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Key Points Question How have trajectories of cardiovascular (CV) mortality among US counties varied over 35 years, and are county-level factors associated with this variation? Findings In this cross-sectional study, cardiovascular mortality declined in all groups from 1980 to 2014 in this cross-sectional analysis of 3133 US counties. Three unique phenogroups based on mortality trajectory were identified, with the difference between high- and low-mortality counties unchanged during the study period, and were associated with social, behavioral, and environmental characteristics at the county level. Meaning These findings suggest that despite an overall decline in CV mortality rates over the past 35 years, differences in health behavior patterns and other societal risk factors are associated with persistent CV mortality disparities at the county level., This cross-sectional study identifies clusters based on cardiovascular mortality trajectory among US counties and county-level social, demographic, environmental, and health-related risk factors that are associated with these clusters., Importance Cardiovascular (CV) mortality has declined for more than 3 decades in the US. However, differences in declines among residents at a US county level are not well characterized. Objective To identify unique county-level trajectories of CV mortality in the US during a 35-year study period and explore county-level factors that are associated with CV mortality trajectories. Design, Setting, and Participants This longitudinal cross-sectional analysis of CV mortality trends used data from 3133 US counties from 1980 to 2014. County-level demographic, socioeconomic, environmental, and health-related risk factors were compiled. Data were analyzed from December 2019 to September 2021. Exposures County-level characteristics, collected from 5 county-level data sets. Main Outcomes and Measures Cardiovascular mortality data were obtained for 3133 US counties from 1980 to 2014 using age-standardized county-level mortality rates from the Global Burden of Disease study. The longitudinal K-means approach was used to identify 3 distinct clusters based on underlying mortality trajectory. Multinomial logistic regression models were constructed to evaluate associations between county characteristics and cluster membership. Results Among 3133 US counties (median, 49.5% [IQR, 48.9%-50.5%] men; 30.7% [IQR, 27.1%-34.4%] older than 55 years; 9.9% [IQR, 4.5%-22.7%] racial minority group [individuals self-identifying as Black or African American, American Indian or Alaska Native, Asian, Native Hawaiian, Pacific Islander, other, or multiple races/ethnicities]), CV mortality declined by 45.5% overall and by 38.4% in high-mortality strata (694 counties), by 45.0% in intermediate-mortality strata (1382 counties), and by 48.3% in low-mortality strata (1057 counties). Counties with the highest mortality in 1980 continued to demonstrate the highest mortality in 2014. Trajectory groups were regionally distributed, with high-mortality trajectory counties focused in the South and in portions of Appalachia. Low- vs high-mortality groups varied significantly in demographic (racial minority group proportion, 7.6% [IQR, 4.1%-14.5%]) vs 23.9% [IQR, 6.5%-40.8%]) and socioeconomic characteristics such as high-school education (9.4% [IQR, 7.3%-12.6%] vs 20.1% [IQR, 16.1%-23.2%]), poverty rates (11.4% [IQR, 8.8%-14.6%] vs 20.6% [IQR, 17.1%-24.4%]), and violent crime rates (161.5 [IQR, 89.0-262.4] vs 272.8 [IQR, 155.3-431.3] per 100 000 population). In multinomial logistic regression, a model incorporating demographic, socioeconomic, environmental, and health characteristics accounted for 60% of the variance in the CV mortality trajectory (R2 = 0.60). Sociodemographic factors such as racial minority group proportion (odds ratio [OR], 1.70 [95% CI, 1.35-2.14]) and educational attainment (OR, 6.17 [95% CI, 4.55-8.36]) and health behaviors such as smoking (OR for high vs low, 2.04 [95% CI, 1.58-2.64]) and physical inactivity (OR, 3.74 [95% CI, 2.83-4.93]) were associated with the high-mortality trajectory. Conclusions and Relevance Cardiovascular mortality declined in all subgroups during the 35-year study period; however, disparities remained unchanged during that time. Disparate trajectories were associated with social and behavioral risks. Health policy efforts across multiple domains, including structural and public health targets, may be needed to reduce existing county-level cardiovascular mortality disparities.

