ It is critical to note that the VOMS is contraindicated if there is concern of an unstable cervical spine or absence of a trained HCP. An examination summary provides guidance on test scoring and yields a positive or negative indication for concussive injury. A positive test refers users to guidelines listed in the Concussion Management Tool for recommendations. The final page provides coding instructions for entering the results into the patient’s electronic medical record for documentation and future reference.

Progressive Return To Activities Clinical Recommendation

The Progressive Return to Activities Clinical Recommendation (PRA CR) also was developed by DVBIC for the DoD to assist military HCPs in managing SMs with concussion by providing systematic and evidence-based guidance to both prevent extended rest and promote return to full duty as quickly and safely as clinically indicated. The general guidance is to monitor the SM at each of the 6 stages in the process and safely and gradually increase activity to the next stage as tolerated. Daily symptoms are measured using the Neurobehavioral Symptom Inventory (NSI), which SMs self-administer every morning at each stage within the process.

Prior to initiation of the progressive return to activity, SM education using the educational brochure is strongly encouraged, as previous evidence suggests that it is an effective intervention during the acute stages of injury.^10,11 Return to activity follows a 6 stage process, from stage 1 (rest) through stage 6 (unrestricted activity) (Table 4). Referral to rehabilitation providers (RPs) or higher care is left to the discretion of the PCM when (1) recovery is not progressing as anticipated; (2) progression is not being made within a 7-day period; or (3) symptoms worsen with time. The guidance outlined in the PRA CR is consistent with current policies and medical literature, and undergoes reviews as updates in the field emerge. The PRA for PCM, PRA for RP, Clinical Support Tool for PCM, Clinical Support Tool for RP, Training Slides for PCM, Training Slides for RP, Educational Brochure for PCM, and Patient Educational Tool for RP can be found on the DVBIC website (dvbic.dcoe.mil).

Description

To improve the clinical utility, 2 separate PRA CRs were developed specifically for PCMs (Figure 2) and RPs (Figure 3). The PRA CR for PCMs provides the initial framework to monitor SMs during recovery and gradually increase physical, cognitive, and vestibular/balance activities as symptoms improve in order to return to preinjury activities. The PRA CR for RPs outlines the approach for treating SMs who meet 1 of the following criteria: recovery is not progressing as anticipated, there is no progression in 7 days, symptoms are worsening, the SM is symptomatic after exertional testing following stage 5, or referral made per PCM judgment. Following the mandatory 24-hour rest period after a diagnosis of a concussion, progression through the PRA algorithm is based on history of concussion within the past 12 months (ie, 1, 2, or ≥ 3 concussions) and symptomatology, with varying treatment pathways depending on the SM’s responses to history and symptomology.

Guidelines

• One Concussion within Past 12 Months. Following the mandatory 24-hour rest period, if the SM is asymptomatic, then exertional testing (eg, activities such as push-ups, sit-ups, running in place, step aerobics, stationary bike, treadmill and/or hand crank) is performed at 65 to 85% of target heart rate for 2 minutes and symptoms are reassessed. If still asymptomatic, the SM may return to preinjury activity; however, if exertional testing provokes symptoms > 1 (mild) on the NSI, the SM should return to stage 1 with an additional 24 hours of rest. A second exertional test can be performed after stage 1, and if symptoms are provoked, progression through the remaining stages 2 to 5 is encouraged. Symptoms are continually monitored throughout each stage to determine whether the SM is recovered sufficiently to proceed to the next stage.

Concussion Management Tool

Beyond the initial assessment and concussion evaluation and the promotion of SMs’ timely return to duty, the DoD developed a tool to help endpoint users manage concussion, to include those with more protracted symptoms (Figure 4). The CMT assists HCPs and the SMs they treat in the management of symptoms before and after they return to duty. Specifically, the CMT is designed to be given in combination with guidelines issued by the DoD in the PRA CR but extends management of concussion to include those symptoms experienced more long-term, or symptoms that are not solely addressed during the timeline of the PRA CR. Together, the MACE 2, PRA CR, and the CMT provide endpoint users with a set of tools to comprehensively evaluate, treat, and manage concussions in SMs.

Description

The CMT provides step-by-step guidance for the initial and comprehensive management of concussion, once a diagnosis is made using assessments in the MACE 2. All types of HCPs, particularly those with limited training, such as Navy Hospital Corpsman and Army Combat Medics, are the intended clinical audience for the CMT. This tool was revised in 2019 to better align with the MACE 2, PRA CR, and other DVBIC CRs, and replaces the 2012 Concussion Management Algorithm and the 2014 Army Concussion Management in Garrison Setting Algorithm. The first 2 sections of the CMT are action cards, which provide management guidelines for acute injuries up to 7 days following injury and for comprehensive management beyond 1 week. Guidelines within the CMT partially overlap with those in the PRA CR; however, the PRA is designed for a more acute timeline, whereas the CMT focuses on symptom management following a more protracted recovery. The CMT clinical tool, provider training, instructor guide, and student workbook all can be found on the DVBIC website (Table 3).

Discussion

It is important for HCPs to have the skills and clinically relevant tools to optimize accurate TBI assessment. Early and accurate assessment and effective symptom management allows SMs to receive timely treatment based on clinical recommendations, and prevent and/or minimize secondary injury and prolonged recovery. Several longitudinal studies emphasize the benefits of early diagnosis and systematic follow-up.^16-18 Prompt diagnosis, patient education, and early initiation to treatment may help optimize triage to care, mitigate prolonged symptoms by educating the patient on what to expect, and target specific symptoms early.^8,10 Beyond the health outcomes of an individual SM, TBI recovery impacts unit readiness and consequently force readiness. As such, health outcomes and medical readiness are a priority of the Defense Health Agency (DHA).

The DHA priorities are, in part, based on DoD policy guidance for the management of concussion in the deployed setting. According to DoD instruction, “Medically documented mTBI/concussion in service members shall be clinically evaluated, treated, and managed according to the most current DoD clinical practice guidance for the deployed environment found in the Defense and Veterans Brain Injury Center (DVBIC) guidance, ‘Medical Providers: Clinical Tools.’”¹² In 2018, the Deputy Secretary of Defense issued a memorandum regarding the comprehensive strategy and action plan for warfighter brain health.¹² Therein, the memorandum acknowledges the enduring responsibility of the DoD to promote and protect the health and well-being of members of the nation’s armed forces. Particular emphasis was placed on issuing a response to the effects caused by concussive impacts and exposure to blast waves. This response resulted in a commitment by the DoD to understanding, preventing, diagnosing, and treating TBI in all forms. Taken together, the message from the secretary of defense and instruction from the DoD is clear and makes imperative the use of DoD clinical tools to accomplish this commitment.

Conclusion

This article showcases 3 of the DoD’s TBI clinical tools (MACE 2, PRA CR, and CMT) that assist HCPs in identifying and treating concussion. Over time, these tools undergo revisions according to the state of the science, and are adapted to meet the needs of clinicians and the SMs they treat. Studies are currently ongoing to better understand the effectiveness of these tools as well as to assist clinicians in making return-to-duty and/or medical separation decisions. These tools assist clinicians throughout the recovery process; from initial assessment and treatment (acute phase), as well as with symptom management (acute and protracted symptoms).

Concussion is not a homogenous condition and the experiences of the SM, including events that may cause emotional distress, other injuries and/or other factors, may further complicate the injury. Accordingly, there is no single clinical tool that can conclusively determine return-to-duty status; rather, these tools can help characterize injury, validate, and treat symptoms, which have been suggested to improve outcomes. More research and data are needed confirm the effectiveness of these tools to improve outcomes.

It is beyond the scope of this article to provide a more in-depth discussion on TBI prevention or longer term effects/care. However, there are additional, personalized tools for specific symptoms, deficits, or dysfunctions following concussion. These tools include the Management of Headache Following mTBI for PCM CR, Management of Sleep Disturbances Following mTBI for PCM CR, Assessment and Management of Visual Dysfunction Associated with mTBI CR, and Assessment and Management of Dizziness Associated mTBI CR. These tools enable endpoint users to evaluate and treat SMs as well as know when to elevate to higher levels of care.

The DoD commitment toward treating TBI influenced the development of the clinical tools highlighted in this article. They are the result of collective efforts among military and civilian TBI subject matter experts, data from medical literature and state-of-the-science research, and feedback from endpoint users to create the most effective, evidence-based tools. These tools undergo continuous review and revision to ensure alignment with the most up-to-date science within the field, to meet the needs of SMs and to continue the commitment to DoD concussion care.

Acknowledgments
This work was prepared under Contract (HT0014-19-C-0004) General Dynamics Information Technology and (W81XWH-16-F-0330) Credence Management Solutions, and is defined as U.S. Government work under Title 17 U.S.C.§101. Per Title 17 U.S.C.§105, copyright protection is not available for any work of the U.S. Government. For more information, please contact [email protected].

