Association between pan-immune inflammatory value and all-cause mortality in critically ill patients with ischemic stroke: a retrospective analysis of the MIMIC-IV database (2008-2022)

缺血性卒中危重患者泛免疫炎症值与全因死亡率之间的关联:MIMIC-IV 数据库(2008-2022 年)的回顾性分析

阅读:1

Abstract

BACKGROUND: Systemic inflammation and immune responses are key contributors to the onset and progression of ischemic stroke, influencing both tissue damage and repair. This study investigates the association between the pan-immune inflammatory value (PIV)-a composite biomarker derived from routine blood tests-and all-cause mortality (ACM) in critically ill ischemic stroke patients. METHODS: We extracted data from the MIMIC-IV (v3.0) database, identifying ischemic stroke patients using ICD-9/10 codes. PIV was calculated using the formula: (monocytes × neutrophils × platelets) ÷ lymphocytes. ACM was assessed during hospitalization and at 30-, 90-, and 365-days post-admission. Multivariable Cox proportional hazards models and restricted cubic spline (RCS) analyses were used to assess the relationship between PIV and mortality. Kaplan-Meier curves, time-dependent ROC curves, and decision curve analysis (DCA) evaluated survival differences and predictive performance. Subgroup and interaction analyses were conducted using likelihood ratio tests. RESULTS: A total of 1,365 critically ill ischemic stroke patients were included, with 50.48% male. Elevated PIV was significantly associated with higher mortality during hospitalization (HR: 1.98), and at 30-day (HR: 2.56), 90-day (HR: 1.97), and 365-day (HR: 1.76) follow-ups (all p < 0.01). RCS analysis revealed a J-shaped relationship between PIV and ACM. Subgroup analyses showed consistent results without significant interaction effects. CONCLUSION: PIV is an independent predictor of short- and long-term mortality in critically ill ischemic stroke patients. These findings suggest PIV could serve as a practical and cost-effective biomarker for risk stratification and prognosis in clinical settings.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。