Cardiology Department, Kocaeli University School of Medicine, İzmit, Turkey.
Cardiorenal Med. 2022;12(2):71-80. doi: 10.1159/000524945. Epub 2022 May 17.
The systemic immune-inflammation index (SII), derived from counts of neutrophils, platelets, and lymphocytes, has been developed to predict clinical outcomes in several cancers and cardiovascular diseases. The aim of this study was to evaluate the utility of SII to predict contrast-induced nephropathy (CIN) in patients with ST-segment elevation myocardial infarction (STEMI) who underwent primary percutaneous coronary intervention (PCI).
A total of 632 patients with STEMI who underwent primary PCI were retrospectively included. The patients were divided into two groups based on the presence or absence of CIN. Baseline demographic, laboratory, and clinic characteristics were evaluated between the two groups. Logistic regression analysis was used to identify independent predictors of CIN.
The receiver operating characteristic curve analysis demonstrated that the optimal cutoff value of SII for predicting CIN was 1,282 with a sensitivity of 76.1% and specificity of 86.7% (AUC: 0.834; 95% CI: 0.803-0.863; p < 0.001). Multivariate analysis performed in two models (SII; as separate continuous and categorical variables) showed age, estimated glomerular filtration rate (eGFR), diabetes, left ventricular ejection fraction (LVEF), Killip class ≥2, use of an intravenous diuretic, troponin I, and SII as independent predictors of CIN in model 1. In model 2, age, eGFR, diabetes, LVEF, Killip class ≥2, use of an intravenous diuretic, troponin I, and a value of SII >1,282 (p < 0.001, OR 6.205, 95% CI: 2.301-12.552) remained as independent predictors of CIN.
SII may be a useful and reliable indicator to predict the development of CIN in patients with STEMI undergoing primary PCI than NLR and PLR.
基于中性粒细胞、血小板和淋巴细胞计数推导得出的全身免疫炎症指数（SII）已被开发用于预测多种癌症和心血管疾病的临床结局。本研究旨在评估 SII 预测行直接经皮冠状动脉介入治疗（PCI）的 ST 段抬高型心肌梗死（STEMI）患者对比剂诱导肾病（CIN）的效用。
回顾性纳入 632 例行直接 PCI 的 STEMI 患者。根据是否发生 CIN 将患者分为两组。评估两组间的基线人口统计学、实验室和临床特征。采用 logistic 回归分析确定 CIN 的独立预测因素。
受试者工作特征曲线分析显示，SII 预测 CIN 的最佳截断值为 1,282，其灵敏度为 76.1%，特异性为 86.7%（AUC：0.834；95%CI：0.803-0.863；p<0.001）。在两个模型（SII；分别为连续和分类变量）中进行的多变量分析显示，年龄、估算肾小球滤过率（eGFR）、糖尿病、左心室射血分数（LVEF）、Killip 分级≥2、静脉使用利尿剂、肌钙蛋白 I 和 SII 是模型 1 中 CIN 的独立预测因素。在模型 2 中，年龄、eGFR、糖尿病、LVEF、Killip 分级≥2、静脉使用利尿剂、肌钙蛋白 I 和 SII 值>1,282（p<0.001，OR 6.205，95%CI：2.301-12.552）仍是 CIN 的独立预测因素。
与 NLR 和 PLR 相比，SII 可能是预测行直接 PCI 的 STEMI 患者发生 CIN 的有用且可靠指标。