Traumatic brain injury (TBI) is a major health concern that can cause significant disability as well as economic and social burden. The Centers for Disease Control and Prevention (CDC) reported a 58% increase in the number of TBI-related emergency department visits, hospitalizations, and deaths from 2006 to 2014.¹ In the CDC report, falls and motor vehicle accidents accounted for 52.3% and 20.4%, respectively, of all civilian TBI-related hospitalizations. In 2014, 56,800 TBIs in the US resulted in death. A large proportion of severe TBI survivors continue to experience long-term physical, cognitive, and psychologic disorders and require extensive rehabilitation, which may disrupt relationships and prevent return to work.² About 37% of people with mild TBI (mTBI) cases and 51% of severe cases were unable to return to previous jobs. A study examining psychosocial burden found that people with a history of TBI reported greater feelings of loneliness compared with individuals without TBI.³

Within the US military, the Defense and Veterans Brain Injury Center (DVBIC) indicates that > 417,503 service members (SMs) have been diagnosed with TBI since November 2000.⁴ Of these, 82.4% were classified as having a mTBI, or concussion (Tables 1 and 2). The nature of combat and military training to which SMs are routinely exposed may increase the risk for sustaining a TBI. Specifically, the increased use of improvised explosives devices by enemy combatants in the recent military conflicts (ie, Operation Enduring Freedom, Operation Iraqi Freedom and Operation New Dawn) resulted in TBI being recognized as the signature injury of these conflicts and brought attention to the prevalence of concussion within the US military.^5,6 In the military, the effects of concussion can decrease individual and unit effectiveness, emphasizing the importance of prompt diagnosis and proper management.⁷

Military Acute Concussion Evaluation 2

Early concussion identification and evaluation are important steps in the treatment process to ensure timely recovery and return to duty for SMs. As such, DVBIC assembled a working group of military and civilian brain injury experts to create an evidence-based clinical practice guideline for the assessment and management of concussion in a military operational setting that could be learned and effectively used by corpsmen and combat medics in the battlefield to screen for a possible concussion.⁷ This team created the first version of the MACE, a clinical tool that prompted a systematic assessment of concussion related symptoms, neurologic signs, and cognitive deficits. The cognitive assessment portion was based on the standardized assessment of concussion (SAC) that had been reported by McCrea and colleagues in 1998.¹¹ Soon after its creation, field utilization of the MACE for screening of concussion was mandated by the Army through an All Army Action (ALARACT 178/2008) and for all of the Services through the DoD Instruction (DoDI) 6490.11 published in 2014.¹²

The MACE has been updated several times since the original version. Most recently, the MACE was revised in 2018 to include a vestibular oculomotor assessment section, and red flags that immediately alert the HCP to the need for immediate triage referral and treatment of the patient possibly at a higher echelon of care or with more emergent evaluation.^13-15 Additionally, the neurologic examination was expanded to increase clarity and comprehensiveness, including speech and balance testing. Updates made to the tool were intended to provide a more thorough and informative evaluation of the SM with suspected concussion.

Description

The MACE 2 is a brief multimodal screening tool that assists medics, corpsman, and primary care managers (PCMs) in the assessment and identification of a potential concussion (Figure 1). Embedded in the MACE 2 is the Standardized Assessment of Concussion (SAC), a well-validated sports concussion tool, and the VOMS tool as portions of the 2-part cognitive examination. The entirety of the tool has 5 sections: (1) red flags; (2) acute concussion screening; (3) cognitive examination, part 1; (4) neurologic examination; and (5) cognitive examination, part 2. The end of the MACE 2 includes sections on the scoring, instructions for International Classification of Diseases, Tenth Revision, TBI coding, and next steps following completion of the MACE 2. The latest version of this screening tool impacts TBI care in several noteworthy ways. First, it broadens the scope of users by expanding use to all medically trained personnel, allowing any provider to treat SMs in the field. Second, it combines state-of-the-science advances from the research field and reflects feedback from end-users collected during the development. Last, the MACE 2 is updated as changes in the field occur, and is currently undergoing research to better identify end-user utility and usability.

Screening Tools

• Red Flags. The red flags section aids in identifying potentially serious underlying conditions in patients presenting with Glasgow Coma Scale (GCS) between 13 and 15. A positive red flag prompts the practitioner to stop administering the MACE 2 and immediately consult a higher level of care and consider urgent evacuation. While the red flags are completed first, and advancement to later sections of the MACE 2 is dependent upon the absence of red flags, the red flags should be monitored throughout the completion of the MACE 2. Upon completion of patient demographics and red flags, the remaining sections of the MACE 2 are dedicated to acute concussion screening.

• Acute Concussion Screening. The acute concussion screening portion consists of 4 sections: description of the incident; alteration of consciousness or memory; a “check all that apply” symptom inventory; and a patient history that includes concussions within the past 12 months, headache disorders, and/or behavioral health concerns. The final portion of the acute concussion screening section provides an algorithm to identify a positive or negative concussion screen. When a negative screen is identified, the user is prompted to prescribe a 24-hour rest period and follow up with the SM based on the guidance in the CMT. A positive screen warrants the user to continue administration of the MACE 2.

Neurologic and CognitiveExaminations

• Cognitive Exam Part 1. The initial cognitive examination is designed to assess orientation to time (eg, What is the day of the week, day of the month, the month, the year, and the timeof day?) as well as immediate recall of a short list of concrete words (5 words total, repeated for 3 trials). These tests are based on other neuropsychological measures designed to assess cognitive/mental status and short-term memory.

• The Neurological Exam. The neurological exam section of the MACE 2 includes brief neuropsychologic tests such as speech fluency and word finding. Other sections within the neurological exam assess the

following: grip strength, vestibular function/balance (eg, tandem gait and single leg stance), as well as motor function (eg, pronator drift), autonomic nervous system function (eg, pupil response), and vestibular function (eye-tracking).

• Cognitive Exam Part 2. After completion of the first cognitive examination and the neurologic examination, the second part of the cognitive examination is initiated. Part 2 includes measures of short-term and working memory (eg, digits-reverse tasks, listing the months in reverse order, and a delayed recall task of the short list of concrete words presented in the first part). The final assessment is the administration of the VOMS, a tool developed from the sports concussion field and designed to measure vestibular-ocular function.¹³ It is critical to note that the VOMS is contraindicated if there is concern of an unstable cervical spine or absence of a trained HCP. An examination summary provides guidance on test scoring and yields a positive or negative indication for concussive injury. A positive test refers users to guidelines listed in the Concussion Management Tool for recommendations. The final page provides coding instructions for entering the results into the patient’s electronic medical record for documentation and future reference.

Progressive Return To Activities Clinical Recommendation

The Progressive Return to Activities Clinical Recommendation (PRA CR) also was developed by DVBIC for the DoD to assist military HCPs in managing SMs with concussion by providing systematic and evidence-based guidance to both prevent extended rest and promote return to full duty as quickly and safely as clinically indicated. The general guidance is to monitor the SM at each of the 6 stages in the process and safely and gradually increase activity to the next stage as tolerated. Daily symptoms are measured using the Neurobehavioral Symptom Inventory (NSI), which SMs self-administer every morning at each stage within the process.

Prior to initiation of the progressive return to activity, SM education using the educational brochure is strongly encouraged, as previous evidence suggests that it is an effective intervention during the acute stages of injury.^10,11 Return to activity follows a 6 stage process, from stage 1 (rest) through stage 6 (unrestricted activity) (Table 4). Referral to rehabilitation providers (RPs) or higher care is left to the discretion of the PCM when (1) recovery is not progressing as anticipated; (2) progression is not being made within a 7-day period; or (3) symptoms worsen with time. The guidance outlined in the PRA CR is consistent with current policies and medical literature, and undergoes reviews as updates in the field emerge. The PRA for PCM, PRA for RP, Clinical Support Tool for PCM, Clinical Support Tool for RP, Training Slides for PCM, Training Slides for RP, Educational Brochure for PCM, and Patient Educational Tool for RP can be found on the DVBIC website (dvbic.dcoe.mil).

Description

To improve the clinical utility, 2 separate PRA CRs were developed specifically for PCMs (Figure 2) and RPs (Figure 3). The PRA CR for PCMs provides the initial framework to monitor SMs during recovery and gradually increase physical, cognitive, and vestibular/balance activities as symptoms improve in order to return to preinjury activities. The PRA CR for RPs outlines the approach for treating SMs who meet 1 of the following criteria: recovery is not progressing as anticipated, there is no progression in 7 days, symptoms are worsening, the SM is symptomatic after exertional testing following stage 5, or referral made per PCM judgment. Following the mandatory 24-hour rest period after a diagnosis of a concussion, progression through the PRA algorithm is based on history of concussion within the past 12 months (ie, 1, 2, or ≥ 3 concussions) and symptomatology, with varying treatment pathways depending on the SM’s responses to history and symptomology.

