Ou Shuheng, Lu Hong, Qu Rui, Cui Xiaolong, Xiong Zhou, Fan Fangfang, Yu Xiao, Hasi Chaolu
Academy of Medical Sciences, Shanxi Medical University School, Taiyuan, People's Republic of China.
Department of Laboratory Medicine, First Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.
J Inflamm Res. 2025 Jul 30;18:10181-10192. doi: 10.2147/JIR.S531272. eCollection 2025.
We analyzed the correlation between systemic immune inflammatory index (SII), systemic inflammatory response index (SIRI), systemic inflammatory index (AISI), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR) and mortality in patients with bloodstream infection to determine their application potential in predicting the prognosis of bloodstream infection.
We calculated SII, SIRI, AISI, NLR, PLR, and MLR in 469 patients with bloodstream infections. Logistic regression modeling, generalized additive modeling (GAM), and smoothed curve fitting were used to investigate the correlation of SII and other inflammatory markers with mortality in patients with bloodstream infections. Area under the curve (AUC) of ROC was used to assess the predictive effect of SII and other inflammatory markers.
Levels of SII, SIRI, AISI, NLR, PLR, and MLR were significantly higher in the mortality group of this study (P < 0.05). There were significant differences in gender, age, diabetes, cardiovascular disease, respiratory disease, NEUT and LUMPH between the survival group and the death group (p < 0.05). Smooth curve fitting and GAM showed that SII and NLR had a non-linear relationship with death. After adjustment, the breakpoints (K) were 1711 and 7.22, respectively (P < 0.05), and there was a positive correlation on both sides of the breakpoint. The comparison of AUC values showed that SII and NLR had higher accuracy in predicting the risk of death in patients with bloodstream infection.
Studies demonstrates that SII and NLR are more predictive of mortality risk in patients with bloodstream infections. Patients with diabetes, cardiovascular disease, or respiratory disease should be monitored regularly for SII and NLR indicators to reduce the risk of death.
我们分析了全身免疫炎症指数（SII）、全身炎症反应指数（SIRI）、全身炎症指数（AISI）、中性粒细胞与淋巴细胞比值（NLR）、血小板与淋巴细胞比值（PLR）、单核细胞与淋巴细胞比值（MLR）与血流感染患者死亡率之间的相关性，以确定它们在预测血流感染预后方面的应用潜力。
我们计算了469例血流感染患者的SII、SIRI、AISI、NLR、PLR和MLR。采用逻辑回归建模、广义相加模型（GAM）和平滑曲线拟合来研究SII和其他炎症标志物与血流感染患者死亡率的相关性。采用ROC曲线下面积（AUC）评估SII和其他炎症标志物的预测效果。
本研究死亡组的SII、SIRI、AISI、NLR、PLR和MLR水平显著更高（P<0.05）。生存组和死亡组在性别、年龄、糖尿病、心血管疾病、呼吸系统疾病、中性粒细胞和淋巴细胞数量方面存在显著差异（P<0.05）。平滑曲线拟合和GAM显示SII和NLR与死亡呈非线性关系。调整后，断点（K）分别为1711和7.22（P<0.05），断点两侧呈正相关。AUC值比较显示，SII和NLR在预测血流感染患者死亡风险方面具有更高的准确性。
研究表明，SII和NLR在预测血流感染患者的死亡风险方面更具预测性。糖尿病、心血管疾病或呼吸系统疾病患者应定期监测SII和NLR指标，以降低死亡风险。
