经皮肾镜取石术后并发全身炎症反应综合征的预测因素及其应用进展
Advances in predictive factors for systemic inflammatory response syndrome after percutaneous nephrolithotomy
经皮肾镜取石术(PCNL)作为复杂性肾结石的一线微创治疗方案,其术后全身炎症反应综合征(SIRS)发生率高达 10%~30%,可在数小时内进展为脓毒血症甚至脓毒性休克,严重危及患者生命。既往 PCNL 术后 SIRS 预测因素相关研究多聚焦于单一指标,缺乏对多维度预测因素的系统整合。本研究基于近 5 年国内外最新循证证据,从术前细菌学评估、手术相关因素、患者基础状态、复合炎症标志物、营养免疫评估指标、影像学解剖学参数及机器学习预测模型 7 个维度,系统梳理 PCNL 术后 SIRS 预测因素的最新研究进展。文章提出基于循证证据的 PCNL 围手术期 SIRS 分级风险评估流程及其差异化围手术期管理策略,将抽象的预测因素转化为可量化、可操作的临床决策工具,为临床医师精准识别高危患者、个体化制定围手术期方案、优化预防性抗感染策略以及合理选择监护强度提供了循证参考,对降低 PCNL 术后 SIRS 的发生率、改善患者预后具有重要的临床指导价值。
Percutaneous nephrolithotomy (PCNL), as a first-line minimally invasive treatment for complex renal calculi, is associated with a postoperative incidence of systemic inflammatory response syndrome (SIRS) as high as 10%-30%. SIRS may progress within hours to sepsis or even septic shock, posing a serious threat to patients’ lives. Previous studies on predictors of SIRS after PCNL have mostly focused on individual indicators, with insufficient systematic integration of multidimensional predictive factors. Based on the latest evidence from China and abroad over the past five years, this study systematically reviews recent research advances in predictors of SIRS after PCNL from seven dimensions: preoperative bacteriological assessment, surgery-related factors, baseline patient status, composite inflammatory markers, nutritional and immune assessment indicators, imaging and anatomical parameters and machine learning prediction models. This study proposes an evidence-based graded risk assessment workflow for perioperative SIRS in PCNL and corresponding differentiated perioperative management strategies. It transforms abstract predictive factors into quantifiable and operable clinical decision-making tools, providing evidence-based references for clinicians to accurately identify high-risk patients, formulate individualized perioperative plans, optimize prophylactic anti-infective strategies, and reasonably determine the intensity of monitoring. These findings have important clinical guiding value for reducing the incidence of SIRS after PCNL and improving patient prognosis.
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国家自然科学基金(82560155)
国家自然科学基金(82260156)
贵州省“千层次”创新型人才(GZSYQCC〔2023〕016)
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