Disease trajectory research in critical illness: applications, examples, and prospects

Abstract

Trajectories refer to the motion paths followed by objects in space. Disease trajectories, which depict the evolution of disease processes over time, are significantly important for assessing diseases, formulating treatment strategies, and predicting prognosis. Critical illness is one of the leading causes of death. With advances in critical care medicine, there is increasing focus on the occurrence and development of critical illnesses. Understanding the development trajectory of critical illness is helpful to promote the early identification, intervention, and treatment of high-risk patients, avoid prolongation of the course of disease, reduce the risk of multiple organ failure, and provide important reference for the development of targeted prevention and intervention strategies, thereby reducing the incidence and mortality of critical illness. In recent years, various trajectory modeling methods have been applied to the study of critical illness. These include, but are not limited to, latent growth curve modeling (LGCM), growth mixture modeling (GMM), group-based trajectory modeling (GBTM), latent transition analysis (LTA), and latent class analysis (LCA). The aim of this article is to review the definition of disease trajectories, the methods used in trajectory modeling, and their applications and future prospects in critical illness research.