Foundation models for generalist medical artificial intelligence.

The exceptionally rapid development of highly flexible, reusable artificial intelligence (AI) models is likely to usher in newfound capabilities in medicine. We propose a new paradigm for medical AI, which we refer to as generalist medical AI (GMAI). GMAI models will be capable of carrying out a diverse set of tasks using very little or no task-specific labelled data. Built through self-supervision on large, diverse datasets, GMAI will flexibly interpret different combinations of medical modalities, including data from imaging, electronic health records, laboratory results, genomics, graphs or medical text. Models will in turn produce expressive outputs such as free-text explanations, spoken recommendations or image annotations that demonstrate advanced medical reasoning abilities. Here we identify a set of high-impact potential applications for GMAI and lay out specific technical capabilities and training datasets necessary to enable them. We expect that GMAI-enabled applications will challenge current strategies for regulating and validating AI devices for medicine and will shift practices associated with the collection of large medical datasets.

Distinguishing features of long COVID identified through immune profiling.

Post-acute infection syndromes may develop after acute viral disease1. Infection with SARS-CoV-2 can result in the development of a post-acute infection syndrome known as long COVID. Individuals with long COVID frequently report unremitting fatigue, post-exertional malaise, and a variety of cognitive and autonomic dysfunctions2-4. However, the biological processes that are associated with the development and persistence of these symptoms are unclear. Here 275 individuals with or without long COVID were enrolled in a cross-sectional study that included multidimensional immune phenotyping and unbiased machine learning methods to identify biological features associated with long COVID. Marked differences were noted in circulating myeloid and lymphocyte populations relative to the matched controls, as well as evidence of exaggerated humoral responses directed against SARS-CoV-2 among participants with long COVID. Furthermore, higher antibody responses directed against non-SARS-CoV-2 viral pathogens were observed among individuals with long COVID, particularly Epstein-Barr virus. Levels of soluble immune mediators and hormones varied among groups, with cortisol levels being lower among participants with long COVID. Integration of immune phenotyping data into unbiased machine learning models identified the key features that are most strongly associated with long COVID status. Collectively, these findings may help to guide future studies into the pathobiology of long COVID and help with developing relevant biomarkers.

Long-term exposure to wildland fire smoke PM2.5 and mortality in the contiguous United States.

Despite the substantial evidence on the health effects of short-term exposure to ambient fine particles (PM2.5), including increasing studies focusing on those from wildland fire smoke, the impacts of long-term wildland fire smoke PM2.5 exposure remain unclear. We investigated the association between long-term exposure to wildland fire smoke PM2.5 and nonaccidental mortality and mortality from a wide range of specific causes in all 3,108 counties in the contiguous United States, 2007 to 2020. Controlling for nonsmoke PM2.5, air temperature, and unmeasured spatial and temporal confounders, we found a nonlinear association between 12-mo moving average concentration of smoke PM2.5 and monthly nonaccidental mortality rate. Relative to a month with the long-term smoke PM2.5 exposure below 0.1 µg/m3, nonaccidental mortality increased by 0.16 to 0.63 and 2.11 deaths per 100,000 people per month when the 12-mo moving average of PM2.5 concentration was of 0.1 to 5 and 5+ µg/m3, respectively. Cardiovascular, ischemic heart disease, digestive, endocrine, diabetes, mental, and chronic kidney disease mortality were all found to be associated with long-term wildland fire smoke PM2.5 exposure. Smoke PM2.5 contributed to approximately 11,415 nonaccidental deaths/y (95% CI: 6,754, 16,075) in the contiguous United States. Higher smoke PM2.5-related increases in mortality rates were found for people aged 65 and above. Positive interaction effects with extreme heat were also observed. Our study identified the detrimental effects of long-term exposure to wildland fire smoke PM2.5 on a wide range of mortality outcomes, underscoring the need for public health actions and communications that span the health risks of both short- and long-term exposure.

Class I Recalls of Cardiovascular Devices Between 2013 and 2022 : A Cross-Sectional Analysis.

