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Open Access
CC BY 4.0 · ACI open 2022; 06(01): e34-e38
DOI: 10.1055/s-0042-1749193
Original Article

Vitals are Vital: Simpler Clinical Data Model Predicts Decompensation in COVID-19 Patients

Joanna Schneider Cavalier
1   Department of Medicine, Duke University, Durham, North Carolina, United States
,
Cara L. O'Brien
1   Department of Medicine, Duke University, Durham, North Carolina, United States
,
Benjamin A. Goldstein
2   Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, United States
,
Congwen Zhao
2   Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, United States
,
Armando Bedoya
1   Department of Medicine, Duke University, Durham, North Carolina, United States
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Abstract

Objective Several risk scores have been developed and tested on coronavirus disease 2019 (COVID-19) patients to predict clinical decompensation. We aimed to compare an institutional, automated, custom-built early warning score (EWS) to the National Early Warning Score (NEWS) in COVID-19 patients.

Methods A retrospective cohort analysis was performed on patients with COVID-19 infection who were admitted to an intermediate ward from March to December 2020. A machine learning–based customized EWS algorithm, which incorporates demographics, laboratory values, vital signs, and comorbidities, and the NEWS, which uses vital signs only, were calculated at 12-hour intervals. These patients were retrospectively assessed for decompensation in the subsequent 12 or 24 hours, defined as death or transfer to an intensive care unit.

Results Of 709 patients, 112 (15.8%) had a decompensation event. Using the custom EWS, decompensation within 12 and 24 hours was predicted with areas under the receiver operating curve (AUC) of 0.81 and 0.79, respectively. The NEWS score applied to the same population yielded AUCs of 0.83 and 0.81, respectively. The 24-hour negative predictive values (NPV) of the NEWS and EWS in patients identified as low risk were 99.6 and 99.2%, respectively.

Conclusion The NEWS score performs as well as a customized EWS in COVID-19 patients, demonstrating the significance of vital signs in predicting outcomes. The relatively high positive predictive value and NPV of both scores are indispensable for optimally allocating clinical resources. In this relatively young, healthy population, a more complex score incorporating electronic health record data beyond vital signs does not add clinical benefit.

Keywords

COVID-19 - 2019 novel coronavirus - early warning score - predictive modeling - decompensation

Protection of Human and Animal Subjects

Given the retrospective nature of this work using deidentified clinical data, this work was exempt from human subjects' protections.




Publikationsverlauf

Eingereicht: 31. Mai 2021

Angenommen: 03. Februar 2022

Artikel online veröffentlicht:
27. Mai 2022

© 2022. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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