Latent trajectory modeling of platelet counts and mortality risk in intensive care unit patients with atrial fibrillation.

BackgroundEarly changes in platelet count may reflect disease mechanisms affecting prognosis in critically ill patients, but their role in atrial fibrillation (AF) remains unclear.MethodsThis retrospective study analyzed intensive care unit (ICU) patients with AF from the Medical Information Mart for Intensive Care IV database. Platelet count within the first 36 h of ICU admission was assessed using latent growth mixture modeling to identify temporal trajectories. Associations between these trajectories and 28-day all-cause mortality were examined using Cox proportional hazards regression, Kaplan-Meier survival analysis, and subgroup analyses.ResultsCompared with the reference group, Class 2 showed a significantly higher risk of 28-day mortality in fully adjusted models (p = 0.013), whereas Class 3 showed no significant difference (p = 0.163). Kaplan-Meier analysis further confirmed reduced survival in Class 2 (log-rank p < 0.001). Stratified subgroup analysis indicated that the mortality association was more evident among female patients and those with a history of hypertension or heart failure.ConclusionIn ICU patients with AF, early platelet count trajectories are independently associated with 28-day mortality. A downward trend in platelet levels signals a high-risk population, suggesting the potential utility of platelet dynamics in early prognostic assessment and risk stratification.