BACKGROUND: Cardiovascular devices account for one third of all Class I recalls, the U.S. Food and Drug Administration's (FDA) most severe designation, indicating a reasonable probability of "serious adverse health consequences or death." Understanding recalls and their causes is important for patient safety. OBJECTIVE: To characterize Class I recalls of cardiovascular devices and the clinical evidence supporting authorization. DESIGN: In this cross-sectional study, cardiovascular device recalls from 1 January 2013 through 31 December 2022 were identified using the FDA's annual log. Information about devices was extracted from publicly available FDA decision summaries. SETTING: The FDA Medical Device Recalls database. PARTICIPANTS: Cardiovascular devices with Class I recalls. MEASUREMENTS: Recalls were characterized by their causes and scope. Devices were characterized by their regulatory history (product code, special designations) and clinical evidence (premarket testing, postmarket surveillance). Clinical studies were analyzed for quality, including end point selection (clinical vs. surrogate, use of composites). RESULTS: From 2013 to 2022, there were 137 Class I recall events affecting 157 unique cardiovascular devices, of which 112 (71.3%) were moderate-risk 510(k) devices and 45 (28.7%) were high-risk premarket approval (PMA) devices. Recalls affected a median of 7649 units (IQR, 953 to 28 446) and were most commonly attributed to device design (43 [31.4%]). Forty-two (26.8%) devices had multiple Class I recalls. Thirty (19.1%) devices underwent premarket clinical testing (7 [6.2%] 510(k) devices, 17 [85.0%] PMA devices, and 6 [24.0%] PMA supplement devices). Most studies used surrogate (27 [79.4%]) and composite (24 [70.6%]) measures as primary end points. Twenty-two (48.9%) PMA devices had required postapproval studies, with 14 reporting delays. No 510(k) devices were subject to postmarket surveillance. LIMITATION: Details about clinical testing may be missing from FDA summaries. CONCLUSION: Cardiovascular devices with Class I recalls were infrequently subjected to premarket or postmarket testing, with recalls affecting thousands of patients annually. PRIMARY FUNDING SOURCE: None.

Detection of Left Ventricular Systolic Dysfunction From Electrocardiographic Images.

BACKGROUND: Left ventricular (LV) systolic dysfunction is associated with a >8-fold increased risk of heart failure and a 2-fold risk of premature death. The use of ECG signals in screening for LV systolic dysfunction is limited by their availability to clinicians. We developed a novel deep learning-based approach that can use ECG images for the screening of LV systolic dysfunction. METHODS: Using 12-lead ECGs plotted in multiple different formats, and corresponding echocardiographic data recorded within 15 days from the Yale New Haven Hospital between 2015 and 2021, we developed a convolutional neural network algorithm to detect an LV ejection fraction <40%. The model was validated within clinical settings at Yale New Haven Hospital and externally on ECG images from Cedars Sinai Medical Center in Los Angeles, CA; Lake Regional Hospital in Osage Beach, MO; Memorial Hermann Southeast Hospital in Houston, TX; and Methodist Cardiology Clinic of San Antonio, TX. In addition, it was validated in the prospective Brazilian Longitudinal Study of Adult Health. Gradient-weighted class activation mapping was used to localize class-discriminating signals on ECG images. RESULTS: Overall, 385 601 ECGs with paired echocardiograms were used for model development. The model demonstrated high discrimination across various ECG image formats and calibrations in internal validation (area under receiving operation characteristics [AUROCs], 0.91; area under precision-recall curve [AUPRC], 0.55); and external sets of ECG images from Cedars Sinai (AUROC, 0.90 and AUPRC, 0.53), outpatient Yale New Haven Hospital clinics (AUROC, 0.94 and AUPRC, 0.77), Lake Regional Hospital (AUROC, 0.90 and AUPRC, 0.88), Memorial Hermann Southeast Hospital (AUROC, 0.91 and AUPRC 0.88), Methodist Cardiology Clinic (AUROC, 0.90 and AUPRC, 0.74), and Brazilian Longitudinal Study of Adult Health cohort (AUROC, 0.95 and AUPRC, 0.45). An ECG suggestive of LV systolic dysfunction portended >27-fold higher odds of LV systolic dysfunction on transthoracic echocardiogram (odds ratio, 27.5 [95% CI, 22.3-33.9] in the held-out set). Class-discriminative patterns localized to the anterior and anteroseptal leads (V2 and V3), corresponding to the left ventricle regardless of the ECG layout. A positive ECG screen in individuals with an LV ejection fraction ≥40% at the time of initial assessment was associated with a 3.9-fold increased risk of developing incident LV systolic dysfunction in the future (hazard ratio, 3.9 [95% CI, 3.3-4.7]; median follow-up, 3.2 years). CONCLUSIONS: We developed and externally validated a deep learning model that identifies LV systolic dysfunction from ECG images. This approach represents an automated and accessible screening strategy for LV systolic dysfunction, particularly in low-resource settings.