Key Points Question What factors are associated with observed trends in the in-hospital mortality rates in the United States during the first 9 months of the COVID-19 pandemic? Findings In this cohort study of 20 736 patients, in-hospital mortality rates decreased in the US between March and November 2020, even after accounting for the changing mix in patient age, sex, comorbidities, and disease severity at the time of admission. Hospital and intensive care unit length of stay and use of mechanical ventilation decreased over time, whereas the use of glucocorticoids and remdesivir increased. Meaning Changes in age, sex, comorbidities, and disease severity among patients with COVID-19 do not fully explain the decrease in the in-hospital mortality rates observed during the first 9 months of the COVID-19 pandemic., Importance In-hospital mortality rates from COVID-19 are high but appear to be decreasing for selected locations in the United States. It is not known whether this is because of changes in the characteristics of patients being admitted. Objective To describe changing in-hospital mortality rates over time after accounting for individual patient characteristics. Design, Setting, and Participants This was a retrospective cohort study of 20 736 adults with a diagnosis of COVID-19 who were included in the US American Heart Association COVID-19 Cardiovascular Disease Registry and admitted to 107 acute care hospitals in 31 states from March through November 2020. A multiple mixed-effects logistic regression was then used to estimate the odds of in-hospital death adjusted for patient age, sex, body mass index, and medical history as well as vital signs, use of supplemental oxygen, presence of pulmonary infiltrates at admission, and hospital site. Main Outcomes and Measures In-hospital death adjusted for exposures for 4 periods in 2020. Results The registry included 20 736 patients hospitalized with COVID-19 from March through November 2020 (9524 women [45.9%]; mean [SD] age, 61.2 [17.9] years); 3271 patients (15.8%) died in the hospital. Mortality rates were 19.1% in March and April, 11.9% in May and June, 11.0% in July and August, and 10.8% in September through November. Compared with March and April, the adjusted odds ratios for in-hospital death were significantly lower in May and June (odds ratio, 0.66; 95% CI, 0.58-0.76; P, This cohort study of patients included in the US American Heart Association COVID-19 Cardiovascular Disease Registry evaluates whether any changes in the in-hospital COVID-19 mortality rates during the first 9 months of the pandemic are associated with individual characteristics of patients with COVID-19.

The association of the Hospital Readmission Reduction Program (HRRP) with reductions in racial disparities in 30-day outcomes for myocardial infarction (MI), is unknown, including whether this varies by HRRP hospital penalty status.To assess temporal trends in 30-day readmission and mortality rates among black and nonblack patients discharged after hospitalization for acute MI at low-performing and high-performing hospitals, as defined by readmission penalty status after HRRP implementation.This observational cohort analysis used data from the multicenter National Cardiovascular Data Registry Chest Pain-MI Registry centers that were subject to the first cycle of HRRP, between January 1, 2008, and November 30, 2016. All patients hospitalized with MI who were included in National Cardiovascular Data Registry Chest Pain-MI Registry were included in the analysis. Data were analyzed from April 2018 to September 2019.Hospital performance category and race (black compared with nonblack patients). Centers were classified as high performing or low performing based on the excess readmission ratio (predicted to expected 30-day risk adjusted readmission rate) for MI during the first HRRP cycle (in October 2012).Thirty-day all-cause readmission and mortality rates.Among 753 hospitals that treated 155 397 patients with acute MI (of whom 11 280 [7.3%] were black), 399 hospitals (53.0%) were high performing. Thirty-day readmission rates declined over time in both black and nonblack patients (annualized 30-day readmission rate: 17.9% vs 20.8%). Black (compared with nonblack) race was associated with higher unadjusted odds of 30-day readmission in both low-performing and high-performing centers (odds ratios: before HRRP: low-performing hospitals, 1.14 [95% CI, 1.03-1.26]; P = .01; high-performing hospitals, 1.17 [95% CI, 1.04-1.32]; P = .01; after HRRP: low-performing hospitals, 1.23 [95% CI, 1.13-1.34]; P .001; high-performing hospitals, 1.25 [95% CI, 1.12-1.39]; P .001). However, these racial differences were not significant after adjustment for patient characteristics. The 30-day mortality rates declined significantly over time in nonblack patients, with stable (nonsignificant) temporal trends among black patients. Adjusted associations between race and 30-day mortality showed that 30-day mortality rates were significantly lower among black (compared with nonblack) patients in the low-performing hospitals (odds ratios: pre-HRRP, 0.79 [95% CI, 0.63-0.97]; P = .03; post-HRRP, 0.80 [95% CI, 0.68-0.95]; P = .01) but not in high-performing hospitals. Finally, the association between race and 30-day outcomes did not vary after the HRRP period began in either high-performing or low-performing hospitals.In this analysis, 30-day readmission rates among patients with MI declined over time for both black and nonblack patients. Differences in race-specific 30-day readmission rates persisted but appeared to be attributable to patient-level factors. The 30-day mortality rates have declined for nonblack patients and remained stable among black patients. Implementation of the HRRP was not associated with improvement or worsening of racial disparities in readmission and mortality rates.