Guidelines

• One Concussion within Past 12 Months. Following the mandatory 24-hour rest period, if the SM is asymptomatic, then exertional testing (eg, activities such as push-ups, sit-ups, running in place, step aerobics, stationary bike, treadmill and/or hand crank) is performed at 65 to 85% of target heart rate for 2 minutes and symptoms are reassessed. If still asymptomatic, the SM may return to preinjury activity; however, if exertional testing provokes symptoms > 1 (mild) on the NSI, the SM should return to stage 1 with an additional 24 hours of rest. A second exertional test can be performed after stage 1, and if symptoms are provoked, progression through the remaining stages 2 to 5 is encouraged. Symptoms are continually monitored throughout each stage to determine whether the SM is recovered sufficiently to proceed to the next stage.

Concussion Management Tool

Beyond the initial assessment and concussion evaluation and the promotion of SMs’ timely return to duty, the DoD developed a tool to help endpoint users manage concussion, to include those with more protracted symptoms (Figure 4). The CMT assists HCPs and the SMs they treat in the management of symptoms before and after they return to duty. Specifically, the CMT is designed to be given in combination with guidelines issued by the DoD in the PRA CR but extends management of concussion to include those symptoms experienced more long-term, or symptoms that are not solely addressed during the timeline of the PRA CR. Together, the MACE 2, PRA CR, and the CMT provide endpoint users with a set of tools to comprehensively evaluate, treat, and manage concussions in SMs.

Description

The CMT provides step-by-step guidance for the initial and comprehensive management of concussion, once a diagnosis is made using assessments in the MACE 2. All types of HCPs, particularly those with limited training, such as Navy Hospital Corpsman and Army Combat Medics, are the intended clinical audience for the CMT. This tool was revised in 2019 to better align with the MACE 2, PRA CR, and other DVBIC CRs, and replaces the 2012 Concussion Management Algorithm and the 2014 Army Concussion Management in Garrison Setting Algorithm. The first 2 sections of the CMT are action cards, which provide management guidelines for acute injuries up to 7 days following injury and for comprehensive management beyond 1 week. Guidelines within the CMT partially overlap with those in the PRA CR; however, the PRA is designed for a more acute timeline, whereas the CMT focuses on symptom management following a more protracted recovery. The CMT clinical tool, provider training, instructor guide, and student workbook all can be found on the DVBIC website (Table 3).

Discussion

It is important for HCPs to have the skills and clinically relevant tools to optimize accurate TBI assessment. Early and accurate assessment and effective symptom management allows SMs to receive timely treatment based on clinical recommendations, and prevent and/or minimize secondary injury and prolonged recovery. Several longitudinal studies emphasize the benefits of early diagnosis and systematic follow-up.^16-18 Prompt diagnosis, patient education, and early initiation to treatment may help optimize triage to care, mitigate prolonged symptoms by educating the patient on what to expect, and target specific symptoms early.^8,10 Beyond the health outcomes of an individual SM, TBI recovery impacts unit readiness and consequently force readiness. As such, health outcomes and medical readiness are a priority of the Defense Health Agency (DHA).

The DHA priorities are, in part, based on DoD policy guidance for the management of concussion in the deployed setting. According to DoD instruction, “Medically documented mTBI/concussion in service members shall be clinically evaluated, treated, and managed according to the most current DoD clinical practice guidance for the deployed environment found in the Defense and Veterans Brain Injury Center (DVBIC) guidance, ‘Medical Providers: Clinical Tools.’”¹² In 2018, the Deputy Secretary of Defense issued a memorandum regarding the comprehensive strategy and action plan for warfighter brain health.¹² Therein, the memorandum acknowledges the enduring responsibility of the DoD to promote and protect the health and well-being of members of the nation’s armed forces. Particular emphasis was placed on issuing a response to the effects caused by concussive impacts and exposure to blast waves. This response resulted in a commitment by the DoD to understanding, preventing, diagnosing, and treating TBI in all forms. Taken together, the message from the secretary of defense and instruction from the DoD is clear and makes imperative the use of DoD clinical tools to accomplish this commitment.

Conclusion

This article showcases 3 of the DoD’s TBI clinical tools (MACE 2, PRA CR, and CMT) that assist HCPs in identifying and treating concussion. Over time, these tools undergo revisions according to the state of the science, and are adapted to meet the needs of clinicians and the SMs they treat. Studies are currently ongoing to better understand the effectiveness of these tools as well as to assist clinicians in making return-to-duty and/or medical separation decisions. These tools assist clinicians throughout the recovery process; from initial assessment and treatment (acute phase), as well as with symptom management (acute and protracted symptoms).

Concussion is not a homogenous condition and the experiences of the SM, including events that may cause emotional distress, other injuries and/or other factors, may further complicate the injury. Accordingly, there is no single clinical tool that can conclusively determine return-to-duty status; rather, these tools can help characterize injury, validate, and treat symptoms, which have been suggested to improve outcomes. More research and data are needed confirm the effectiveness of these tools to improve outcomes.

It is beyond the scope of this article to provide a more in-depth discussion on TBI prevention or longer term effects/care. However, there are additional, personalized tools for specific symptoms, deficits, or dysfunctions following concussion. These tools include the Management of Headache Following mTBI for PCM CR, Management of Sleep Disturbances Following mTBI for PCM CR, Assessment and Management of Visual Dysfunction Associated with mTBI CR, and Assessment and Management of Dizziness Associated mTBI CR. These tools enable endpoint users to evaluate and treat SMs as well as know when to elevate to higher levels of care.

The DoD commitment toward treating TBI influenced the development of the clinical tools highlighted in this article. They are the result of collective efforts among military and civilian TBI subject matter experts, data from medical literature and state-of-the-science research, and feedback from endpoint users to create the most effective, evidence-based tools. These tools undergo continuous review and revision to ensure alignment with the most up-to-date science within the field, to meet the needs of SMs and to continue the commitment to DoD concussion care.

Acknowledgments
This work was prepared under Contract (HT0014-19-C-0004) General Dynamics Information Technology and (W81XWH-16-F-0330) Credence Management Solutions, and is defined as U.S. Government work under Title 17 U.S.C.§101. Per Title 17 U.S.C.§105, copyright protection is not available for any work of the U.S. Government. For more information, please contact [email protected].

Traumatic brain injury (TBI) is a major health concern that can cause significant disability as well as economic and social burden. The Centers for Disease Control and Prevention (CDC) reported a 58% increase in the number of TBI-related emergency department visits, hospitalizations, and deaths from 2006 to 2014.¹ In the CDC report, falls and motor vehicle accidents accounted for 52.3% and 20.4%, respectively, of all civilian TBI-related hospitalizations. In 2014, 56,800 TBIs in the US resulted in death. A large proportion of severe TBI survivors continue to experience long-term physical, cognitive, and psychologic disorders and require extensive rehabilitation, which may disrupt relationships and prevent return to work.² About 37% of people with mild TBI (mTBI) cases and 51% of severe cases were unable to return to previous jobs. A study examining psychosocial burden found that people with a history of TBI reported greater feelings of loneliness compared with individuals without TBI.³

Within the US military, the Defense and Veterans Brain Injury Center (DVBIC) indicates that > 417,503 service members (SMs) have been diagnosed with TBI since November 2000.⁴ Of these, 82.4% were classified as having a mTBI, or concussion (Tables 1 and 2). The nature of combat and military training to which SMs are routinely exposed may increase the risk for sustaining a TBI. Specifically, the increased use of improvised explosives devices by enemy combatants in the recent military conflicts (ie, Operation Enduring Freedom, Operation Iraqi Freedom and Operation New Dawn) resulted in TBI being recognized as the signature injury of these conflicts and brought attention to the prevalence of concussion within the US military.^5,6 In the military, the effects of concussion can decrease individual and unit effectiveness, emphasizing the importance of prompt diagnosis and proper management.⁷

Military Acute Concussion Evaluation 2

Early concussion identification and evaluation are important steps in the treatment process to ensure timely recovery and return to duty for SMs. As such, DVBIC assembled a working group of military and civilian brain injury experts to create an evidence-based clinical practice guideline for the assessment and management of concussion in a military operational setting that could be learned and effectively used by corpsmen and combat medics in the battlefield to screen for a possible concussion.⁷ This team created the first version of the MACE, a clinical tool that prompted a systematic assessment of concussion related symptoms, neurologic signs, and cognitive deficits. The cognitive assessment portion was based on the standardized assessment of concussion (SAC) that had been reported by McCrea and colleagues in 1998.¹¹ Soon after its creation, field utilization of the MACE for screening of concussion was mandated by the Army through an All Army Action (ALARACT 178/2008) and for all of the Services through the DoD Instruction (DoDI) 6490.11 published in 2014.¹²

The MACE has been updated several times since the original version. Most recently, the MACE was revised in 2018 to include a vestibular oculomotor assessment section, and red flags that immediately alert the HCP to the need for immediate triage referral and treatment of the patient possibly at a higher echelon of care or with more emergent evaluation.^13-15 Additionally, the neurologic examination was expanded to increase clarity and comprehensiveness, including speech and balance testing. Updates made to the tool were intended to provide a more thorough and informative evaluation of the SM with suspected concussion.

