No abstract

IMPORTANCE Black and Hispanic populations have higher rates of coronavirus disease 2019 hospitalization and mortality than White populations but lower in-hospital case-fatality rates. The extent to which neighborhood characteristics and comorbidity explain these disparities is unclear. Outcomes in Asian American populations have not been explored. OBJECTIVETo compare COVID-19 outcomes based on race and ethnicity and assess the association of any disparities with comorbidity and neighborhood characteristics. DESIGN, SETTING, AND PARTICIPANTSThis retrospective cohort study was conducted within the New York University Langone Health system, which includes over 260 outpatient practices and 4 acute care hospitals. All patients within the system's integrated health record who were tested for severe acute respiratory syndrome coronavirus 2 between March 1, 2020, and April 8, 2020, were identified and followed up through May 13, 2020. Data were analyzed in June 2020. Among 11 547 patients tested, outcomes were compared by race and ethnicity and examined against differences by age, sex, body mass index, comorbidity, insurance type, and neighborhood socioeconomic status.EXPOSURES Race and ethnicity categorized using self-reported electronic health record data (ie, non-Hispanic White, non-Hispanic Black, Hispanic, Asian, and multiracial/other patients). MAIN OUTCOMES AND MEASURESThe likelihood of receiving a positive test, hospitalization, and critical illness (defined as a composite of care in the intensive care unit, use of mechanical ventilation, discharge to hospice, or death). RESULTSAmong 9722 patients (mean [SD] age, 50.7 [17.5] years; 58.8% women), 4843 (49.8%) were positive for COVID-19; 2623 (54.2%) of those were admitted for hospitalization (1047 [39.9%] White, 375 [14.3%] Black, 715 [27.3%] Hispanic, 180 [6.9%] Asian, 207 [7.9%] multiracial/other). In fully adjusted models, Black patients (odds ratio [OR], 1.3; 95% CI, 1.2-1.6) and Hispanic patients (OR, 1.5; 95% CI, 1.3-1.7) were more likely than White patients to test positive. Among those who tested positive, odds of hospitalization were similar among White, Hispanic, and Black patients, but higher among Asian (OR, 1.6, 95% CI, 1.1-2.3) and multiracial patients (OR, 1.4; 95% CI, 1.0-1.9) compared with White patients. Among those hospitalized, Black patients were less likely than White patients to have severe illness (OR, 0.6; 95% CI, 0.4-0.8) and to die or be discharged to hospice (hazard ratio, 0.7; 95% CI, 0.6-0.9). CONCLUSIONS AND RELEVANCEIn this cohort study of patients in a large health system in New York City, Black and Hispanic patients were more likely, and Asian patients less likely, than White patients to test positive; once hospitalized, Black patients were less likely than White patients to have (continued) Key Points Question Do outcomes among patients with coronavirus disease 2019 (COVID-19) differ by race/ethnicity, and are observed disparities associated with comorbidity and neighborhood characteristics? Findings This cohort study including ...

Background Type 2 myocardial infarction (MI) is defined as myocardial necrosis (myonecrosis) due to an imbalance in supply and demand with clinical evidence of ischemia. Some clinical scenarios of supply-demand mismatch predispose to myonecrosis but limit the identification of symptoms and ECG changes referable to ischemia; therefore, the MI definition may not be met. Factors that predispose to type 2 MI and myonecrosis without definite MI, approaches to treatment, and outcomes remain poorly characterized. Methods Patients admitted to an academic medical center with an ICD-9 diagnosis of secondary myocardial ischemia or non-primary diagnosis of non-ST-elevation MI were retrospectively reviewed. Cases were classified as either MI (n=255) or myonecrosis without definite MI (n=220) based on reported symptoms, ischemic ECG changes, and new wall motion abnormalities. Results Conditions associated with type 2 MI or myonecrosis included non-cardiac surgery (38%), anemia or bleeding requiring transfusion (32%), sepsis (31%), tachyarrhythmia (23%), hypotension (22%), respiratory failure (23%), and severe hypertension (8%). Inpatient mortality was 5%, with no difference between patients with MI and those with myonecrosis (6% vs. 5%, p=0.41). At discharge, only 43% of patients received aspirin and statin therapy. Conclusions Type 2 MI and myonecrosis occur frequently in the setting of supply-demand mismatch due to non-cardiac surgery, sepsis, or anemia. Myonecrosis without definite MI is associated with similar in-hospital mortality as type 2 MI; both groups warrant further workup for cardiovascular disease. Antiplatelet and statin prescriptions were infrequent at discharge, reflecting physician uncertainty about the role of secondary prevention in these patients.

