A phenome-wide association study (PheWAS) of COVID-19 outcomes by race using the electronic health records data in Michigan Medicine (preprint)

Blacks/African Americans are overrepresented in the number of hospitalizations and deaths from COVID-19 in the United States, which could be explained through differences in the prevalence of existing comorbidities. We performed a disease-disease phenome-wide association study (PheWAS) using data representing 5,698 COVID-19 patients from a large academic medical center, stratified by race. We explore the association of 1,043 pre-occurring conditions with several COVID-19 outcomes: testing positive, hospitalization, ICU admission, and mortality. Obesity, iron deficiency anemia and type II diabetes were associated with susceptibility in the full cohort, while ill-defined descriptions/complications of heart disease and stage III chronic kidney disease were associated among non-Hispanic White (NHW) and non-Hispanic Black/African American (NHAA) patients, respectively. The top phenotype hits in the full, NHW, and NHAA cohorts for hospitalization were acute renal failure, hypertension, and insufficiency/arrest respiratory failure, respectively. Suggestive relationships between respiratory issues and COVID-19-related ICU admission and mortality were observed, while circulatory system diseases showed stronger association in NHAA patients. We were able to replicate some known comorbidities related to COVID-19 outcomes while discovering potentially unknown associations, such as endocrine/metabolic conditions related to hospitalization and mental disorders related to mortality, for future validation. We provide interactive PheWAS visualization for broader exploration.

COVID-19 outcomes, risk factors and associations by race: a comprehensive analysis using electronic health records data in Michigan Medicine (preprint)

Structured AbstractO_ST_ABSImportanceC_ST_ABSBlacks/African-Americans are overrepresented in the number of COVID-19 infections, hospitalizations and deaths. Reasons for this disparity have not been well-characterized but may be due to underlying comorbidities or sociodemographic factors. ObjectiveTo systematically determine patient characteristics associated with racial/ethnic disparities in COVID-19 outcomes. DesignA retrospective cohort study with comparative control groups. SettingPatients tested for COVID-19 at University of Michigan Medicine from March 10, 2020 to April 22, 2020. Participants5,698 tested patients and two sets of comparison groups who were not tested for COVID-19: randomly selected unmatched controls (n = 7,211) and frequency-matched controls by race, age, and sex (n = 13,351). Main Outcomes and MeasuresWe identified factors associated with testing and testing positive for COVID-19, being hospitalized, requiring intensive care unit (ICU) admission, and mortality (in/out-patient during the time frame). Factors included race/ethnicity, age, smoking, alcohol consumption, healthcare utilization, and residential-level socioeconomic characteristics (SES; i.e., education, unemployment, population density, and poverty rate). Medical comorbidities were defined from the International Classification of Diseases (ICD) codes, and were aggregated into a comorbidity score. ResultsOf 5,698 patients, (median age, 47 years; 38% male; mean BMI, 30.1), the majority were non-Hispanic Whites (NHW, 59.2%) and non-Hispanic Black/African-Americans (NHAA, 17.2%). Among 1,119 diagnosed, there were 41.2% NHW and 37.4% NHAA; 44.8% hospitalized, 20.6% admitted to ICU, and 3.8% died. Adjusting for age, sex, and SES, NHAA were 1.66 times more likely to be hospitalized (95% CI, 1.09-2.52; P=.02), 1.52 times more likely to enter ICU (95% CI, 0.92-2.52; P=.10). In addition to older age, male sex and obesity, high population density neighborhood (OR, 1.27 associated with one SD change [95% CI, 1.20-1.76]; P=.02) was associated with hospitalization. Pre-existing kidney disease led to 2.55 times higher risk of hospitalization (95% CI, 1.62-4.02; P

Validating a Widely Implemented Deterioration Index Model Among Hospitalized COVID-19 Patients (preprint)

IntroductionThe Epic Deterioration Index (EDI) is a proprietary prediction model implemented in over 100 U.S. hospitals that was widely used to support medical decision-making during the COVID-19 pandemic. The EDI has not been independently evaluated, and other proprietary models have been shown to be biased against vulnerable populations. MethodsWe studied adult patients admitted with COVID-19 to non-ICU care at a large academic medical center from March 9 through May 20, 2020. We used the EDI, calculated at 15-minute intervals, to predict a composite outcome of ICU-level care, mechanical ventilation, or in-hospital death. In a subset of patients hospitalized for at least 48 hours, we also evaluated the ability of the EDI to identify patients at low risk of experiencing this composite outcome during their remaining hospitalization. ResultsAmong 392 COVID-19 hospitalizations meeting inclusion criteria, 103 (26%) met the composite outcome. Median age of the cohort was 64 (IQR 53-75) with 168 (43%) African Americans and 169 (43%) women. Area under the receiver-operating-characteristic curve (AUC) of the EDI was 0.79 (95% CI 0.74-0.84). EDI predictions did not differ by race or sex. When exploring clinically-relevant thresholds of the EDI, we found patients who met or exceeded an EDI of 68.8 made up 14% of the study cohort and had a 74% probability of experiencing the composite outcome during their hospitalization with a median lead time of 24 hours from when this threshold was first exceeded. Among the 286 patients hospitalized for at least 48 hours who had not experienced the composite outcome, 14 (13%) never exceeded an EDI of 37.9, with a negative predictive value of 90% and a sensitivity above this threshold of 91%. ConclusionWe found the EDI identifies small subsets of high- and low-risk COVID-19 patients with fair discrimination. We did not find evidence of bias by race or sex. These findings highlight the importance of independent evaluation of proprietary models before widespread operational use among COVID-19 patients.

Survival After In-Hospital Cardiac Arrest In Critically Ill Patients: Implications For The Covid-19 Pandemic? (preprint)

The coronavirus disease 2019 (COVID-19) outbreak is placing a considerable strain on U.S. healthcare systems. Due to presumptions of poor outcomes in such critically ill patients, many hospitals have started considering a universal do-not-resuscitate order in patients with confirmed Covid-19 given a limited supply of intensive care unit (ICU) beds and the potential risk of transmission of infection to healthcare workers during resuscitation. However, empirical data on survival of cardiac arrest in Covid-19 patients are unavailable at this time. To inform this debate, we report survival outcomes following cardiopulmonary resuscitation in a cohort of similar critically ill patients with pneumonia or sepsis who were receiving mechanical ventilation in an ICU at the time of arrest. The probability of survival without severe neurological disability (CPC of 1 or 2) ranged from less than 3% to over 22% across key patient subgroups, For patients with an initial rhythm of asystole or PEA, who were also receiving vasopressors at the time of arrest, fewer than 10% were discharged without severe neurological disability (CPC of 1 or 2), and this number dropped to less than 3% in patients over 80 years old. In contrast, survival rates were much higher in younger patients, patients with an initial rhythm of VF or pulseless VT, and in patients receiving ventilatory support without vasopressors. Our findings suggest caution in universal resuscitation policies. Even in a cohort of critically ill patients on mechanical ventilation, survival outcomes following in-hospital resuscitation were not uniformly poor and varied markedly depending on age, co-morbidities and illness severity. We believe that these data can help inform discussions among patients, providers and hospital leaders regarding resuscitation policies and goals of care in the context of the COVID-19 pandemic.