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Laboratory Findings Associated With Severe Illness and Mortality Among Hospitalized Individuals With Coronavirus Disease 2019 in Eastern Massachusetts

Educational Objective
To identify the key insights or developments described in this article
1 Credit CME
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 a severe illness course?

Findings  In this cohort study of 2511 hospitalized individuals positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by polymerase chain reaction who were admitted to 1 of 6 hospitals, 215 (8.6%) were admitted to the instensive care unit, 164 (6.5%) required mechanical ventilation, and 292 (11.6%) died. In a risk prediction model, 212 deaths (78%) occurred in the top mortality-risk quintile.

Meaning  Simple prediction models may assist in risk stratification among hospitalized patients with COVID-19.

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, Setting, and Participants  Retrospective cohort study of all individuals admitted to the hospital who tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by polymerase chain reaction across these 6 hospitals through June 5, 2020, using hospital course, prior diagnoses, and laboratory values in emergency department and inpatient settings from 2 academic medical centers and 4 community hospitals. The data were extracted on June 11, 2020, and the analysis was conducted from June to July 2020.

Exposures  SARS-CoV-2.

Main Outcomes and Measures  Severe illness defined by admission to intensive care unit, mechanical ventilation, or death.

Results  Of 2511 hospitalized individuals who tested positive for SARS-CoV-2 (of whom 50.9% were male, 53.9% White, and 27.0% Hispanic, with a mean [SD ]age of 62.6 [19.0] years), 215 (8.6%) were admitted to the intensive care unit, 164 (6.5%) required mechanical ventilation, and 292 (11.6%) died. L1-regression models developed in 3 of these hospitals yielded an area under the receiver operating characteristic curve of 0.807 for severe illness and 0.847 for mortality in the 3 held-out hospitals. In total, 212 of 292 deaths (72.6%) 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.

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CME Disclosure Statement: Unless noted, all individuals in control of content reported no relevant financial relationships. If applicable, all relevant financial relationships have been mitigated.

Article Information

Accepted for Publication: September 2, 2020.

Published: October 30, 2020. doi:10.1001/jamanetworkopen.2020.23934

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2020 Castro VM et al. JAMA Network Open.

Corresponding Author: Roy H. Perlis, MD, MSc, Center for Quantitative Health, Division of Clinical Research, Massachusetts General Hospital, 185 Cambridge St, 6th Floor, Boston, MA 02114 (rperlis@mgh.harvard.edu).

Author Contributions: Dr Perlis had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: All authors.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Castro, McCoy.

Administrative, technical, or material support: All authors.

Supervision: Perlis.

Conflict of Interest Disclosures: Dr Perlis has received consulting fees from Burrage Capital, Genomind, RID Ventures, and Takeda. He holds equity in Outermost Therapeutics and Psy Therapeutics. Dr McCoy has received research funding from the Stanley Center at the Broad Institute, the Brain and Behavior Research Foundation, National Institute of Mental Health, National Human Genome Research Institute Home, and Telefonica Alfa. No other disclosures were reported.

Disclaimer: Dr Perlis is an Associate Editor at JAMA Network Open; however, he had no role in the editorial review or decision to accept the manuscript for publication.

Additional Contributions: The authors would like to thank the Partners Research Patient Data Registry and Analytics Enclave team members for their support in making up-to-date electronic health record data available for this research. No financial compensation was provided specifically for this work.

AMA CME Accreditation Information

Credit Designation Statement: The American Medical Association designates this Journal-based CME activity activity for a maximum of 1.00  AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Successful completion of this CME activity, which includes participation in the evaluation component, enables the participant to earn up to:

  • 1.00 Medical Knowledge MOC points in the American Board of Internal Medicine's (ABIM) Maintenance of Certification (MOC) program;;
  • 1.00 Self-Assessment points in the American Board of Otolaryngology – Head and Neck Surgery’s (ABOHNS) Continuing Certification program;
  • 1.00 MOC points in the American Board of Pediatrics’ (ABP) Maintenance of Certification (MOC) program;
  • 1.00 Lifelong Learning points in the American Board of Pathology’s (ABPath) Continuing Certification program; and
  • 1.00 credit toward the CME [and Self-Assessment requirements] of the American Board of Surgery’s Continuous Certification program

It is the CME activity provider's responsibility to submit participant completion information to ACCME for the purpose of granting MOC credit.

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