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.

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.

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.

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.

Variation in Risk-standardized Rates and Causes of Unplanned Hospital Visits Within 7 Days of Hospital Outpatient Surgery.

OBJECTIVES: The objectives of this study were to compare risk-standardized hospital visit ratios of the predicted to expected number of unplanned hospital visits within 7 days of same-day surgeries performed at US hospital outpatient departments (HOPDs) and to describe the causes of hospital visits. SUMMARY OF BACKGROUND DATA: More than half of procedures in the US are performed in outpatient settings, yet little is known about facility-level variation in short-term safety outcomes. METHODS: The study cohort included 1,135,441 outpatient surgeries performed at 4058 hospitals between October 1, 2015 and September 30, 2016 among Medicare Fee-for-Service beneficiaries aged ≥65 years. Hospital-level, risk-standardized measure scores of unplanned hospital visits (emergency department visits, observation stays, and unplanned inpatient admissions) within 7 days of hospital outpatient surgery were calculated using hierarchical logistic regression modeling that adjusted for age, clinical comorbidities, and surgical procedural complexity. RESULTS: Overall, 7.8% of hospital outpatient surgeries were followed by an unplanned hospital visit within 7 days. Many of the leading reasons for unplanned visits were for potentially preventable conditions, such as urinary retention, infection, and pain. We found considerable variation in the risk-standardized ratio score across hospitals. The 203 best-performing HOPDs, at or below the 5th percentile, had at least 22% fewer unplanned hospital visits than expected, whereas the 202 worst-performing HOPDs, at or above the 95th percentile, had at least 29% more post-surgical visits than expected, given their case and surgical procedure mix. CONCLUSIONS: Many patients experience an unplanned hospital visit within 7 days of hospital outpatient surgery, often for potentially preventable reasons. The observed variation in performance across hospitals suggests opportunities for quality improvement.

Identifying quality of life outcome patterns to inform treatment choices in ischemic cardiomyopathy.

BACKGROUND: The Surgical Treatment for Ischemic Heart Failure (STICH) trial found that routine use of coronary artery bypass surgery (CABG) improved mean quality of life (QoL) scores relative to guideline-directed medical therapy (GDMT) in patients with ischemic cardiomyopathy. However, mean differences in QoL scores do not provide what patients want to know when facing a high-risk/high-benefit treatment choice. METHODS: We analyzed Kansas City Cardiomyopathy Questionnaire (KCCQ) Overall Summary scores in CABG and GDMT patients over 36 months using a combination of statistical methods to group QoL data into clinically relevant outcome patterns (phenotype trajectories) and to then identify the main baseline predictors of each phenotype. QoL outcome phenotypes were developed using mixture models to define the dominant phenotype trajectories present in STICH QoL data. Logistic regression models were used to predict each patient's probability of achieving each outcome pattern with each treatment. RESULTS: In STICH, 592 patients underwent CABG and 607 were managed with GDMT. Our analyses identified 3 phenotype trajectory patterns in both treatment groups. Two of the 3 trajectories showed improving patterns, and were classified as "good QoL trajectories," seen in 498 (84.1%) CABG and 449 (73.9%) GDMT patients. Defining a consequential CABG-GDMT treatment difference as a >10% higher absolute predicted probability of belonging to good QoL trajectories, 277 (23.5%) patients were more likely to have good outcome with CABG while 45 (3.8%) patients were more likely to have a good outcome with GDMT. For 644 (54.7%) patients, CABG and GDMT probabilities of a good outcome were within 5% of each other. CONCLUSIONS: The pattern of QoL outcomes after CABG compared with GDMT in STICH followed 3 main phenotypic trajectories, which could be predicted based on individual baseline features. Patient-specific predictions about expected QoL outcomes with different treatment choices provide an intuitive framework for personalizing patient decision making.

Trends and Variation in the Gap Between Current and Anticipated Life Satisfaction in the United States, 2008-2020.

Objectives. To describe national- and county-level trends and variation in a novel measure of hope. Methods. Using data from the Gallup National Health and Well-Being Index (n = 2 766 728), we summarized the difference between anticipated life satisfaction (ALS) and current life satisfaction (CLS), measured by the Cantril Self-Anchoring Scale, for each year from 2008 to 2020 and by county over two 5-year periods in the United States. Results. Across all years, there was a significant positive trend in the difference between ALS and CLS for the nation (P = .024), which remained positive but not significant when we excluded 2020. Maintenance of ALS with a decrease in CLS drove the 2020 increase. From 2008-2012 to 2013-2017, 14.5% of counties with 300 or more responses (n = 599) experienced an increase in the difference of more than 1 SD, whereas 13.9% experienced a more than 1 SD decrease. Fifty-two counties experienced decreases in ALS and CLS. Conclusions. Responding to trends in the gap between ALS and CLS at national and local levels is essential for the collective well-being of our nation, especially as we navigate and emerge from crisis.

A prospective cohort study examining exposure to incarceration and cardiovascular disease (Justice-Involved Individuals Cardiovascular Disease Epidemiology - JUSTICE study): a protocol paper.

BACKGROUND: People who have been incarcerated have high rates of cardiovascular risk factors, such as hypertension and smoking, and cardiovascular disease (CVD) is a leading cause of hospitalizations and mortality in this population. Despite this, little is known regarding what pathways mediate the association between incarceration exposure and increased rates of CVD morbidity and especially what incarceration specific factors are associated with this risk. The objective of this study is to better understand CVD risk in people exposed to incarceration and the pathways by which accumulate cardiovascular risk over time. METHODS AND ANALYSIS: The Justice-Involved Individuals Cardiovascular Disease Epidemiology (JUSTICE) study is a prospective cohort study of individuals released from incarceration with known cardiovascular risk factors. We are recruiting 500 individuals within three months after release from jail/prison. At baseline we are assessing traditional risk factors for CVD, including diet, exercise, and smoking, and exposure to incarceration-related policies, psychosocial stress, and self-efficacy. Cardiovascular risk factors are measured at baseline through point of care testing. We are following these individuals for the 12 months following the index release from incarceration with re-evaluation of psychosocial factors and clinical risk factors every 6 months. Using these data, we will estimate the direct and indirect latent effects of incarceration on cardiovascular risk factors and the paths via which these effects are mediated. We will also model the anticipated 10-year burden of CVD incidence, health care use, and mortality associated with incarceration. DISCUSSION: Our study will identify factors associated with CVD risk factor control among people released from incarceration. Our measurement of incarceration-related exposures, psychosocial factors, and clinical measures of cardiovascular risk will allow for identification of unique targets for intervention to modify CVD risk in this vulnerable population.