Ischemic Stroke and Reduced Left Ventricular Ejection Fraction: A Multidisciplinary Approach to Optimize Brain and Cardiac Health.

Reduced left ventricular ejection fraction ≤40%, a known risk factor for adverse cardiac outcomes and recurrent acute ischemic stroke, may be detected during an acute ischemic stroke hospitalization. A multidisciplinary care paradigm informed by neurology and cardiology expertise may facilitate the timely implementation of an array of proven heart failure-specific therapies and procedures in a nuanced manner to optimize brain and cardiac health.

Fibrinolytic Agents in Thromboembolic Diseases: Historical Perspectives and Approved Indications.

Fibrinolytic agents catalyze the conversion of the inactive proenzyme plasminogen into the active protease plasmin, degrading fibrin within the thrombus and recanalizing occluded vessels. The history of these medications dates to the discovery of the first fibrinolytic compound, streptokinase, from bacterial cultures in 1933. Over time, researchers identified two other plasminogen activators in human samples, namely urokinase and tissue plasminogen activator (tPA). Subsequently, tPA was cloned using recombinant DNA methods to produce alteplase. Several additional derivatives of tPA, such as tenecteplase and reteplase, were developed to extend the plasma half-life of tPA. Over the past decades, fibrinolytic medications have been widely used to manage patients with venous and arterial thromboembolic events. Currently, alteplase is approved by the U.S. Food and Drug Administration (FDA) for use in patients with pulmonary embolism with hemodynamic compromise, ST-segment elevation myocardial infarction (STEMI), acute ischemic stroke, and central venous access device occlusion. Reteplase and tenecteplase have also received FDA approval for treating patients with STEMI. This review provides an overview of the historical background related to fibrinolytic agents and briefly summarizes their approved indications across various thromboembolic diseases.

Developmental or Procedural Vena Cava Interruption and Venous Thromboembolism: A Review.

The inferior vena cava (IVC) and superior vena cava are the main conduits of the systemic venous circulation into the right atrium. Developmental or procedural interruptions of vena cava might predispose to stasis and deep vein thrombosis (DVT) distal to the anomaly and may impact the subsequent rate of pulmonary embolism (PE). This study aimed to review the various etiologies of developmental or procedural vena cava interruption and their impact on venous thromboembolism. A systematic search was performed in PubMed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines per each clinical question. For management questions with no high-quality evidence and no mutual agreements between authors, Delphi methods were used. IVC agenesis is the most common form of congenital vena cava interruption, is associated with an increased risk of DVT, and should be suspected in young patients with unexpected extensive bilateral DVT. Surgical techniques for vena cava interruption (ligation, clipping, and plication) to prevent PE have been largely abandoned due to short-term procedural risks and long-term complications, although survivors of prior procedures are occasionally encountered. Vena cava filters are now the most commonly used method of procedural interruption, frequently placed in the infrarenal IVC. The most agreed-upon indication for vena cava filters is for patients with acute venous thromboembolism and coexisting contraindications to anticoagulation. Familiarity with different forms of vena cava interruption and their local and systemic adverse effects is important to minimize complications and thrombotic events.

Decreasing alloimmunization-specific mortality in sickle cell disease in the United States: Cost-effectiveness of a shared transfusion resource.