Description

The MACE 2 is a brief multimodal screening tool that assists medics, corpsman, and primary care managers (PCMs) in the assessment and identification of a potential concussion (Figure 1). Embedded in the MACE 2 is the Standardized Assessment of Concussion (SAC), a well-validated sports concussion tool, and the VOMS tool as portions of the 2-part cognitive examination. The entirety of the tool has 5 sections: (1) red flags; (2) acute concussion screening; (3) cognitive examination, part 1; (4) neurologic examination; and (5) cognitive examination, part 2. The end of the MACE 2 includes sections on the scoring, instructions for International Classification of Diseases, Tenth Revision, TBI coding, and next steps following completion of the MACE 2. The latest version of this screening tool impacts TBI care in several noteworthy ways. First, it broadens the scope of users by expanding use to all medically trained personnel, allowing any provider to treat SMs in the field. Second, it combines state-of-the-science advances from the research field and reflects feedback from end-users collected during the development. Last, the MACE 2 is updated as changes in the field occur, and is currently undergoing research to better identify end-user utility and usability.

Screening Tools

• Red Flags. The red flags section aids in identifying potentially serious underlying conditions in patients presenting with Glasgow Coma Scale (GCS) between 13 and 15. A positive red flag prompts the practitioner to stop administering the MACE 2 and immediately consult a higher level of care and consider urgent evacuation. While the red flags are completed first, and advancement to later sections of the MACE 2 is dependent upon the absence of red flags, the red flags should be monitored throughout the completion of the MACE 2. Upon completion of patient demographics and red flags, the remaining sections of the MACE 2 are dedicated to acute concussion screening.

• Acute Concussion Screening. The acute concussion screening portion consists of 4 sections: description of the incident; alteration of consciousness or memory; a “check all that apply” symptom inventory; and a patient history that includes concussions within the past 12 months, headache disorders, and/or behavioral health concerns. The final portion of the acute concussion screening section provides an algorithm to identify a positive or negative concussion screen. When a negative screen is identified, the user is prompted to prescribe a 24-hour rest period and follow up with the SM based on the guidance in the CMT. A positive screen warrants the user to continue administration of the MACE 2.

Neurologic and CognitiveExaminations

• Cognitive Exam Part 1. The initial cognitive examination is designed to assess orientation to time (eg, What is the day of the week, day of the month, the month, the year, and the timeof day?) as well as immediate recall of a short list of concrete words (5 words total, repeated for 3 trials). These tests are based on other neuropsychological measures designed to assess cognitive/mental status and short-term memory.

• The Neurological Exam. The neurological exam section of the MACE 2 includes brief neuropsychologic tests such as speech fluency and word finding. Other sections within the neurological exam assess the

following: grip strength, vestibular function/balance (eg, tandem gait and single leg stance), as well as motor function (eg, pronator drift), autonomic nervous system function (eg, pupil response), and vestibular function (eye-tracking).

• Cognitive Exam Part 2. After completion of the first cognitive examination and the neurologic examination, the second part of the cognitive examination is initiated. Part 2 includes measures of short-term and working memory (eg, digits-reverse tasks, listing the months in reverse order, and a delayed recall task of the short list of concrete words presented in the first part). The final assessment is the administration of the VOMS, a tool developed from the sports concussion field and designed to measure vestibular-ocular function.¹³ It is critical to note that the VOMS is contraindicated if there is concern of an unstable cervical spine or absence of a trained HCP. An examination summary provides guidance on test scoring and yields a positive or negative indication for concussive injury. A positive test refers users to guidelines listed in the Concussion Management Tool for recommendations. The final page provides coding instructions for entering the results into the patient’s electronic medical record for documentation and future reference.

Progressive Return To Activities Clinical Recommendation

The Progressive Return to Activities Clinical Recommendation (PRA CR) also was developed by DVBIC for the DoD to assist military HCPs in managing SMs with concussion by providing systematic and evidence-based guidance to both prevent extended rest and promote return to full duty as quickly and safely as clinically indicated. The general guidance is to monitor the SM at each of the 6 stages in the process and safely and gradually increase activity to the next stage as tolerated. Daily symptoms are measured using the Neurobehavioral Symptom Inventory (NSI), which SMs self-administer every morning at each stage within the process.

Prior to initiation of the progressive return to activity, SM education using the educational brochure is strongly encouraged, as previous evidence suggests that it is an effective intervention during the acute stages of injury.^10,11 Return to activity follows a 6 stage process, from stage 1 (rest) through stage 6 (unrestricted activity) (Table 4). Referral to rehabilitation providers (RPs) or higher care is left to the discretion of the PCM when (1) recovery is not progressing as anticipated; (2) progression is not being made within a 7-day period; or (3) symptoms worsen with time. The guidance outlined in the PRA CR is consistent with current policies and medical literature, and undergoes reviews as updates in the field emerge. The PRA for PCM, PRA for RP, Clinical Support Tool for PCM, Clinical Support Tool for RP, Training Slides for PCM, Training Slides for RP, Educational Brochure for PCM, and Patient Educational Tool for RP can be found on the DVBIC website (dvbic.dcoe.mil).

Description

To improve the clinical utility, 2 separate PRA CRs were developed specifically for PCMs (Figure 2) and RPs (Figure 3). The PRA CR for PCMs provides the initial framework to monitor SMs during recovery and gradually increase physical, cognitive, and vestibular/balance activities as symptoms improve in order to return to preinjury activities. The PRA CR for RPs outlines the approach for treating SMs who meet 1 of the following criteria: recovery is not progressing as anticipated, there is no progression in 7 days, symptoms are worsening, the SM is symptomatic after exertional testing following stage 5, or referral made per PCM judgment. Following the mandatory 24-hour rest period after a diagnosis of a concussion, progression through the PRA algorithm is based on history of concussion within the past 12 months (ie, 1, 2, or ≥ 3 concussions) and symptomatology, with varying treatment pathways depending on the SM’s responses to history and symptomology.

Guidelines

• One Concussion within Past 12 Months. Following the mandatory 24-hour rest period, if the SM is asymptomatic, then exertional testing (eg, activities such as push-ups, sit-ups, running in place, step aerobics, stationary bike, treadmill and/or hand crank) is performed at 65 to 85% of target heart rate for 2 minutes and symptoms are reassessed. If still asymptomatic, the SM may return to preinjury activity; however, if exertional testing provokes symptoms > 1 (mild) on the NSI, the SM should return to stage 1 with an additional 24 hours of rest. A second exertional test can be performed after stage 1, and if symptoms are provoked, progression through the remaining stages 2 to 5 is encouraged. Symptoms are continually monitored throughout each stage to determine whether the SM is recovered sufficiently to proceed to the next stage.

Concussion Management Tool

Beyond the initial assessment and concussion evaluation and the promotion of SMs’ timely return to duty, the DoD developed a tool to help endpoint users manage concussion, to include those with more protracted symptoms (Figure 4). The CMT assists HCPs and the SMs they treat in the management of symptoms before and after they return to duty. Specifically, the CMT is designed to be given in combination with guidelines issued by the DoD in the PRA CR but extends management of concussion to include those symptoms experienced more long-term, or symptoms that are not solely addressed during the timeline of the PRA CR. Together, the MACE 2, PRA CR, and the CMT provide endpoint users with a set of tools to comprehensively evaluate, treat, and manage concussions in SMs.

Description

The CMT provides step-by-step guidance for the initial and comprehensive management of concussion, once a diagnosis is made using assessments in the MACE 2. All types of HCPs, particularly those with limited training, such as Navy Hospital Corpsman and Army Combat Medics, are the intended clinical audience for the CMT. This tool was revised in 2019 to better align with the MACE 2, PRA CR, and other DVBIC CRs, and replaces the 2012 Concussion Management Algorithm and the 2014 Army Concussion Management in Garrison Setting Algorithm. The first 2 sections of the CMT are action cards, which provide management guidelines for acute injuries up to 7 days following injury and for comprehensive management beyond 1 week. Guidelines within the CMT partially overlap with those in the PRA CR; however, the PRA is designed for a more acute timeline, whereas the CMT focuses on symptom management following a more protracted recovery. The CMT clinical tool, provider training, instructor guide, and student workbook all can be found on the DVBIC website (Table 3).

