Modeling clinical trajectory status of critically ill COVID-19 patients over time: A method for analyzing discrete longitudinal and ordinal outcomes

Modeling clinical trajectory status of critically ill COVID-19 patients over time: A method for analyzing discrete longitudinal and ordinal outcomes

Early in the COVID-19 pandemic, the World Health Organization stressed the importance of daily clinical assessments of infected patients, yet current approaches frequently consider cross-sectional timepoints, cumulative summary measures, or time-to-event analyses. Statistical methods are available t...

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Bibliographic Details
Main Authors: Michael J. Ward, David J. Douin, Wu Gong, Adit A. Ginde, Catherine L. Hough, Matthew C. Exline, Mark W. Tenforde, William B. Stubblefield, Jay S. Steingrub, Matthew E. Prekker, Akram Khan, D. Clark Files, Kevin W. Gibbs, Todd W. Rice, Jonathan D. Casey, Daniel J. Henning, Jennifer G. Wilson, Samuel M. Brown, Manish M. Patel, Wesley H. Self, Christopher J. Lindsell, for the Influenza and Other Viruses in the Acutely Ill (IVY) Network
Format: Article
Language:English
Published: Cambridge University Press 2022-01-01
Series:Journal of Clinical and Translational Science
Subjects:
COVID
critical illness
proportional odds
longitudinal assessment
Clinical Progression Scale
Online Access:https://www.cambridge.org/core/product/identifier/S2059866122003934/type/journal_article

Internet

https://www.cambridge.org/core/product/identifier/S2059866122003934/type/journal_article

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