Modeling clinical trajectory status of critically ill COVID-19 patients over time: A method for analyzing discrete longitudinal and ordinal outcomes - 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; et al. (Journal of Clinical and Translational Science, 2022)
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.