Association of longitudinal platelet count trajectory with ICU mortality: A multi-cohort study

• Published in: Frontiers in immunology Vol. 13; p. 936662
• Main Authors: Chen, Jiajin, Gao, Xi, Shen, Sipeng, Xu, Jingyuan, Sun, Zhe, Lin, Ruilang, Dai, Zhixiang, Su, Li, Christiani, David C., Chen, Feng, Zhang, Ruyang, Wei, Yongyue
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 19.08.2022
• Subjects: critical care; immunity; Immunology; inflammation; longitudinal trajectory; multi-cohort; platelet count
• ISSN: 1664-3224; 1664-3224
• DOI: 10.3389/fimmu.2022.936662

Objective Platelet (PLT) engages in immune and inflammatory responses, all of which are related to the prognosis of critically ill patients. Although thrombocytopenia at ICU admission contributes to in-hospital mortality, PLT is repeatedly measured during ICU hospitalization and the role of longitudinal PLT trajectory remains unclear. We aimed to identify dynamic PLT trajectory patterns and evaluate their relationships with mortality risk and thrombocytopenia. Methods We adopted a three-phase, multi-cohort study strategy. Firstly, longitudinal PLT trajectory patterns within the first four ICU days and their associations with 28-day survival were tested in the eICU Collaborative Research Database (eICU-CRD) and independently validated in the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Secondly, the relationships among PLT trajectory patterns, thrombocytopenia, and 28-day mortality were explored and validated. Finally, a Mortality GRade system for ICU dynamically monitoring patients (Mortality-GRID) was developed to quantify the mortality risk based on longitudinal PLT, which was further validated in the Molecular Epidemiology of Acute Respiratory Distress Syndrome (MEARDS) cohort. Results A total of 35,332 ICU patients were included from three cohorts. Trajectory analysis clustered patients into ascending (AS), stable (ST), or descending (DS) PLT patterns. DS patients with high baseline PLT decline quickly, resulting in poor prognosis. AS patients have low baseline PLT but recover quickly, favoring a better prognosis. ST patients maintain low PLT, having a moderate prognosis in between ( HR ST vs AS = 1.26, 95% CI: 1.14–1.38, P = 6.15 × 10 −6 ; HR DS vs AS = 1.58, 95% CI: 1.40–1.79, P = 1.41 × 10 −13 ). The associations remained significant in patients without thrombocytopenia during the entire ICU hospitalization and were robust in sensitivity analyses and stratification analyses. Further, the trajectory pattern was a warning sign of thrombocytopenia, which mediated 27.2% of the effects of the PLT trajectory on 28-day mortality ( HR indirect = 1.11, 95% CI: 1.06–1.17, P = 9.80 × 10 −6 ). Mortality-GRID well predicts mortality risk, which is in high consistency with that directly estimated in MEARDS ( r = 0.98, P = 1.30 × 10 −23 ). Conclusion Longitudinal PLT trajectory is a complementary predictor to baseline PLT for patient survival, even in patients without risk of thrombocytopenia. Mortality-GRID could identify patients at high mortality risk.