Red blood cell alloimmunization and consequent delayed hemolytic transfusion reaction (DHTR) incidence and mortality in patients with sickle cell disease (SCD) are high. A shared transfusion resource has decreased both in other countries, while in the United States cost concerns persist. We conducted a Markov cohort simulation of a birth cohort of alloimmunized patients with SCD to estimate lifetime DHTR incidence, DHTR-specific mortality, quality-adjusted life expectancy (QALE), and costs with the implementation of a shared transfusion resource to identify antibody history versus without (i.e., status quo). We conducted our analysis using a lifetime analytic time horizon and from a United States health system perspective. Implementation of shared transfusion resource projects to decrease cumulative DHTR-specific mortality by 26% for alloimmunized patients with SCD in the United States, relative to the status quo. For an average patient population of 32 000, this intervention would generate a discounted increment of 4000 QALYs at an incremental discounted cost of $0.3 billion, resulting in an incremental cost-effectiveness ratio of $75 600/QALY [95% credible interval $70 200-81 400/QALY]. The results are most sensitive to the baseline lifetime medical expenditure of patients with SCD. Alloantibody data exchange is cost-effective in 100% of 10 000 Monte Carlo simulations. The resource would theoretically need a minimum patient population of 1819 patients or cost no more than $5.29 million annually to be cost-effective. By reducing DHTR-specific mortality, a shared transfusion resource in the United States projects to be a life-saving and cost-effective intervention for patients with SCD in the United States.

Use of electronic health records to characterize patients with uncontrolled hypertension in two large health system networks.

BACKGROUND: Improving hypertension control is a public health priority. However, consistent identification of uncontrolled hypertension using computable definitions in electronic health records (EHR) across health systems remains uncertain. METHODS: In this retrospective cohort study, we applied two computable definitions to the EHR data to identify patients with controlled and uncontrolled hypertension and to evaluate differences in characteristics, treatment, and clinical outcomes between these patient populations. We included adult patients (≥ 18 years) with hypertension (based on either ICD-10 codes of hypertension or two elevated blood pressure [BP] measurements) receiving ambulatory care within Yale-New Haven Health System (YNHHS; a large US health system) and OneFlorida Clinical Research Consortium (OneFlorida; a Clinical Research Network comprised of 16 health systems) between October 2015 and December 2018. We identified patients with controlled and uncontrolled hypertension based on either a single BP measurement from a randomly selected visit or all BP measurements recorded between hypertension identification and the randomly selected visit). RESULTS: Overall, 253,207 and 182,827 adults at YNHHS and OneFlorida were identified as having hypertension. Of these patients, 83.1% at YNHHS and 76.8% at OneFlorida were identified using ICD-10-CM codes, whereas 16.9% and 23.2%, respectively, were identified using elevated BP measurements (≥ 140/90 mmHg). A total of 24.1% of patients at YNHHS and 21.6% at OneFlorida had both diagnosis code for hypertension and elevated blood pressure measurements. Uncontrolled hypertension was observed among 32.5% and 43.7% of patients at YNHHS and OneFlorida, respectively. Uncontrolled hypertension was disproportionately higher among Black patients when compared with White patients (38.9% versus 31.5% in YNHHS; p < 0.001; 49.7% versus 41.2% in OneFlorida; p < 0.001). Medication prescription for hypertension management was more common in patients with uncontrolled hypertension when compared with those with controlled hypertension (overall treatment rate: 39.3% versus 37.3% in YNHHS; p = 0.04; 42.2% versus 34.8% in OneFlorida; p < 0.001). Patients with controlled and uncontrolled hypertension had similar incidence rates of deaths, CVD events, and healthcare visits at 3, 6, 12, and 24 months. The two computable definitions generated consistent results. CONCLUSIONS: While the current EHR systems are not fully optimized for disease surveillance and stratification, our findings illustrate the potential of leveraging EHR data to conduct digital population surveillance in the realm of hypertension management.

Long-Term Stability of Coverage Among Michigan Medicaid Beneficiaries : A Cohort Study.