Background In response to COVID-19, the informatics community united to aggregate as much clinical data as possible to characterize this new disease and reduce its impact through collaborative analytics. The National COVID Cohort Collaborative (N3C) is now the largest publicly available HIPAA limited dataset in US history with over 6.4 million patients and is a testament to a partnership of over 100 organizations. Methods We developed a pipeline for ingesting, harmonizing, and centralizing data from 56 contributing data partners using four federated Common Data Models. N3C Data quality (DQ) review involves both automated and manual procedures. In the process, several DQ heuristics were discovered in our centralized context, both within the pipeline and during downstream project-based analysis. Feedback to the sites led to many local and centralized DQ improvements. Results Beyond well-recognized DQ findings, we discovered 15 heuristics relating to source CDM conformance, demographics, COVID tests, conditions, encounters, measurements, observations, coding completeness and fitness for use. Of 56 sites, 37 sites (66%) demonstrated issues through these heuristics. These 37 sites demonstrated improvement after receiving feedback. Discussion We encountered site-to-site differences in DQ which would have been challenging to discover using federated checks alone. We have demonstrated that centralized DQ benchmarking reveals unique opportunities for data quality improvement that will support improved research analytics locally and in aggregate. Conclusion By combining rapid, continual assessment of DQ with a large volume of multi-site data, it is possible to support more nuanced scientific questions with the scale and rigor that they require.

Background Morbidity and death due to coronavirus disease 2019 (COVID‐19) experienced by older adults in nursing homes have been well described, but COVID‐19's impact on community‐living older adults is less studied. Similarly, the previous ambulatory care experience of such patients has rarely been considered in studies of COVID‐19 risks and outcomes. Methods To investigate the relationship of advanced age (65+), on risk factors associated with COVID‐19 outcomes in community‐living elders, we identified an electronic health records cohort of older patients aged 65+ with laboratory‐confirmed COVID‐19 with and without an ambulatory care visit in the past 24 months ( n = 47,219) in the New York City (NYC) academic medical institutions and the NYC public hospital system from January 2020 to February 2021. The main outcomes are COVID‐19 hospitalization; severe outcomes/Intensive care unit (ICU), intubation, dialysis, stroke, in‐hospital death), and in‐hospital death. The exposures include demographic characteristics, and those with ambulatory records, comorbidities, frailty, and laboratory results. Results The 31,770 patients with an ambulatory history had a median age of 74 years; were 47.4% male, 24.3% non‐Hispanic white, 23.3% non‐Hispanic black, and 18.4% Hispanic. With increasing age, the odds ratios and attributable fractions of sex, race–ethnicity, comorbidities, and biomarkers decreased except for dementia and frailty (Hospital Frailty Risk Score). Patients without ambulatory care histories, compared to those with, had significantly higher adjusted rates of COVID‐19 hospitalization and severe outcomes, with strongest effect in the oldest group. Conclusions In this cohort of community‐dwelling older adults, we provided evidence of age‐specific risk factors for COVID‐19 hospitalization and severe outcomes. Future research should explore the impact of frailty and dementia in severe COVID‐19 outcomes in community‐living older adults, and the role of engagement in ambulatory care in mitigating severe disease.