系统性炎症生物标志物的预测价值,用于预测经皮膜瘤切除术后的术后系统性炎症反应综合征
Qi Wei1,2, AiMin Liu2, ZhiYong Sun2
1Department 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.
International journal of general medicine
|January 3, 2025
概括
手术前的中性粒细胞与淋巴细胞的比率 (NLR),血小板与淋巴细胞的比率 (PLR) 和全身免疫炎症指数 (SII) 预测皮肤透神经切除术 (PCNL) 后的全身炎症反应综合征 (SIRS). 这些生物标志物有助于风险分层,以改善患者管理.
科学领域:
- 泌尿器科 泌尿器科 泌尿器科 泌尿器科
- 外科手术炎症 在外科手术炎症.
- 生物标志物研究 生物标志物研究
背景情况:
- 系统性炎症响应综合征 (SIRS) 是皮肤透神经切除术 (PCNL) 后的一种潜在并发症.
- 确定SIRS可靠的预测因子对于优化患者的治疗结果和术后管理至关重要.
- 系统性炎症生物标志物,包括NLR,LMR,PLR和SII,在各种炎症条件中显示出潜力.
研究的目的:
- 评估中性粒细胞与淋巴细胞比率 (NLR),淋巴细胞与单细胞比率 (LMR),血小板与淋巴细胞比率 (PLR) 和系统性免疫炎症指数 (SII) 对PCNL后SIRS发生的预测意义.
主要方法:
- 对接受PCNL的317名患者的回顾性分析,分为SIRS (n=51) 和非SIRS (n=266) 组.
- 评估NLR,LMR,PLR和SII,以及人口和手术因素,作为SIRS的潜在预测因素.
- 应用单变量和多变量逻辑回归,以及接收器运行特征 (ROC) 曲线分析.
主要成果:
- 与非SIRS组相比,SIRS组的NLR,PLR和SII显著增加.
- 多变量分析确定了NLR (OR=1.292),PLR (OR=1.008) 和SII (OR=1.001) 作为PCNL后SIRS的独立预测因素.
- 经过ROC分析,NLR (AUC=0.638),PLR (AUC=0.644) 和SII (AUC=0.680) 的区分能力得到了证明.
结论:
- 手术前的NLR,PLR和SII是预测PCNL后SIRS风险的有价值指标.
- 这些生物标志物可以帮助识别高风险患者,使得手术前评估和治疗策略能够量身定制.
- 进一步的研究可以探索将这些炎症标志物整合到PCNL患者的常规术前评估中.
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