Laboratory findings associated with severe illness and mortality among hospitalized individuals with coronavirus disease 2019 in Eastern Massachusetts
Abstract
Importance
The coronavirus disease 2019 (COVID-19) pandemic has placed unprecedented stress on health systems across the world, and reliable estimates of risk for adverse hospital outcomes are needed.
Objective
To quantify admission laboratory and comorbidity features associated with critical illness and mortality risk across 6 Eastern Massachusetts hospitals.
Design
Retrospective cohort study using hospital course, prior diagnoses, and laboratory values.
Setting
Emergency department and inpatient settings from 2 academic medical centers and 4 community hospitals.
Participants
All individuals with hospital admission and positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by PCR testing across these 6 hospitals through June 5, 2020.
Exposure
Coronavirus 2 (SARS-CoV-2).
Main Outcome Measures
Severe illness defined by ICU admission, mechanical ventilation, or death.
Results
Among 2,511 hospitalized individuals who tested positive for SARS-CoV-2 (of whom 50.9% were male, 53.9% white, and 27.0% Hispanic, with mean age 62.6 years), 215 (8.6%) were admitted to the ICU, 164 (6.5%) required mechanical ventilation, and 292 (11.6%) died. L1-regression models developed in 3 of these hospitals yielded area under ROC curve (AUC) of 0.807 for severe illness and 0.847 for mortality in the 3 held-out hospitals. In total, 212/292 (78%) of the deaths occurred in the highest-risk mortality quintile.
Conclusions and Relevance
In this cohort, specific admission laboratory studies in concert with sociodemographic features and prior diagnosis facilitated risk stratification among individuals hospitalized for COVID-19.
Funding
1R56MH115187-01
Trial Registration
None
Key Points
Question
How well can sociodemographic features, laboratory values, and comorbidities of individuals hospitalized with coronavirus disease 2019 (COVID-19) in Eastern Massachusetts through June 5, 2020 predict severe illness course?
Findings
In this cohort study of 2,511 hospitalized individuals positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by PCR who were admitted to one of six hospitals, 215 (8.6%) were admitted to the ICU, 164 (6.5%) required mechanical ventilation, and 292 (11.6%) died. In a risk prediction model, 212 (78%) deaths occurred in the top mortality-risk quintile.
Meaning
Simple prediction models may assist in risk stratification among hospitalized COVID-19 patients.
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