Shangguan Xinghe, Zhang Ziwei, Shangguan Xinyi, Wang Jike, Gong Yuanqi
Department of Critical Care Medicine, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
J Intensive Care Med. 2025 Aug 25:8850666251363853. doi: 10.1177/08850666251363853.
BackgroundSepsis-associated acute kidney injury (SA-AKI) is a serious condition with a high mortality rate. Whole blood-derived inflammatory markers like the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI), are emerging prognostic indicators for various diseases. This study endeavors to unravel the link of these markers to all-cause mortality(ACM) in the SA-AKI population utilizing the MIMIC-IV database.MethodsA retrospective cohort study was conducted on SA-AKI patients meeting the Sepsis-3 and KDIGO criteria. Cox regression analysis was performed to evaluate the association between inflammatory markers and mortality. Restricted cubic spline (RCS) analysis was employed to unveil the potential nonlinear relation of inflammatory markers to mortality. Survival differences across varying levels of inflammation were compared via Kaplan-Meier (KM) survival curves. Subgroup analyses were executed to examine the robustness of the relation and possible interactions between variables. The predictive performance of inflammatory markers was evaluated via receiver operating characteristic (ROC) curves, and the clinical utility of these markers was assessed through clinical decision curve analysis(DCA).Results3429 SA-AKI patients were encompassed (2785 survivors at 30 days and 644 non-survivors). Cox regression analysis revealed a significant link between risen NLR, PLR, MLR, SII, and SIRI to elevated ACM. KM survival analysis demonstrated that patients with higher levels of inflammatory markers had notably higher 30-day death rates. Subgroup analysis indicated an interaction between coronary artery disease (CHD) and inflammation in influencing mortality risk. Among the markers assessed, NLR exhibited the highest forecasting accuracy for 30-day death (AUC = 0.624). Propensity score matching (PSM) confirmed the robustness of these findings.ConclusionWhole blood-derived inflammatory markers, particularly NLR, are closely linked to mortality in patients with SA-AKI. These markers may serve as valuable prognostic tools for identifying high-risk patients and improving clinical outcomes.
背景
脓毒症相关急性肾损伤（SA-AKI）是一种死亡率很高的严重病症。全血源性炎症标志物，如中性粒细胞与淋巴细胞比率（NLR）、血小板与淋巴细胞比率（PLR）、单核细胞与淋巴细胞比率（MLR）、全身免疫炎症指数（SII）和全身炎症反应指数（SIRI），正在成为各种疾病新的预后指标。本研究旨在利用MIMIC-IV数据库揭示这些标志物与SA-AKI人群全因死亡率（ACM）之间的联系。
方法
对符合脓毒症-3和KDIGO标准的SA-AKI患者进行回顾性队列研究。采用Cox回归分析评估炎症标志物与死亡率之间的关联。采用限制立方样条（RCS）分析揭示炎症标志物与死亡率之间潜在的非线性关系。通过Kaplan-Meier（KM）生存曲线比较不同炎症水平下的生存差异。进行亚组分析以检验这种关系的稳健性以及变量之间可能的相互作用。通过受试者工作特征（ROC）曲线评估炎症标志物的预测性能，并通过临床决策曲线分析（DCA）评估这些标志物的临床效用。
结果
纳入3429例SA-AKI患者（30天时有2785例存活者和644例非存活者）。Cox回归分析显示，升高的NLR、PLR、MLR、SII和SIRI与升高的ACM之间存在显著联系。KM生存分析表明，炎症标志物水平较高的患者30天死亡率显著更高。亚组分析表明，冠状动脉疾病（CHD）与炎症在影响死亡风险方面存在相互作用。在所评估的标志物中，NLR对30天死亡的预测准确性最高（AUC = 0.624）。倾向评分匹配（PSM）证实了这些发现的稳健性。
结论
全血源性炎症标志物尤其是NLR与SA-AKI患者的死亡率密切相关。这些标志物可作为识别高危患者和改善临床结局的有价值的预后工具。