Discussion

It is important for HCPs to have the skills and clinically relevant tools to optimize accurate TBI assessment. Early and accurate assessment and effective symptom management allows SMs to receive timely treatment based on clinical recommendations, and prevent and/or minimize secondary injury and prolonged recovery. Several longitudinal studies emphasize the benefits of early diagnosis and systematic follow-up.^16-18 Prompt diagnosis, patient education, and early initiation to treatment may help optimize triage to care, mitigate prolonged symptoms by educating the patient on what to expect, and target specific symptoms early.^8,10 Beyond the health outcomes of an individual SM, TBI recovery impacts unit readiness and consequently force readiness. As such, health outcomes and medical readiness are a priority of the Defense Health Agency (DHA).

The DHA priorities are, in part, based on DoD policy guidance for the management of concussion in the deployed setting. According to DoD instruction, “Medically documented mTBI/concussion in service members shall be clinically evaluated, treated, and managed according to the most current DoD clinical practice guidance for the deployed environment found in the Defense and Veterans Brain Injury Center (DVBIC) guidance, ‘Medical Providers: Clinical Tools.’”¹² In 2018, the Deputy Secretary of Defense issued a memorandum regarding the comprehensive strategy and action plan for warfighter brain health.¹² Therein, the memorandum acknowledges the enduring responsibility of the DoD to promote and protect the health and well-being of members of the nation’s armed forces. Particular emphasis was placed on issuing a response to the effects caused by concussive impacts and exposure to blast waves. This response resulted in a commitment by the DoD to understanding, preventing, diagnosing, and treating TBI in all forms. Taken together, the message from the secretary of defense and instruction from the DoD is clear and makes imperative the use of DoD clinical tools to accomplish this commitment.

Conclusion

This article showcases 3 of the DoD’s TBI clinical tools (MACE 2, PRA CR, and CMT) that assist HCPs in identifying and treating concussion. Over time, these tools undergo revisions according to the state of the science, and are adapted to meet the needs of clinicians and the SMs they treat. Studies are currently ongoing to better understand the effectiveness of these tools as well as to assist clinicians in making return-to-duty and/or medical separation decisions. These tools assist clinicians throughout the recovery process; from initial assessment and treatment (acute phase), as well as with symptom management (acute and protracted symptoms).

Concussion is not a homogenous condition and the experiences of the SM, including events that may cause emotional distress, other injuries and/or other factors, may further complicate the injury. Accordingly, there is no single clinical tool that can conclusively determine return-to-duty status; rather, these tools can help characterize injury, validate, and treat symptoms, which have been suggested to improve outcomes. More research and data are needed confirm the effectiveness of these tools to improve outcomes.

It is beyond the scope of this article to provide a more in-depth discussion on TBI prevention or longer term effects/care. However, there are additional, personalized tools for specific symptoms, deficits, or dysfunctions following concussion. These tools include the Management of Headache Following mTBI for PCM CR, Management of Sleep Disturbances Following mTBI for PCM CR, Assessment and Management of Visual Dysfunction Associated with mTBI CR, and Assessment and Management of Dizziness Associated mTBI CR. These tools enable endpoint users to evaluate and treat SMs as well as know when to elevate to higher levels of care.

The DoD commitment toward treating TBI influenced the development of the clinical tools highlighted in this article. They are the result of collective efforts among military and civilian TBI subject matter experts, data from medical literature and state-of-the-science research, and feedback from endpoint users to create the most effective, evidence-based tools. These tools undergo continuous review and revision to ensure alignment with the most up-to-date science within the field, to meet the needs of SMs and to continue the commitment to DoD concussion care.

Acknowledgments
This work was prepared under Contract (HT0014-19-C-0004) General Dynamics Information Technology and (W81XWH-16-F-0330) Credence Management Solutions, and is defined as U.S. Government work under Title 17 U.S.C.§101. Per Title 17 U.S.C.§105, copyright protection is not available for any work of the U.S. Government. For more information, please contact [email protected].

Knowing that I am a psychiatrist, my friends and colleagues recently started to ask me, “Am I losing my mind?” The symptoms underlying these concerned queries are remarkably similar: inability to concentrate, becoming easily frustrated, forgetting things, not being as productive as usual, being overly tired despite doing less, and feeling unusually irritable, among other vague somatic symptoms. This condition is to be distinguished from COVID-19 in the brain, which is the protean serious neuropsychiatric manifestations of infection with the virus ranging from strokes and seizures to encephalopathy and psychosis especially in severe cases of infection.¹

As federal health care professionals (HCPs), many of us are familiar with acute high stress medical situations, which the pandemic has expanded and intensified: In New York City during the surge, the US Department of Veterans Affairs (VA) intensive care physician pushing life-sustaining resources to their limits in a valiant effort to keep alive as many people as possible; the US Public Health Service HCP working miracles without adequate supplies or staff in underserved hard-hit areas of the country; or the US Department of Defense clinician deftly trying to contain outbreaks in contained spaces like ships.

Emerging data already show that HCPs and other first responders facing these repeated episodes of acute stress are experiencing increased depression and anxiety.² Research from prior pandemics suggests that this is only the beginning of a wave of negative mental health complications in HCPs.³

In the acute form of stress, the hypothalamic pituitary axis (HPA axis) is an evolutionary engine that coordinates multiple organ systems from lungs to liver to ensure efficient escape from primeval dinosaurs or more modern threats like viruses. Fueling that engine is the hormonal cascade that ends in excessive secretion of cortisol.

Chronic stress affects the body and brain in a different way than does acute stress. The problem is that this sympathetic nervous system surge is meant to power a sprint to survival not the marathon of uncertainty that COVID-19 has become. As long as the body stays in acute stress mode, the brain cannot downshift to the parasympathetic system that would usually moderate and regulate our neurobiologic circuits and neuropsychological processes. Like any other engine in overdrive, the stress gear erodes the machinery of our body and brain. Hence, the symptoms of psychophysical wear and tear—allostatic load—that most of us are experiencing.⁴

The subject of this column is the lower level of prolonged chronic stress. The mild and amorphous pertubations that can be described as “the brain in COVID-19.” It is a syndrome that affects even those who have never been infected with the actual virus. Though not usually life-threatening or disabling, it is unnerving and distressing as the queries from my colleagues and friends show. Their reports and my observations have led me to opine that “no one is okay” due to months of living under the strain of a pandemic.

The degree and scope of chronic stress that a person experiences caused by COVID-19 has to be contextualized and individualized. Those who have lost jobs, who are working while children are going to school online, who are caring for relatives, or who are in fear of losing their home face tremendous stress and challenges.⁵ Yet even those like me, whose biggest worry is a dog barking through important teleconference meetings, still undergo a milder form of near constant stress.

Consider that all of us have become strangers in an even stranger land. Masks have become an object of political controversy. In states where masking is mandatory, you must be mask vigilant every time you go out. In many areas of the country stores have limited hours, access, and supplies and any trip away from the house risks infection. Conversely, for those in a high-risk population, it may have been months since they have left home at all, and many sick, older, and vulnerable persons are suffering from isolation, loneliness, and boredom. The minor distractions and innocent pleasures that relieve day-to-day stress are no longer safe or available options, like eating out, attending shows, or taking trips.

Most of us are waiting for news of an effective available vaccine, some with yearning and others with dread. For George Gershwin, summertime meant that “the livin’ is easy,” but the summer of 2020 has been anything but easy and that takes its toll on the mind. Without adequate positive stimulation, attention wanders and memory fails to encode details, making even routine tasks more difficult; without meaningful social contact, emotions become sharp and ragged often hurting others. Most important, without periods in which we can relax, there is psychic exhaustion.⁶

At this point you may be thinking, “So, now that you told us we are all under chronic stress, are you going to tell us whether we can do anything about it?” There are many fantastic websites (including the VA) where experts far more qualified than I am offer excellent advice on coping with the pandemic.⁷ What I can provide is 5 reflections on managing the stress that I have used and that others with whom I shared them have found helpful.

1. Set realistic expectations. We are in a different reality in which we may need to take on smaller tasks, pace our work and take more breaks and, most of all, give ourselves a break when we are not as functional as we were before the pandemic.

2. Get out in nature. Find a green space to walk or sit, spend time with companion animals, go for a hike or bicycle near water or mountains, or watch the birds in a forest. Nothing can help restore our perspective or calm frayed nerves like the socially distanced outdoors.

3. Reach out. Even though we cannot hug or even shake hands, we can still pick up the phone or mouse and check on someone who is down. All the great traditions of the world agree that the best way to lift our own spirits is to help others.