BACKGROUND: Medicaid, the primary source of insurance coverage for disadvantaged Americans, was originally designed as a temporary safety-net program. No studies have used long-run data to assess the recent use of the program by beneficiaries. OBJECTIVE: To assess patterns of short- and long-term enrollment among beneficiaries, using a 10-year longitudinal panel of Michigan Medicaid eligibility data. DESIGN: Primary analyses assessing trends in Medicaid enrollment among cohorts of existing and new beneficiaries. SETTING: Administrative records from Michigan Medicaid for the period 2011 to 2020. PARTICIPANTS: 3.97 million Medicaid beneficiaries. MEASUREMENTS: Short- and long-term enrollment in the program. RESULTS: The sample includes 3.97 million unique beneficiaries enrolled at some point between 2011 and 2020. Among a cohort of 1.23 million beneficiaries enrolled in 2011, over half (53%) were also enrolled in Medicaid in June 2020, spending, on average, two-thirds of that period (67%) on Medicaid. These beneficiaries, however, experienced substantial lapses in coverage, as only 25% were continuously enrolled throughout the period. Enrollment was less stable when assessed from the perspective of newly enrolled beneficiaries, of whom only 37% remained enrolled at the end of the study period. LIMITATION: Primary estimates from a single state. CONCLUSION: For many beneficiaries, Medicaid has served as their primary source of coverage for at least a decade. This pattern would justify increasing investments in the program to improve long-term health outcomes. PRIMARY FUNDING SOURCE: Self-funded.

Severe aortic stenosis detection by deep learning applied to echocardiography.

BACKGROUND AND AIMS: Early diagnosis of aortic stenosis (AS) is critical to prevent morbidity and mortality but requires skilled examination with Doppler imaging. This study reports the development and validation of a novel deep learning model that relies on two-dimensional (2D) parasternal long axis videos from transthoracic echocardiography without Doppler imaging to identify severe AS, suitable for point-of-care ultrasonography. METHODS AND RESULTS: In a training set of 5257 studies (17 570 videos) from 2016 to 2020 [Yale-New Haven Hospital (YNHH), Connecticut], an ensemble of three-dimensional convolutional neural networks was developed to detect severe AS, leveraging self-supervised contrastive pretraining for label-efficient model development. This deep learning model was validated in a temporally distinct set of 2040 consecutive studies from 2021 from YNHH as well as two geographically distinct cohorts of 4226 and 3072 studies, from California and other hospitals in New England, respectively. The deep learning model achieved an area under the receiver operating characteristic curve (AUROC) of 0.978 (95% CI: 0.966, 0.988) for detecting severe AS in the temporally distinct test set, maintaining its diagnostic performance in geographically distinct cohorts [0.952 AUROC (95% CI: 0.941, 0.963) in California and 0.942 AUROC (95% CI: 0.909, 0.966) in New England]. The model was interpretable with saliency maps identifying the aortic valve, mitral annulus, and left atrium as the predictive regions. Among non-severe AS cases, predicted probabilities were associated with worse quantitative metrics of AS suggesting an association with various stages of AS severity. CONCLUSION: This study developed and externally validated an automated approach for severe AS detection using single-view 2D echocardiography, with potential utility for point-of-care screening.

Modernizing the Data Infrastructure for Clinical Research to Meet Evolving Demands for Evidence.

Importance: The ways in which we access, acquire, and use data in clinical trials have evolved very little over time, resulting in a fragmented and inefficient system that limits the amount and quality of evidence that can be generated. Observations: Clinical trial design has advanced steadily over several decades. Yet the infrastructure for clinical trial data collection remains expensive and labor intensive and limits the amount of evidence that can be collected to inform whether and how interventions work for different patient populations. Meanwhile, there is increasing demand for evidence from randomized clinical trials to inform regulatory decisions, payment decisions, and clinical care. Although substantial public and industry investment in advancing electronic health record interoperability, data standardization, and the technology systems used for data capture have resulted in significant progress on various aspects of data generation, there is now a need to combine the results of these efforts and apply them more directly to the clinical trial data infrastructure. Conclusions and Relevance: We describe a vision for a modernized infrastructure that is centered around 2 related concepts. First, allowing the collection and rigorous evaluation of multiple data sources and types and, second, enabling the possibility to reuse health data for multiple purposes. We address the need for multidisciplinary collaboration and suggest ways to measure progress toward this goal.

Association of Neighborhood-Level Material Deprivation With Atrial Fibrillation Care in a Single-Payer Health Care System: A Population-Based Cohort Study.

