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Background: The COVID-19 pandemic has evolved through multiple phases characterized by new viral variants, vaccine development, and changes in therapies. It is unknown whether rates of cardiovascular disease (CVD) risk factor profiles and complications have changed over time. Methods: We analyzed the American Heart Association COVID-19 CVD registry, a national multicenter registry of hospitalized adults with active COVID-19 infection. The time period from April 2020 to December 2021 was divided into 3-month epochs, with March 2020 analyzed separately as a potential outlier. Participating centers varied over the study period. Trends in all-cause in-hospital mortality, CVD risk factors, and in-hospital CVD outcomes, including a composite primary outcome of cardiovascular death, cardiogenic shock, new heart failure, stroke, and myocardial infarction, were evaluated across time epochs. Risk-adjusted analyses were performed using generalized linear mixed-effects models. Results: A total of 46 007 patient admissions from 134 hospitals were included (mean patient age 61.8 years, 53% male, 22% Black race). Patients admitted later in the pandemic were younger, more likely obese, and less likely to have existing CVD ( P trend ≤0.001 for each). The incidence of the primary outcome increased from 7.0% in March 2020 to 9.8% in October to December 2021 (risk-adjusted P trend =0.006). This was driven by an increase in the diagnosis of myocardial infarction and stroke ( P trend P trend P trend =0.63). Conclusions: Despite a shifting risk factor profile toward a younger population with lower rates of established CVD, the incidence of diagnosed cardiovascular complications of COVID increased from the onset of the pandemic through December 2021. All-cause mortality decreased during the initial months of the pandemic and thereafter remained consistently high through December 2021.

Background and Purpose: Coronavirus disease 2019 (COVID-19) may be associated with increased risk for ischemic stroke. We present prevalence and characteristics of strokes in patients with laboratory-confirmed severe acute respiratory syndrome coronavirus-2 infection enrolled in the American Heart Association COVID-19 Cardiovascular Disease Registry. Methods: In this quality improvement registry study, we examined demographic, baseline clinical characteristics, and in-hospital outcomes among hospitalized COVID-19 patients. The primary outcomes were ischemic stroke or transient ischemic attack (TIA) and in-hospital death. Results: Among 21 073 patients with COVID-19 admitted at 107 hospitals between January 29, 2020, and November 23, 2020, 160 (0.75%) experienced acute ischemic stroke/TIA (55.3% of all acute strokes) and 129 (0.61%) had other types of stroke. Among nonischemic strokes, there were 44 (15.2%) intracerebral hemorrhages, 33 (11.4%) subarachnoid hemorrhages, 21 (7.3%) epidural/subdural hemorrhages, 2 (0.7%) cerebral venous sinus thromboses, and 24 (8.3%) strokes not otherwise classified. Asians and non-Hispanic Blacks were overrepresented among ischemic stroke/TIA patients compared with their overall representation in the registry, but adjusted odds of stroke did not vary by race. Median time from COVID-19 symptom onset to ischemic stroke was 11.5 days (interquartile range, 17.8); median National Institutes of Health Stroke Scale score was 11 (interquartile range, 17). COVID-19 patients with acute ischemic stroke/TIA had higher prevalence of hypertension, diabetes, and atrial fibrillation compared with those without stroke. Intensive care unit admission and mechanical ventilation were associated with higher odds of acute ischemic stroke/TIA, but older age was not a predictor. In adjusted models, acute ischemic stroke/TIA was not associated with in-hospital mortality. Conclusions: Ischemic stroke risk did not vary by race. In contrast to the association between older age and death from COVID-19, ischemic stroke risk was the highest among middle-aged adults after adjusting for comorbidities and illness severity, suggesting a potential mechanism for ischemic stroke in COVID-19 independent of age-related atherosclerotic pathways.

Background The AHA Registry (American Heart Association COVID‐19 Cardiovascular Disease Registry) captures detailed information on hospitalized patients with COVID‐19. The registry, however, does not capture information on social determinants of health or long‐term outcomes. Here we describe the linkage of the AHA Registry with external data sources, including fee‐for‐service (FFS) Medicare claims, to fill these gaps and assess the representativeness of linked registry patients to the broader Medicare FFS population hospitalized with COVID‐19. Methods and Results We linked AHA Registry records of adults ≥65 years from March 2020 to September 2021 with Medicare FFS claims using a deterministic linkage algorithm and with the American Hospital Association Annual Survey, Rural Urban Commuting Area codes, and the Social Vulnerability Index using hospital and geographic identifiers. We compared linked individuals with unlinked FFS beneficiaries hospitalized with COVID‐19 to assess the representativeness of the AHA Registry. A total of 10 010 (47.0%) records in the AHA Registry were successfully linked to FFS Medicare claims. Linked and unlinked FFS beneficiaries were similar with respect to mean age (78.1 versus 77.9, absolute standardized difference [ASD] 0.03); female sex (48.3% versus 50.2%, ASD 0.04); Black race (15.1% versus 12.0%, ASD 0.09); dual‐eligibility status (26.1% versus 23.2%, ASD 0.07); and comorbidity burden. Linked patients were more likely to live in the northeastern United States (35.7% versus 18.2%, ASD 0.40) and urban/metropolitan areas (83.9% versus 76.8%, ASD 0.18). There were also differences in hospital‐level characteristics between cohorts. However, in‐hospital outcomes were similar (mortality, 23.3% versus 20.1%, ASD 0.08; home discharge, 45.5% versus 50.7%, ASD 0.10; skilled nursing facility discharge, 24.4% versus 22.2%, ASD 0.05). Conclusions Linkage of the AHA Registry with external data sources such as Medicare FFS claims creates a unique and generalizable resource to evaluate long‐term health outcomes after COVID‐19 hospitalization.