4. Be kind. This is among the most important responses. As the epigraph suggests, everyone is engaged in an often silent and secret struggle and deserves our compassion. This call for kindness should be extended to ourselves so that we can be patient and compassionate to others.

5. Have courage and hope. This may be the most important of all. Whether we are infected or are fearing/avoiding infection, COVID-19 makes us sick in body and brain. We must have faith that there is something—the mind, the spirit—beyond the purely physical that gives us courage to outlast COVID-19 and to have hope for a postpandemic future that though not the same as before may well be in some ways better

Knowing that I am a psychiatrist, my friends and colleagues recently started to ask me, “Am I losing my mind?” The symptoms underlying these concerned queries are remarkably similar: inability to concentrate, becoming easily frustrated, forgetting things, not being as productive as usual, being overly tired despite doing less, and feeling unusually irritable, among other vague somatic symptoms. This condition is to be distinguished from COVID-19 in the brain, which is the protean serious neuropsychiatric manifestations of infection with the virus ranging from strokes and seizures to encephalopathy and psychosis especially in severe cases of infection.¹

As federal health care professionals (HCPs), many of us are familiar with acute high stress medical situations, which the pandemic has expanded and intensified: In New York City during the surge, the US Department of Veterans Affairs (VA) intensive care physician pushing life-sustaining resources to their limits in a valiant effort to keep alive as many people as possible; the US Public Health Service HCP working miracles without adequate supplies or staff in underserved hard-hit areas of the country; or the US Department of Defense clinician deftly trying to contain outbreaks in contained spaces like ships.

Emerging data already show that HCPs and other first responders facing these repeated episodes of acute stress are experiencing increased depression and anxiety.² Research from prior pandemics suggests that this is only the beginning of a wave of negative mental health complications in HCPs.³

In the acute form of stress, the hypothalamic pituitary axis (HPA axis) is an evolutionary engine that coordinates multiple organ systems from lungs to liver to ensure efficient escape from primeval dinosaurs or more modern threats like viruses. Fueling that engine is the hormonal cascade that ends in excessive secretion of cortisol.

Chronic stress affects the body and brain in a different way than does acute stress. The problem is that this sympathetic nervous system surge is meant to power a sprint to survival not the marathon of uncertainty that COVID-19 has become. As long as the body stays in acute stress mode, the brain cannot downshift to the parasympathetic system that would usually moderate and regulate our neurobiologic circuits and neuropsychological processes. Like any other engine in overdrive, the stress gear erodes the machinery of our body and brain. Hence, the symptoms of psychophysical wear and tear—allostatic load—that most of us are experiencing.⁴

The subject of this column is the lower level of prolonged chronic stress. The mild and amorphous pertubations that can be described as “the brain in COVID-19.” It is a syndrome that affects even those who have never been infected with the actual virus. Though not usually life-threatening or disabling, it is unnerving and distressing as the queries from my colleagues and friends show. Their reports and my observations have led me to opine that “no one is okay” due to months of living under the strain of a pandemic.

The degree and scope of chronic stress that a person experiences caused by COVID-19 has to be contextualized and individualized. Those who have lost jobs, who are working while children are going to school online, who are caring for relatives, or who are in fear of losing their home face tremendous stress and challenges.⁵ Yet even those like me, whose biggest worry is a dog barking through important teleconference meetings, still undergo a milder form of near constant stress.

Consider that all of us have become strangers in an even stranger land. Masks have become an object of political controversy. In states where masking is mandatory, you must be mask vigilant every time you go out. In many areas of the country stores have limited hours, access, and supplies and any trip away from the house risks infection. Conversely, for those in a high-risk population, it may have been months since they have left home at all, and many sick, older, and vulnerable persons are suffering from isolation, loneliness, and boredom. The minor distractions and innocent pleasures that relieve day-to-day stress are no longer safe or available options, like eating out, attending shows, or taking trips.

Most of us are waiting for news of an effective available vaccine, some with yearning and others with dread. For George Gershwin, summertime meant that “the livin’ is easy,” but the summer of 2020 has been anything but easy and that takes its toll on the mind. Without adequate positive stimulation, attention wanders and memory fails to encode details, making even routine tasks more difficult; without meaningful social contact, emotions become sharp and ragged often hurting others. Most important, without periods in which we can relax, there is psychic exhaustion.⁶

At this point you may be thinking, “So, now that you told us we are all under chronic stress, are you going to tell us whether we can do anything about it?” There are many fantastic websites (including the VA) where experts far more qualified than I am offer excellent advice on coping with the pandemic.⁷ What I can provide is 5 reflections on managing the stress that I have used and that others with whom I shared them have found helpful.

1. Set realistic expectations. We are in a different reality in which we may need to take on smaller tasks, pace our work and take more breaks and, most of all, give ourselves a break when we are not as functional as we were before the pandemic.

2. Get out in nature. Find a green space to walk or sit, spend time with companion animals, go for a hike or bicycle near water or mountains, or watch the birds in a forest. Nothing can help restore our perspective or calm frayed nerves like the socially distanced outdoors.

3. Reach out. Even though we cannot hug or even shake hands, we can still pick up the phone or mouse and check on someone who is down. All the great traditions of the world agree that the best way to lift our own spirits is to help others.

4. Be kind. This is among the most important responses. As the epigraph suggests, everyone is engaged in an often silent and secret struggle and deserves our compassion. This call for kindness should be extended to ourselves so that we can be patient and compassionate to others.

5. Have courage and hope. This may be the most important of all. Whether we are infected or are fearing/avoiding infection, COVID-19 makes us sick in body and brain. We must have faith that there is something—the mind, the spirit—beyond the purely physical that gives us courage to outlast COVID-19 and to have hope for a postpandemic future that though not the same as before may well be in some ways better

Knowing that I am a psychiatrist, my friends and colleagues recently started to ask me, “Am I losing my mind?” The symptoms underlying these concerned queries are remarkably similar: inability to concentrate, becoming easily frustrated, forgetting things, not being as productive as usual, being overly tired despite doing less, and feeling unusually irritable, among other vague somatic symptoms. This condition is to be distinguished from COVID-19 in the brain, which is the protean serious neuropsychiatric manifestations of infection with the virus ranging from strokes and seizures to encephalopathy and psychosis especially in severe cases of infection.¹

As federal health care professionals (HCPs), many of us are familiar with acute high stress medical situations, which the pandemic has expanded and intensified: In New York City during the surge, the US Department of Veterans Affairs (VA) intensive care physician pushing life-sustaining resources to their limits in a valiant effort to keep alive as many people as possible; the US Public Health Service HCP working miracles without adequate supplies or staff in underserved hard-hit areas of the country; or the US Department of Defense clinician deftly trying to contain outbreaks in contained spaces like ships.

Emerging data already show that HCPs and other first responders facing these repeated episodes of acute stress are experiencing increased depression and anxiety.² Research from prior pandemics suggests that this is only the beginning of a wave of negative mental health complications in HCPs.³

In the acute form of stress, the hypothalamic pituitary axis (HPA axis) is an evolutionary engine that coordinates multiple organ systems from lungs to liver to ensure efficient escape from primeval dinosaurs or more modern threats like viruses. Fueling that engine is the hormonal cascade that ends in excessive secretion of cortisol.

Chronic stress affects the body and brain in a different way than does acute stress. The problem is that this sympathetic nervous system surge is meant to power a sprint to survival not the marathon of uncertainty that COVID-19 has become. As long as the body stays in acute stress mode, the brain cannot downshift to the parasympathetic system that would usually moderate and regulate our neurobiologic circuits and neuropsychological processes. Like any other engine in overdrive, the stress gear erodes the machinery of our body and brain. Hence, the symptoms of psychophysical wear and tear—allostatic load—that most of us are experiencing.⁴

The subject of this column is the lower level of prolonged chronic stress. The mild and amorphous pertubations that can be described as “the brain in COVID-19.” It is a syndrome that affects even those who have never been infected with the actual virus. Though not usually life-threatening or disabling, it is unnerving and distressing as the queries from my colleagues and friends show. Their reports and my observations have led me to opine that “no one is okay” due to months of living under the strain of a pandemic.

The degree and scope of chronic stress that a person experiences caused by COVID-19 has to be contextualized and individualized. Those who have lost jobs, who are working while children are going to school online, who are caring for relatives, or who are in fear of losing their home face tremendous stress and challenges.⁵ Yet even those like me, whose biggest worry is a dog barking through important teleconference meetings, still undergo a milder form of near constant stress.