BACKGROUND: There are limited data on the association of material deprivation with clinical care and outcomes after atrial fibrillation (AF) diagnosis in jurisdictions with universal health care. METHODS: This was a population-based cohort study of individuals ≥66 years of age with first diagnosis of AF between April 1, 2007, and March 31, 2019, in the Canadian province of Ontario, which provides public funding and prohibits private payment for medically necessary physician and hospital services. Prescription medications are subsidized for residents >65 years of age. The primary exposure was neighborhood material deprivation, a metric derived from Canadian census data to estimate inability to attain basic material needs. Neighborhoods were categorized by quintile from Q1 (least deprived) to Q5 (most deprived). Cause-specific hazards regression was used to study the association of material deprivation quintile with time to AF-related adverse events (death or hospitalization for stroke, heart failure, or bleeding), clinical services (physician visits, cardiac diagnostics), and interventions (anticoagulation, cardioversion, ablation) while adjusting for individual characteristics and regional cardiologist supply. RESULTS: Among 347 632 individuals with AF (median age 79 years, 48.9% female), individuals in the most deprived neighborhoods (Q5) had higher prevalence of cardiovascular disease, risk factors, and noncardiovascular comorbidity relative to residents of the least deprived neighborhoods (Q1). After adjustment, Q5 residents had higher hazards of death (hazard ratio [HR], 1.16 [95% CI, 1.13-1.20]) and hospitalization for stroke (HR, 1.16 [95% CI, 1.07-1.27]), heart failure (HR, 1.14 [95% CI, 1.11-1.18]), or bleeding (HR, 1.16 [95% CI, 1.07-1.25]) relative to Q1. There were small differences across quintiles in primary care physician visits (HR, Q5 versus Q1, 0.91 [95% CI, 0.89-0.92]), echocardiography (HR, Q5 versus Q1, 0.97 [95% CI, 0.96-0.99]), and dispensation of anticoagulation (HR, Q5 versus Q1, 0.97 [95% CI, 0.95-0.98]). There were more prominent disparities for Q5 versus Q1 in cardiologist visits (HR, 0.84 [95% CI, 0.82-0.86]), cardioversion (HR, 0.80 [95% CI, 0.76-0.84]), and ablation (HR, 0.45 [95% CI, 0.30-0.67]). CONCLUSIONS: Despite universal health care and prescription medication coverage, residents of more deprived neighborhoods were less likely to visit cardiologists or receive rhythm control interventions after AF diagnosis, even though they exhibited higher cardiovascular disease burden and higher risk of adverse outcomes.

Sex-Related Differences in Patient Characteristics, Risk Factors, and Symptomatology in Older Adults with Pulmonary Embolism: Findings from the SERIOUS-PE Study.

Sex-specific factors are implicated in pulmonary embolism (PE) presentation in young patients, as indicated by increased risk in pregnancy. Whether sex differences exist in PE presentation, comorbidities, and symptomatology in older adults, the age group in which most PEs occur, remains unknown. We identified older adults (aged ≥65 years) with PE in a large international PE registry replete with information about relevant clinical characteristics (RIETE registry, 2001-2021). To provide national data from the United States, we assessed sex differences in clinical characteristics and risk factors of Medicare beneficiaries with PE (2001-2019). The majority of older adults with PE in RIETE (19,294/33,462, 57.7%) and in the Medicare database (551,492/948,823, 58.7%) were women. Compared with men, women with PE less frequently had atherosclerotic diseases, lung disease, cancer, or unprovoked PE, but more frequently had varicose veins, depression, prolonged immobility, or history of hormonal therapy (p < 0.001 for all). Women less often presented with chest pain (37.3 vs. 40.6%) or hemoptysis (2.4 vs. 5.6%) but more often with dyspnea (84.6 vs. 80.9%) (p < 0.001 for all). Measures of clot burden, PE risk stratification, and use of imaging modalities were comparable between women and men. PE is more common in elderly women than in men. Cancer and cardiovascular disease are more common in men, whereas transient provoking factors including trauma, immobility, or hormone therapy are more common in elderly women with PE. Whether such differences correlate with disparities in treatment or differences in short- or long-term clinical outcomes warrants further investigation.

