Zhang Lijuan, Liu Liyan, Yan Guosheng, Ma Xu, Zhu Guizhen, Dong Xinxin, Lu Yang, Zhang Hongtao
Department of Nephrology, People's Hospital of Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
Blood Purification Center, Henan Provincial People's Hospital, Zhengzhou, Henan, People's Republic of China.
J Inflamm Res. 2024 Nov 12;17:8727-8739. doi: 10.2147/JIR.S488900. eCollection 2024.
The predictive value of the Systemic Immune-Inflammation Index (SII) on mortality in patients with sepsis-associated acute kidney injury (S-AKI) remains unclear. This study aims to investigate the predictive value of SII levels at the Intensive Care Unit (ICU) on the 28-day mortality of S-AKI patients.
S-AKI patients admitted to the ICU of Henan Provincial People's Hospital from January 1, 2023, to December 31, 2023. Patients who were diagnosed with S-AKI were divided into survival and death groups based on their 28-day outcome after ICU admission. Using receiver operating characteristic (ROC) curves to determine the best cut-off values and prognostic abilities of various parameters. Kaplan-Meier survival curves describe the 28-day survival of patients after ICU admission. Cox regression analysis identified the main risk factors associated with mortality in S-AKI patients, constructing a predictive nomogram. The concordance index (C-index) and decision curve analysis were used to validate the predictive ability of this model.
A total of 216 patients with S-AKI were included. ROC analysis showed that SII had the highest predictive value for mortality risk in S-AKI patients after ICU admission. Compared with the low-SII group, the high-SII group had higher 28-day (86.7% vs 32.4%, respectively, P <0.001) mortality rate. Based on Cox regression analysis, a nomogram predictive model was constructed, including age, respiratory failure, SII levels, number of organ dysfunctions at ICU admission, sequential organ failure assessment (SOFA), and acute physiology and chronic health evaluation II (APACHEII). The C-index for predicting the 28-day survival rate was 0.682. Decision curve analysis indicated a high level of clinical predictive efficacy.
SII serves as a potential biomarker for predicting the prognosis of S-AKI patients. The constructed nomogram prognostic model can aid in assessing the prognosis of S-AKI patients.
全身免疫炎症指数（SII）对脓毒症相关性急性肾损伤（S-AKI）患者死亡率的预测价值尚不清楚。本研究旨在探讨重症监护病房（ICU）中SII水平对S-AKI患者28天死亡率的预测价值。
选取2023年1月1日至2023年12月31日入住河南省人民医院ICU的S-AKI患者。根据入住ICU后28天的结局，将诊断为S-AKI的患者分为存活组和死亡组。采用受试者工作特征（ROC）曲线确定各参数的最佳截断值和预后能力。Kaplan-Meier生存曲线描述了患者入住ICU后28天的生存情况。Cox回归分析确定了与S-AKI患者死亡率相关的主要危险因素，构建了预测列线图。一致性指数（C指数）和决策曲线分析用于验证该模型的预测能力。
共纳入216例S-AKI患者。ROC分析显示，SII对入住ICU后S-AKI患者的死亡风险具有最高的预测价值。与低SII组相比，高SII组的28天死亡率更高（分别为86.7%和32.4%，P<0.001）。基于Cox回归分析，构建了列线图预测模型，包括年龄、呼吸衰竭、SII水平、入住ICU时器官功能障碍数量、序贯器官衰竭评估（SOFA）和急性生理与慢性健康状况评估II（APACHEII）。预测28天生存率的C指数为0.682。决策曲线分析表明临床预测效能较高。
SII可作为预测S-AKI患者预后的潜在生物标志物。构建的列线图预后模型有助于评估S-AKI患者的预后。