Consider that all of us have become strangers in an even stranger land. Masks have become an object of political controversy. In states where masking is mandatory, you must be mask vigilant every time you go out. In many areas of the country stores have limited hours, access, and supplies and any trip away from the house risks infection. Conversely, for those in a high-risk population, it may have been months since they have left home at all, and many sick, older, and vulnerable persons are suffering from isolation, loneliness, and boredom. The minor distractions and innocent pleasures that relieve day-to-day stress are no longer safe or available options, like eating out, attending shows, or taking trips.

Most of us are waiting for news of an effective available vaccine, some with yearning and others with dread. For George Gershwin, summertime meant that “the livin’ is easy,” but the summer of 2020 has been anything but easy and that takes its toll on the mind. Without adequate positive stimulation, attention wanders and memory fails to encode details, making even routine tasks more difficult; without meaningful social contact, emotions become sharp and ragged often hurting others. Most important, without periods in which we can relax, there is psychic exhaustion.⁶

At this point you may be thinking, “So, now that you told us we are all under chronic stress, are you going to tell us whether we can do anything about it?” There are many fantastic websites (including the VA) where experts far more qualified than I am offer excellent advice on coping with the pandemic.⁷ What I can provide is 5 reflections on managing the stress that I have used and that others with whom I shared them have found helpful.

1. Set realistic expectations. We are in a different reality in which we may need to take on smaller tasks, pace our work and take more breaks and, most of all, give ourselves a break when we are not as functional as we were before the pandemic.

2. Get out in nature. Find a green space to walk or sit, spend time with companion animals, go for a hike or bicycle near water or mountains, or watch the birds in a forest. Nothing can help restore our perspective or calm frayed nerves like the socially distanced outdoors.

3. Reach out. Even though we cannot hug or even shake hands, we can still pick up the phone or mouse and check on someone who is down. All the great traditions of the world agree that the best way to lift our own spirits is to help others.

4. Be kind. This is among the most important responses. As the epigraph suggests, everyone is engaged in an often silent and secret struggle and deserves our compassion. This call for kindness should be extended to ourselves so that we can be patient and compassionate to others.

5. Have courage and hope. This may be the most important of all. Whether we are infected or are fearing/avoiding infection, COVID-19 makes us sick in body and brain. We must have faith that there is something—the mind, the spirit—beyond the purely physical that gives us courage to outlast COVID-19 and to have hope for a postpandemic future that though not the same as before may well be in some ways better

Women are more than twice as likely as men to use antidepressants, and use among White women is at least double that of other races/ethnicities, according to a new analysis from the National Center for Health Statistics.

Here are the actual numbers: 17.7% of women and 8.4% of men used an antidepressant in the 30 days before being interviewed for the National Health and Nutrition Examination Survey (NHANES). Put them together, and it works out to 13.2% of all adults over the 4-year period from 2015 to 2018, Debra J. Brody, MPH, and Qiuping Gu, MD, PhD, said Sept. 4 in an NCHS data brief.

The racial/ethnic differences in antidepressant use were even greater, at least for women. Non-Hispanic White women had a past-30-day prevalence of 22.3%, compared with 10.0% for non-Hispanic Black women, 3.4% for non-Hispanic Asian women, and 8.9% for Hispanic women, based on the NHANES data.

The order was the same for men, but the numbers are lower. Non-Hispanic Whites had the highest antidepressant use at 10.5%, followed by non-Hispanic Blacks (5.0%), non-Hispanic Asians (2.1%), and Hispanics (4.0%). All of the differences between Whites and non-Whites were significant for both women and men, the researchers noted.

A look at trends over time shows that the gap between men and women has widened in the last 10 years. Past-30-day use among women went from 13.8% in 2009-2010 to 18.6% in 2017-2018, with a corresponding increase from 7.1% to 8.7% in men. For women, that change was significant; for men, it was not, Ms. Brody and Dr. Gu said.

The sample size averaged just over 6,000 for each of the five 2-year NHANES cycles included in the analysis. The survey includes a household interview and a physical examination at a mobile exam center.

[email protected]

Women are more than twice as likely as men to use antidepressants, and use among White women is at least double that of other races/ethnicities, according to a new analysis from the National Center for Health Statistics.

Here are the actual numbers: 17.7% of women and 8.4% of men used an antidepressant in the 30 days before being interviewed for the National Health and Nutrition Examination Survey (NHANES). Put them together, and it works out to 13.2% of all adults over the 4-year period from 2015 to 2018, Debra J. Brody, MPH, and Qiuping Gu, MD, PhD, said Sept. 4 in an NCHS data brief.

The racial/ethnic differences in antidepressant use were even greater, at least for women. Non-Hispanic White women had a past-30-day prevalence of 22.3%, compared with 10.0% for non-Hispanic Black women, 3.4% for non-Hispanic Asian women, and 8.9% for Hispanic women, based on the NHANES data.

The order was the same for men, but the numbers are lower. Non-Hispanic Whites had the highest antidepressant use at 10.5%, followed by non-Hispanic Blacks (5.0%), non-Hispanic Asians (2.1%), and Hispanics (4.0%). All of the differences between Whites and non-Whites were significant for both women and men, the researchers noted.

A look at trends over time shows that the gap between men and women has widened in the last 10 years. Past-30-day use among women went from 13.8% in 2009-2010 to 18.6% in 2017-2018, with a corresponding increase from 7.1% to 8.7% in men. For women, that change was significant; for men, it was not, Ms. Brody and Dr. Gu said.

The sample size averaged just over 6,000 for each of the five 2-year NHANES cycles included in the analysis. The survey includes a household interview and a physical examination at a mobile exam center.

[email protected]

Women are more than twice as likely as men to use antidepressants, and use among White women is at least double that of other races/ethnicities, according to a new analysis from the National Center for Health Statistics.

Here are the actual numbers: 17.7% of women and 8.4% of men used an antidepressant in the 30 days before being interviewed for the National Health and Nutrition Examination Survey (NHANES). Put them together, and it works out to 13.2% of all adults over the 4-year period from 2015 to 2018, Debra J. Brody, MPH, and Qiuping Gu, MD, PhD, said Sept. 4 in an NCHS data brief.

The racial/ethnic differences in antidepressant use were even greater, at least for women. Non-Hispanic White women had a past-30-day prevalence of 22.3%, compared with 10.0% for non-Hispanic Black women, 3.4% for non-Hispanic Asian women, and 8.9% for Hispanic women, based on the NHANES data.

The order was the same for men, but the numbers are lower. Non-Hispanic Whites had the highest antidepressant use at 10.5%, followed by non-Hispanic Blacks (5.0%), non-Hispanic Asians (2.1%), and Hispanics (4.0%). All of the differences between Whites and non-Whites were significant for both women and men, the researchers noted.

A look at trends over time shows that the gap between men and women has widened in the last 10 years. Past-30-day use among women went from 13.8% in 2009-2010 to 18.6% in 2017-2018, with a corresponding increase from 7.1% to 8.7% in men. For women, that change was significant; for men, it was not, Ms. Brody and Dr. Gu said.

The sample size averaged just over 6,000 for each of the five 2-year NHANES cycles included in the analysis. The survey includes a household interview and a physical examination at a mobile exam center.

[email protected]

Sleep disorders may be silent precursors of cardiometabolic disease among U.S. Latinos, said authors of a newly published study.

Xiaoyu Li, ScD, and Susan Redline, MD, MPH, of Harvard Medical School and Brigham and Women’s Hospital, Boston, and coauthors conducted a study of people who self-identified as Latino, who had baseline sleeping disorders, and who developed hypertension and diabetes over time. The study was published in the American Journal of Respiratory and Critical Care Medicine.

The findings suggested that sleep disorders preceded the development of hypertension and diabetes. Examining records from a major multiyear federal project, the Hispanic Community Health Study/Study of Latinos, Dr. Li, Dr. Redline, and coauthors found sleep-disordered breathing (SDB) was associated with a 1.54 higher adjusted odds of incident hypertension (95% confidence interval [CI], 1.18-2.00) and 1.33 higher odds of incident diabetes (95% CI, 1.05-1.67), compared with no SDB. Insomnia was associated with incident hypertension (odds ratio, 1.37; 95% CI, 1.11-1.69), but not diabetes. The association between insomnia and incident hypertension was stronger among men than women, they reported.

“We now need large-scale rigorous trials to evaluate the impact of early treatment of sleep disordered breathing and insomnia on preventing the development of hypertension and diabetes,” Dr. Redline said in an interview. “Clinicians should consider screening their patients at risk for hypertension and diabetes for both sleep-disordered breathing and insomnia.”
 

Implications for public health strategies

The study results may have implications for health strategies and policies aimed at addressing health differentials among ethnic and economic groups in the United States.