Cost-effectiveness of prophylactic emicizumab versus prophylactic recombinant factor VIII in patients with moderate or mild hemophilia A without inhibitors in the United States.

Prophylactic emicizumab is cost-ineffective in adults with moderate or mild hemophilia A without inhibitors at current pricing. The price of prophylactic emicizumab would need to decrease by >35% to become cost-effective in this patient population.

Prevalence of covid-19 and long covid in collegiate student athletes from spring 2020 to fall 2021: a retrospective survey.

BACKGROUND: Symptomatic COVID-19 and Long COVID, also referred to as post-acute sequelae of SARS-CoV-2 (PASC) or post-COVID conditions, have been widely reported in young, healthy people, but their prevalence has not yet been determined in student athletes. We sought to estimate the prevalence of reported COVID-19, symptomatic COVID-19, and Long COVID in college athletes in the United States attending 18 schools from spring 2020 to fall 2021. METHODS: We developed an online survey to measure the prevalence of student athletes who tested positive for COVID-19, developed Long COVID, and did not return to their sport during the relevant time period. We surveyed a convenience sample of 18 collegiate school administrators, representing about 7,000 student athletes. Of those schools surveyed, 16 responded regarding the spring 2020 semester, and 18 responded regarding the full academic year of fall 2020 to spring 2021 (both semesters). RESULTS: According to the survey responses, there were 9.8% of student athletes who tested positive for COVID-19 in spring 2020 and 25.4% who tested positive in the academic year of fall 2020 to spring 2021. About 4% of student athletes who tested positive from spring 2020 to spring 2021 developed Long COVID, defined as new, recurring, or ongoing physical or mental health consequences occurring 4 or more weeks after SARS-CoV-2 infection. CONCLUSIONS: This study highlights that Long COVID occurs among young, healthy athletes and is a real consequence of COVID-19. Understanding the prevalence of Long COVID in this population requires longer follow-up and further study.

Use of Recalled Devices in New Device Authorizations Under the US Food and Drug Administration's 510(k) Pathway and Risk of Subsequent Recalls.

Importance: In the US, nearly all medical devices progress to market under the 510(k) pathway, which uses previously authorized devices (predicates) to support new authorizations. Current regulations permit manufacturers to use devices subject to a Class I recall-the FDA's most serious designation indicating a high probability of adverse health consequences or death-as predicates for new devices. The consequences for patient safety are not known. Objective: To determine the risk of a future Class I recall associated with using a recalled device as a predicate device in the 510(k) pathway. Design and Setting: In this cross-sectional study, all 510(k) devices subject to Class I recalls from January 2017 through December 2021 (index devices) were identified from the FDA's annual recall listings. Information about predicate devices was extracted from the Devices@FDA database. Devices authorized using index devices as predicates (descendants) were identified using a regulatory intelligence platform. A matched cohort of predicates was constructed to assess the future recall risk from using a predicate device with a Class I recall. Main Outcomes and Measures: Devices were characterized by their regulatory history and recall history. Risk ratios (RRs) were calculated to compare the risk of future Class I recalls between devices descended from predicates with matched controls. Results: Of 156 index devices subject to Class I recall from 2017 through 2021, 44 (28.2%) had prior Class I recalls. Predicates were identified for 127 index devices, with 56 (44.1%) using predicates with a Class I recall. One hundred four index devices were also used as predicates to support the authorization of 265 descendant devices, with 50 index devices (48.1%) authorizing a descendant with a Class I recall. Compared with matched controls, devices authorized using predicates with Class I recalls had a higher risk of subsequent Class I recall (6.40 [95% CI, 3.59-11.40]; P<.001). Conclusions and Relevance: Many 510(k) devices subjected to Class I recalls in the US use predicates with a known history of Class I recalls. These devices have substantially higher risk of a subsequent Class I recall. Safeguards for the 510(k) pathway are needed to prevent problematic predicate selection and ensure patient safety.

Excess Mortality and Years of Potential Life Lost Among the Black Population in the US, 1999-2020.