Importance The US Centers for Medicare and Medicaid Services Hospital Readmissions Reduction Program penalizes hospitals with higher-than-expected risk-adjusted 30-day readmission rates (excess readmission ratio [ERR] > 1) after acute myocardial infarction (MI). However, the association of ERR with MI care processes and outcomes are not well established. Objective To evaluate the association between ERR for MI with in-hospital process of care measures and 1-year clinical outcomes. Design, Setting, and Participants Observational analysis of hospitalized patients with MI from National Cardiovascular Data Registry/Acute Coronary Treatment and Intervention Outcomes Network Registry–Get With the Guidelines centers subject to the first cycle of the Hospital Readmissions Reduction Program between July 1, 2008, and June 30, 2011. Exposures The ERR for MI (MI-ERR) in 2011. Main Outcomes and Measures Adherence to process of care measures during index hospitalization in the overall study population and risk of the composite outcome of mortality or all-cause readmission within 1 year of discharge and its individual components among participants with available Centers for Medicare and Medicaid Services–linked data. Results The median ages of patients in the MI-ERR greater than 1 and tertiles 1, 2, and 3 of the MI-ERR greater than 1 groups were 64, 63, 64, and 63 years, respectively. Among 380 hospitals that treated a total of 176 644 patients with MI during the study period, 43% had MI-ERR greater than 1. The proportions of patients of black race, those with heart failure signs at admission, and bleeding complications increased with higher MI-ERR. There was no significant association between adherence to MI performance measures and MI-ERR (adjusted odds ratio, 0.94; 95% CI, 0.81-1.08, per 0.1-unit increase in MI-ERR for overall defect-free care). Among the 51 453 patients with 1-year outcomes data available, higher MI-ERR was associated with higher adjusted risk of the composite outcome and all-cause readmission within 1 year of discharge. This association was largely driven by readmissions early after discharge and was not significant in landmark analyses beginning 30 days after discharge. The MI-ERR was not associated with risk for mortality within 1 year of discharge in the overall and 30-day landmark analyses. Conclusions and Relevance During the first cycle of the Hospital Readmissions Reduction Program, participating hospitals’ risk-adjusted 30-day readmission rates following MI were not associated with in-hospital quality of MI care or clinical outcomes occurring after the first 30 days after discharge.

RESULTS Overall, 31.8% of TTEs resulted in an active change in care; 46.9%, continuation of current care; and 21.3%, no change in care. By 2011 AUC, 91.8% of TTEs were appropriate; 4.3%, inappropriate; and 3.9%, uncertain. We detected no statistically significant difference between appropriate and inappropriate TTEs in the proportion of TTEs that led to active change in care (32.2% vs 21.7%; P = .29). CONCLUSIONS AND RELEVANCE Although 9 in 10 TTEs were appropriate by 2011 AUC, fewer than 1 in 3 TTEs resulted in an active change in care, nearly half resulted in continuation of current care, and slightly more than 1 in 5 resulted in no change in care. The low rate of active change in care (31.8%) among TTEs mostly classified as appropriate (91.8%) highlights the need for a better method to optimize TTE utilization to use limited health care resources efficiently while providing high-quality care.

Context Detectable levels of cardiac troponin T (cTnT) are strongly associated with structural heart disease and increased risk of death and adverse cardiovascular events; however, cTnT is rarely detectable in the general population using standard assays. Objectives TodeterminetheprevalenceanddeterminantsofdetectablecTnTinthepopu- lationusinganewhighlysensitiveassayandtoassesswhethercTnTlevelsmeasuredwith the new assay associate with pathological cardiac phenotypes and subsequent mortality. Design, Setting, and Participants Cardiac troponin T levels were measured using both the standard and the highly sensitive assays in 3546 individuals aged 30 to 65 years enrolled between 2000 and 2002 in the Dallas Heart Study, a multiethnic, popu- lation-based cohort study. Mortality follow-up was complete through 2007. Partici- pants were placed into 5 categories based on cTnT levels. Main Outcome Measures Magnetic resonance imaging measurements of car- diac structure and function and mortality through a median of 6.4 (interquartile range, 6.0-6.8) years of follow-up. Results InDallasCounty,theprevalenceofdetectablecTnT(0.003ng/mL)was25.0% (95% confidence interval (CI), 22.7%-27.4%) with the highly sensitive assay vs 0.7% (95% CI, 0.3%-1.1%) with the standard assay. Prevalence was 37.1% (95% CI, 33.3%- 41.0%)inmenvs12.9%(95%CI,10.6%-15.2%)inwomenand14.0%(95%CI,11.2%- 16.9%)inparticipantsyoungerthan40yearsvs57.6%(95%CI,47.0%-68.2%)inthose 60 years and older. Prevalence of left ventricular hypertrophy increased from 7.5% (95% CI,6.4%-8.8%)inthelowestcTnTcategory(0.003ng/mL)to48.1%(95%CI,36.7%- 59.6%) in the highest (0.014 ng/mL) (P.001); prevalence of left ventricular systolic dysfunctionandchronickidneydiseasealsoincreasedacrosscategories(P.001foreach). During a median follow-up of 6.4 years, there were 151 total deaths, including 62 car- diovascular disease deaths. All-cause mortality increased from 1.9% (95% CI, 1.5%- 2.6%) to 28.4% (95% CI, 21.0%-37.8%) across higher cTnT categories (P.001). Af- ter adjustment for traditional risk factors, C-reactive protein level, chronic kidney disease, and N-terminal pro-brain-type natriuretic peptide level, cTnT category remained inde- pendently associated with all-cause mortality (adjusted hazard ratio, 2.8 (95% CI, 1.4- 5.2) in the highest category). Adding cTnT categories to the fully adjusted mortality model modestlyimprovedmodelfit(P=.02)andtheintegrateddiscriminationindex(0.010(95% CI, 0.002-0.018); P=.01). Conclusion In this population-based cohort, cTnT detected with a highly sensitive assay was associated with structural heart disease and subsequent risk for all-cause mortality.