Background and Purpose: Studies suggest an increased risk of adverse outcomes among patients with acute ischemic stroke (AIS) and coronavirus disease 2019 (COVID-19). Methods: Using Get With The Guidelines–Stroke, we identified 41 971 patients (AIS/COVID-19: 1143; AIS/no COVID-19: 40 828) with AIS hospitalized between February 4, 2020 and June 29, 2020, from 458 Get With The Guidelines–Stroke hospitals with at least one COVID-19 case and evaluated clinical characteristics, treatment patterns, and outcomes. Results: Compared with patients with AIS/no COVID-19, those with AIS/COVID-19 were younger, more likely to be non-Hispanic Black, Hispanic, or Asian, more likely to present with higher National Institutes of Health Stroke Scale scores, and had greater proportions of large vessel occlusions. Rates of thrombolysis and thrombectomy were similar between the groups. Door to computed tomography (median 55 [18–207] versus 35 [14–99] minutes, P P P =0.002) times were longer in the AIS/COVID-19 cohort. In adjusted models, patients with AIS/COVID-19 had decreased odds of discharge with modified Rankin Scale score of ≤2 (odds ratio, 0.65 [95% CI, 0.52–0.81], P P ConclusionS: This analysis demonstrates younger age, greater stroke severity, longer times to evaluation and treatment, and worse morbidity and mortality in patients with AIS/COVID-19 compared with those with AIS/no COVID-19.

Background: Prior prognostic models for acute decompensated HF (ADHF) have incorporated race as a covariate may not have completely account for the social and biological factors that underlie the racial disparities in outcomes. We developed race-specific models to improve risk prediction and better identify race-specific predictors of mortality in patients with ADHF using machine learning (ML) methods. Methods: Race-specific ML-models for in-hospital mortality were developed and validated in ADHF patients enrolled in the GWTG-HF registry between 2007 to 2020 (14,586 Black and 50,351 Non-Black adults) using over 40 candidate variables. External validation was performed among participants from the ARIC study with ADHF (n=1,115 Black and 2,028 Non-Black adults). The discrimination and calibration was compared with a previously validated risk score and cohort-specific logistic regression (LR) models. The changes in model reclassification performance with addition of zip-code level data of socioeconomic (SES) parameters was also assessed. Results: In the GWTG-HF cohort, the ML models had superior performance in both Black and Non-Black participants compared with the traditional GWTG-HF risk score ( Table ). The superior performance of the ML-model was also observed in the external validation cohort as compared with the other LR models ( Table ). Addition of measures of SES did not meaningfully change the performance but improved the reclassification metrics of the ML-models with net up-classification of risk in Black [NRI = 0.21 (0.07, 0.35)] and down-classification in Non-Black patients [NRI = -0.08 (-0.12, -0.04)]. SES was responsible for 21.7% of the total attributable mortality risk in Black adults compared to 0.4% in Non-Black adults. Conclusion: Race-specific, ML-based mortality models demonstrated superior performance when compared to traditional HF mortality risk models. Socioeconomic distress is an important contributor to risk in Black adults.

Background: In response to the public health emergency created by the coronavirus disease 2019 (COVID-19) pandemic, American Heart Association volunteers and staff aimed to rapidly develop and launch a resource for the medical and research community to expedite scientific advancement through shared learning, quality improvement, and research. In Methods and Results: Participating hospitals are enrolling consecutive hospitalized patients with active COVID-19 disease, regardless of CVD status. This hospital quality improvement program will allow participating hospitals and health systems to evaluate patient-level data including mortality rates, intensive care unit bed days, and ventilator days from individual review of electronic medical records of sequential adult patients with active COVID-19 infection. Participating sites can leverage these data for onsite, rapid quality improvement, and benchmarking versus other institutions. After 9 weeks, >130 sites have enrolled in the program and >4000 records have been abstracted in the national dataset. Additionally, the aggregate dataset will be a valuable data resource for the medical research community. Conclusions: The AHA COVID-19 CVD Registry will support greater understanding of the impact of COVID-19 on cardiovascular disease and will inform best practices for evaluation and management of patients with COVID-19.

On April 1, 2020, the confirmed global burden of COVID-19 was more than 900,000 with 46,413 deaths Despite worldwide calls for social distancing and containment, the incidence of the disease continues to increase COVID-19 is a respiratory tract infection caused by the novel coronavirus (SARS-CoV2) Preliminary analyses from the Chinese Center for Disease Control and Prevention indicated an overall case fatality rate (CFR) of 2 3%;however the CFR was higher in older adults (14 8% in those 80+/- years) and 49% of all critical cases Those with preexisting conditions (cardiovascular disease (CVD), diabetes, chronic respiratory disease, hypertension, and cancer) also had higher CRFs In the United States, 116 million adults have hypertension, 26 million US adults have diabetes mellitus, 9% have preexisting CVD and may therefore be at greater risk of complications or adverse health outcomes from COVID-19 infection