Suboptimal sleep health may be an important fundamental but understudied contributor to health disparities, Chandra L. Jackson, PhD, MS, of the National Institute of Environmental Health Sciences, Research Triangle, N.C., said in an interview. Dr. Jackson is the lead author for a report published in August on a 2018 National Institutes of Health workshop regarding the importance of studying sleep health disparities (Sleep 2020 Mar 10. doi: 10.1093/sleep/zsaa037). The NIH workshop emphasized how little research has been done on the prevalence, incidence, morbidity, or mortality of sleep deficiencies of racial and ethnic minority populations, even though members of these groups are generally more likely to experience sleep disorders. The report urged “a nuanced integration between health disparity causal pathways and sleep and circadian-related mechanisms” tailored for these groups, with attention paid to sociocultural context.

Dr. Jackson said the study by Dr. Li and colleagues fits nicely with the strategies recommended in this report. She added: “Prospective design is particularly important for establishing temporality or that the SDB and insomnia symptoms occurred before the outcomes of hypertension and diabetes.”

In commenting on the Xi/Redline paper, Krishna M. Sundar, MD, FCCP, medical director of the Sleep-Wake Center at the University of Utah, Salt Lake City, commended the study and noted that one of the challenges in sleep research is the long time period over which the effects of disordered breathing become clear, he said.

“Things don’t happen immediately. It takes months, years for the effects to develop,” Dr. Sundar said. “To try to piece together the relationships, you need very well planned studies.”
 

Study design: Participants and exclusions

Latinos currently make up 17.8%, or 57.5 million, of the U.S. population, and this group is expected to double within the next 4 decades, the investigators wrote. A few prior studies on the roles of sleep disorders in the cardiometabolic health of Latinos, though suggestive, were limited by cross-sectional designs, relatively small samples, and underrepresentation of various Latino heritage groups.

The investigators on this new study worked with data from the federal Hispanic Community Health Study/Study of Latinos (HCHS/SOL) in which more than 16,000 people participated.

This multiyear federal study drew people who self-identified with different heritage groups, including Cuban, Dominican, Mexican, Central American, South American, and Puerto Rican. Participants initially aged 18-74 years underwent a first round of exams and assessments between 2008 and 2011 to determine what risk factors they had at the start of the study. In the second phase, which took place from 2013 to 2018, participants had a second set of exams. The National Heart, Lung, and Blood Institute and the National Institute of Diabetes and Digestive and Kidney Diseases funded the HCHS/SOL.

The investigators initially had a potential data pool of 11,623 participants in the HCHS/SOL. About 1 of 8 in this group, or 1,424 participants (12.3%), did not undergo a sleep study or did not have sufficient sleep data for analyses. Another 93 (0.8%) participants were excluded for missing data on covariates.

For incident hypertension analyses, participants who had prevalent hypertension at the first screening in the HCHS/SOL (n = 3,139) or had missing data on hypertension (n = 2) were excluded. That resulted in an analytic sample of 6,965 for hypertension questions.

For incident diabetes analyses, participants who had prevalent diabetes at the first screening (n = 2,062) or had missing data on diabetes (n = 21) were excluded, yielding an analytic sample of 8,023.

Incident hypertension was defined as participants not having hypertension at baseline and having hypertension, defined as a systolic blood pressure 140 mm Hg or greater, diastolic blood pressure 90 mm Hg or greater, or receiving antihypertensive medication within 4 weeks, at the second round of screening.
 

Cardiometabolic disease definitions

The researchers did not discriminate between type 1 and type 2 diabetes. They used the American Diabetes Association definition as a fasting plasma glucose 126 mg/dL or greater, 2-hour, postload plasma glucose 200 mg/dL or greater, or hemoglobin A1c 6.5% or greater, with an additional criterion on self-reported use of antidiabetic medication within 4 weeks before the visit.

In line with previous research, the investigators controlled for potential confounders measured at baseline including sociodemographic factors, health behaviors, and adiposity, which are considered important risk factors for both sleep disorders and incident metabolic diseases. These factors include education level, age, gender, and body mass index and whether participants had ever been smokers or users of alcohol.
 

Study limitations

Limitations of the study include use of a home sleep apnea test device that did not allow evaluation of arousal or sleep architecture. The researchers said this may have led to an underestimation of disease severity both due to overestimation of sleep time and underrecognition of hypopneas unassociated with desaturation. In addition, prior research has suggested that minority populations might underreport sleep disturbances, possibly “due to social desirability (a tendency not to encode a negative event), stress, stereotype threat, acculturation, attitudes, etc.” The participants were recruited mostly from urban areas, and the results might not be generalized to rural populations. In addition, 41% of study participants were of Mexican heritage, compared with 63% of the Hispanic population being of Mexican heritage in the United States.

Another researcher in the field of health disparities, Julia Roncoroni, PhD, assistant professor of psychology at the University of Denver, also noted this slight underrepresentation of Hispanics of Mexican origin and an overrepresentation of urban individuals in the HCHS/SOL.

“However, using data from HCHS/SOL, which is the largest multicenter epidemiological study of cardiovascular risk factors and sleep traits in U.S. Hispanics/Latinx, allows researchers to answer a high-impact question that would otherwise be prohibitively expensive and time consuming,” wrote Dr. Roncoroni.
 

Conclusions

The study offers “the first prospective evidence on the associations between SDB and insomnia with incident hypertension and diabetes in US Hispanics/Latinos.” The investigators concluded: “Given the fact that sleep disorders are largely undiagnosed and undertreated, they might represent modifiable targets for disease prevention and reduction among US Hispanics/Latinos. Culturally informed interventions focusing on detecting and treating sleep disorders might improve cardiometabolic health among US Hispanics/Latinos.”

Dr. Redline was partially supported by NIH grant R35 HL135818. This study drew from the Hispanic Community Health Study/Study of Latinos, which has been supported by contracts from the National Heart, Lung, and Blood Institute.

SOURCE: Li X et al. Am J Respir Crit Care Med. 2020 Aug 6. doi: 10.1164/rccm.201912-2330OC.

Sleep disorders may be silent precursors of cardiometabolic disease among U.S. Latinos, said authors of a newly published study.

Xiaoyu Li, ScD, and Susan Redline, MD, MPH, of Harvard Medical School and Brigham and Women’s Hospital, Boston, and coauthors conducted a study of people who self-identified as Latino, who had baseline sleeping disorders, and who developed hypertension and diabetes over time. The study was published in the American Journal of Respiratory and Critical Care Medicine.

The findings suggested that sleep disorders preceded the development of hypertension and diabetes. Examining records from a major multiyear federal project, the Hispanic Community Health Study/Study of Latinos, Dr. Li, Dr. Redline, and coauthors found sleep-disordered breathing (SDB) was associated with a 1.54 higher adjusted odds of incident hypertension (95% confidence interval [CI], 1.18-2.00) and 1.33 higher odds of incident diabetes (95% CI, 1.05-1.67), compared with no SDB. Insomnia was associated with incident hypertension (odds ratio, 1.37; 95% CI, 1.11-1.69), but not diabetes. The association between insomnia and incident hypertension was stronger among men than women, they reported.

“We now need large-scale rigorous trials to evaluate the impact of early treatment of sleep disordered breathing and insomnia on preventing the development of hypertension and diabetes,” Dr. Redline said in an interview. “Clinicians should consider screening their patients at risk for hypertension and diabetes for both sleep-disordered breathing and insomnia.”
 

Implications for public health strategies

The study results may have implications for health strategies and policies aimed at addressing health differentials among ethnic and economic groups in the United States.

Suboptimal sleep health may be an important fundamental but understudied contributor to health disparities, Chandra L. Jackson, PhD, MS, of the National Institute of Environmental Health Sciences, Research Triangle, N.C., said in an interview. Dr. Jackson is the lead author for a report published in August on a 2018 National Institutes of Health workshop regarding the importance of studying sleep health disparities (Sleep 2020 Mar 10. doi: 10.1093/sleep/zsaa037). The NIH workshop emphasized how little research has been done on the prevalence, incidence, morbidity, or mortality of sleep deficiencies of racial and ethnic minority populations, even though members of these groups are generally more likely to experience sleep disorders. The report urged “a nuanced integration between health disparity causal pathways and sleep and circadian-related mechanisms” tailored for these groups, with attention paid to sociocultural context.

Dr. Jackson said the study by Dr. Li and colleagues fits nicely with the strategies recommended in this report. She added: “Prospective design is particularly important for establishing temporality or that the SDB and insomnia symptoms occurred before the outcomes of hypertension and diabetes.”

In commenting on the Xi/Redline paper, Krishna M. Sundar, MD, FCCP, medical director of the Sleep-Wake Center at the University of Utah, Salt Lake City, commended the study and noted that one of the challenges in sleep research is the long time period over which the effects of disordered breathing become clear, he said.

“Things don’t happen immediately. It takes months, years for the effects to develop,” Dr. Sundar said. “To try to piece together the relationships, you need very well planned studies.”