Importance: Amid efforts in the US to promote health equity, there is a need to assess recent progress in reducing excess deaths and years of potential life lost among the Black population compared with the White population. Objective: To evaluate trends in excess mortality and years of potential life lost among the Black population compared with the White population. Design, setting, and participants: Serial cross-sectional study using US national data from the Centers for Disease Control and Prevention from 1999 through 2020. We included data from non-Hispanic White and non-Hispanic Black populations across all age groups. Exposures: Race as documented in the death certificates. Main outcomes and measures: Excess age-adjusted all-cause mortality, cause-specific mortality, age-specific mortality, and years of potential life lost rates (per 100 000 individuals) among the Black population compared with the White population. Results: From 1999 to 2011, the age-adjusted excess mortality rate declined from 404 to 211 excess deaths per 100 000 individuals among Black males (P for trend <.001). However, the rate plateaued from 2011 through 2019 (P for trend = .98) and increased in 2020 to 395-rates not seen since 2000. Among Black females, the rate declined from 224 excess deaths per 100 000 individuals in 1999 to 87 in 2015 (P for trend <.001). There was no significant change between 2016 and 2019 (P for trend = .71) and in 2020 rates increased to 192-levels not seen since 2005. The trends in rates of excess years of potential life lost followed a similar pattern. From 1999 to 2020, the disproportionately higher mortality rates in Black males and females resulted in 997 623 and 628 464 excess deaths, respectively, representing a loss of more than 80 million years of life. Heart disease had the highest excess mortality rates, and the excess years of potential life lost rates were largest among infants and middle-aged adults. Conclusions and relevance: Over a recent 22-year period, the Black population in the US experienced more than 1.63 million excess deaths and more than 80 million excess years of life lost when compared with the White population. After a period of progress in reducing disparities, improvements stalled, and differences between the Black population and the White population worsened in 2020.

National Trends and Disparities in Hospitalization for Acute Hypertension Among Medicare Beneficiaries (1999-2019).

BACKGROUND: In the past 2 decades, hypertension control in the US population has not improved and there are widening disparities. Little is known about progress in reducing hospitalizations for acute hypertension. METHODS: We conducted serial cross-sectional analysis of Medicare fee-for-service beneficiaries age 65 years or older between 1999 and 2019 using Medicare denominator and inpatient files. We evaluated trends in national hospitalization rates for acute hypertension overall and by demographic and geographical subgroups. We identified all beneficiaries admitted with a primary discharge diagnosis of acute hypertension on the basis of International Classification of Diseases codes. We then used a mixed effects model with a Poisson link function and state-specific random intercepts, adjusting for age, sex, race and ethnicity, and dual-eligible status, to evaluate trends in hospitalizations. RESULTS: The sample consisted of 397 238 individual Medicare fee-for-service beneficiaries. From 1999 through 2019, the annual hospitalization rates for acute hypertension increased significantly, from 51.5 to 125.9 per 100 000 beneficiary-years; the absolute increase was most pronounced among the following subgroups: adults ≥85 years (66.8-274.1), females (64.9-160.1), Black people (144.4-369.5), and Medicare/Medicaid insured (dual-eligible, 93.1-270.0). Across all subgroups, Black adults had the highest hospitalization rate in 2019, and there was a significant increase in the differences in hospitalizations between Black and White people from 1999 to 2019. Marked geographic variation was also present, with the highest hospitalization rates in the South. Among patients hospitalized for acute hypertension, the observed 30-day and 90-day all-cause mortality rates (95% CI) decreased from 2.6% (2.27-2.83) and 5.6% (5.18-5.99) to 1.7% (1.53-1.80) and 3.7% (3.45-3.84) and 30-day and 90-day all-cause readmission rates decreased from 15.7% (15.1-16.4) and 29.4% (28.6-30.2) to 11.8% (11.5-12.1) and 24.0% (23.5-24.6). CONCLUSIONS: Among Medicare fee-for-service beneficiaries age 65 years or older, hospitalization rates for acute hypertension increased substantially and significantly from 1999 to 2019. Black adults had the highest hospitalization rate in 2019 across age, sex, race and ethnicity, and dual-eligible strata. There was significant national variation, with the highest rates generally in the South.