Wei Qi, Liu AiMin, Sun ZhiYong, Zhang Shuang, Hao ZongYao
Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Anhui Medical University and Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University, Hefei, People's Republic of China.
Department of Urology, Dongcheng Branch of The First Affiliated Hospital of Anhui Medical University, Hefei, People's Republic of China.
Int J Gen Med. 2024 Dec 28;17:6513-6521. doi: 10.2147/IJGM.S497322. eCollection 2024.
The aim of the study was to evaluate the predictive significance of several systemic inflammatory biomarkers, namely neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR) and systemic immune inflammatory index (SII) in relation to the occurrence of systemic inflammatory response syndrome (SIRS) after percutaneous nephrolithotomy (PCNL).
A cohort of 317 patients who underwent PCNL were retrospectively recruited and evaluated. Based on the subsequent occurrence of SIRS after PCNL, patients were divided into two different groups: SIRS (n = 51) and non-SIRS (n = 266). We examined the effect of neutrophil-to-lymphocyte ratio(NLR), lymphocyte-to-monocyte ratio(LMR), platelet-to-lymphocyte ratio(PLR), and systemic immunoinflammatory index (SII), as well as other demographic characteristics and surgical factors to predict the development of SIRS. Univariate analysis and multivariate logistic regression were used to identify independent predictors of SIRS after PCNL. In addition, receiver operating characteristic (ROC) curves were constructed and area under the curve (AUC) values were calculated to evaluate and compare the discriminatory ability of the studied systemic inflammatory biomarkers.
The NLR, PLR, and SII values in the SIRS group were significantly increased compared to those in the non-SIRS group. Multivariate analysis revealed NLR (OR = 1.292, 95% CI: 1.047-1.594, = 0.017), PLR (OR = 1.008, 95% CI: 1.001-1.016, = 0.032) and SII (OR = 1.001, 95%CI: 1.000-1.003, = 0.016) as independent predictors of SIRS development after PCNL. Furthermore, ROC curve analysis highlighted the discriminative ability of NLR, PLR and SII with AUC values of 0.638, 0.644 and 0.680, respectively.
These results highlight the importance of preoperative NLR, PLR and SII as reliable indicators for risk prediction of SIRS after PCNL. In response to these findings, it is critical to perform careful and comprehensive preoperative evaluations of these patients while developing tailored treatment strategies.
本研究旨在评估几种全身炎症生物标志物,即中性粒细胞与淋巴细胞比值(NLR)、淋巴细胞与单核细胞比值(LMR)、血小板与淋巴细胞比值(PLR)和全身免疫炎症指数(SII),在经皮肾镜取石术(PCNL)后全身炎症反应综合征(SIRS)发生中的预测意义。
回顾性纳入并评估了317例行PCNL的患者。根据PCNL后SIRS的发生情况,将患者分为两组:SIRS组(n = 51)和非SIRS组(n = 266)。我们研究了中性粒细胞与淋巴细胞比值(NLR)、淋巴细胞与单核细胞比值(LMR)、血小板与淋巴细胞比值(PLR)和全身免疫炎症指数(SII),以及其他人口统计学特征和手术因素对SIRS发生的预测作用。采用单因素分析和多因素逻辑回归来确定PCNL后SIRS的独立预测因素。此外,构建了受试者工作特征(ROC)曲线并计算曲线下面积(AUC)值,以评估和比较所研究的全身炎症生物标志物的鉴别能力。
与非SIRS组相比,SIRS组的NLR、PLR和SII值显著升高。多因素分析显示,NLR(OR = 1.292,95%CI:1.047 - 1.594,P = 0.017)、PLR(OR = 1.008,95%CI:1.001 - 1.016,P = 0.032)和SII(OR = 1.001,95%CI:1.000 - 1.003,P = 0.016)是PCNL后SIRS发生的独立预测因素。此外,ROC曲线分析突出了NLR、PLR和SII的鉴别能力,其AUC值分别为0.638、0.644和0.680。
这些结果突出了术前NLR、PLR和SII作为PCNL后SIRS风险预测可靠指标的重要性。鉴于这些发现,在制定个性化治疗策略时,对这些患者进行仔细全面的术前评估至关重要。