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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Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: 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
Μορφή: Άρθρο
Γλώσσα:English
Έκδοση: Cambridge University Press 2022-01-01
Σειρά:Journal of Clinical and Translational Science
Θέματα:
COVID
critical illness
proportional odds
longitudinal assessment
Clinical Progression Scale
Διαθέσιμο Online:https://www.cambridge.org/core/product/identifier/S2059866122003934/type/journal_article

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

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