Frailty Index-laboratory and lymphocyte subset patterns in predicting 28-day mortality among elderly sepsis patients: a multicenter observational cohort study

衰弱指数-实验室指标和淋巴细胞亚群模式在预测老年脓毒症患者28天死亡率中的作用:一项多中心观察性队列研究

阅读:2

Abstract

BACKGROUND: Frailty is associated with poor outcomes in elderly sepsis patients. This study investigated the relationship between Frailty Index-laboratory (FI-lab) and lymphocyte patterns in predicting 28-day mortality among elderly sepsis patients. METHODS: We conducted a multicenter prospective observational study in four tertiary hospitals in Beijing, China. FI-lab was calculated using 24 laboratory parameters. Peripheral blood lymphocyte subsets were measured at ICU admission. Lymphocyte count trajectories were classified into four phenotypes based on patterns during the first 72 hours. The primary outcome was 28-day mortality. RESULTS: Among 1,197 patients (mean age 74.6 ± 7.4 years), those with high FI-lab risk showed higher mortality (22.2%) than intermediate (12.0%) and low-risk groups (6.1%). Age-stratified analysis demonstrated consistent FI-lab prognostic value in both 65-79 years (OR 2.18) and ≥80 years (OR 2.47) groups. All lymphocyte subset counts were lower in non-survivors, particularly natural killer cells. In multivariable analysis, high FI-lab risk (OR 2.31), APACHE-II scores (OR 1.08), heart rate (OR 1.01), NK cell count (OR 0.994), and pulmonary infection (OR 1.96) independently predicted 28-day mortality. A combined model incorporating these variables showed superior discriminative ability (AUC=0.788) with excellent internal validation (optimism-corrected AUC=0.775). CONCLUSIONS: FI-lab independently predicts mortality in elderly sepsis patients and correlates with lymphocyte abnormalities. When comprehensive immune assessment is unavailable, lymphocyte trajectory patterns offer a practical approach for risk stratification.

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。