Serial platelet count as a dynamic prediction marker of hospital mortality among septic patients

作者：Qian Ye, Xuan Wang, Xiaoshuang Xu, Jiajin Chen, David C. Christiani, Feng Chen, Ruyang Zhang, Yongyue Wei · 发表于：Burns & Trauma · 年份：2024 · DOI：10.1093/burnst/tkae016 · 被引用次数：35 · 研究领域：Inflammatory Biomarkers in Disease Prognosis、Platelet Disorders and Treatments、Antiplatelet Therapy and Cardiovascular Diseases

Abstract Background Platelets play a critical role in hemostasis and inflammatory diseases. Low platelet count and activity have been reported to be associated with unfavorable prognosis. This study aims to explore the relationship between dynamics in platelet count and in-hospital morality among septic patients and to provide real-time updates on mortality risk to achieve dynamic prediction. Methods We conducted a multi-cohort, retrospective, observational study that encompasses data on septic patients in the eICU Collaborative Research Database (eICU-CRD) and the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The joint latent class model (JLCM) was utilized to identify heterogenous platelet count trajectories over time among septic patients. We assessed the association between different trajectory patterns and 28-day in-hospital mortality using a piecewise Cox hazard model within each trajectory. We evaluated the performance of our dynamic prediction model through area under the receiver operating characteristic curve, concordance index (C-index), accuracy, sensitivity, and specificity calculated at predefined time points. Results Four subgroups of platelet count trajectories were identified that correspond to distinct in-hospital mortality risk. Including platelet count did not significantly enhance prediction accuracy at early stages (day 1 C-indexDynamic vs C-indexWeibull: 0.713 vs 0.714). However, our model showed superior performance to the static ...