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Modeling clinical trajectory status of critically ill COVID-19 patients over time: A method for analyzing discrete longitudinal and ordinal outcomes. Journal of clinical and translational science Ward, M. J., Douin, D. J., Gong, W., Ginde, A. A., Hough, C. L., Exline, M. C., Tenforde, M. W., Stubblefield, W. B., Steingrub, J. S., Prekker, M. E., Khan, A., Files, D. C., Gibbs, K. W., Rice, T. W., Casey, J. D., Henning, D. J., Wilson, J. G., Brown, S. M., Patel, M. M., Self, W. H., Lindsell, C. J. 2022; 6 (1): e61

Abstract

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 that make use of the rich information content of longitudinal assessments. We demonstrate the use of a multistate transition model to assess the dynamic nature of COVID-19-associated critical illness using daily evaluations of COVID-19 patients from 9 academic hospitals. We describe the accessibility and utility of methods that consider the clinical trajectory of critically ill COVID-19 patients.

View details for DOI 10.1017/cts.2022.393

View details for PubMedID 35720967

View details for PubMedCentralID PMC9161049