Hao Xiaodong, Wang Xiaowei, Ding Hao, Zheng Shuo, Li Zhong, Yin Haijun, Wang Lei, Luo Jie, Wei Hongliang
The First Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Liaocheng People's Hospital, Liaocheng, Shandong, China.
World J Urol. 2022 Dec;40(12):2979-2990. doi: 10.1007/s00345-022-04182-1. Epub 2022 Oct 13.
To study the predictors of sepsis and progression to septic shock after RIRS; to establish and validate predictive models accordingly.
In total, 1220 patients were included in the study during. Eight hundred forty-eight patients were assigned to the development cohort and 372 to the validation cohort according to medical record. Univariate and multivariate logistic regression analyses were used to screen independent risk factors for post-RIRS (Retrograde intrarenal surgery) sepsis and progression to septic shock. Nomogram prediction models were established according to the related independent risk factors. Areas under the receiver operating characteristic curves, calibration plots, and DCA (Decision curve analysis) were used to estimate the discrimination, calibration and clinical usefulness of the prediction model, respectively.
In the development cohort, sepsis occurred in 59 patients, 16 of whom developed septic shock. Multivariate logistic regression analyses showed that the independent risk factors for sepsis after RIRS were preoperative D-J stent implantation, hydronephrosis > 6.25 HU (Hounsfield units), AGR (Albumin/globulin ratio) < 1.95, hs-CRP/Alb (High-sensitivity C-reactive protein/albumin ratio) > 0.060, operating time > 67.5 min, and urinary nitrite positivity. The preoperative/postoperative WBC ratio > 1.5 was an independent risk factor for progression from sepsis to septic shock. In the development cohort, the AUC (Area under curve) for predicting sepsis risk was 0.845, and the AUC for predicting septic shock risk was 0.896; in the validation cohort, the corresponding values were 0.896 and 0.974, respectively. In the development cohort, the calibration test P values in the sepsis and septic shock cohorts, respectively, were 0.921 and 0.817; in the validation cohort, these values were 0.882 and 0.859. DCA of the model in the sepsis and septic shock cohorts showed threshold probabilities of 10-90% in the development cohort and 10-50% and 10-20% in the validation cohort.
These individualized nomogram prediction models can improve the early identification of patients at risk for developing sepsis after RIRS or progressing from sepsis to septic shock.
研究逆行性肾内手术（RIRS）后脓毒症及进展为感染性休克的预测因素；并据此建立和验证预测模型。
本研究共纳入1220例患者。根据病历将848例患者分配至开发队列，372例患者分配至验证队列。采用单因素和多因素逻辑回归分析筛选RIRS后脓毒症及进展为感染性休克的独立危险因素。根据相关独立危险因素建立列线图预测模型。分别采用受试者工作特征曲线下面积、校准图和决策曲线分析（DCA）评估预测模型的辨别力、校准度和临床实用性。
在开发队列中，59例患者发生脓毒症，其中16例进展为感染性休克。多因素逻辑回归分析显示，RIRS后脓毒症的独立危险因素为术前双J管置入、肾积水>6.25 HU（亨氏单位）、白蛋白/球蛋白比值（AGR）<1.95、高敏C反应蛋白/白蛋白比值（hs-CRP/Alb）>0.060、手术时间>67.5分钟及尿亚硝酸盐阳性。术前/术后白细胞比值>1.5是脓毒症进展为感染性休克的独立危险因素。在开发队列中，预测脓毒症风险的曲线下面积（AUC）为0.845，预测感染性休克风险的AUC为0.896；在验证队列中，相应值分别为0.896和0.974。在开发队列中，脓毒症和感染性休克队列的校准检验P值分别为0.921和0.817；在验证队列中，这些值分别为0.882和0.859。该模型在脓毒症和感染性休克队列中的DCA显示，开发队列的阈值概率为10%-90%，验证队列的阈值概率为10%-50%和10%-20%。
这些个体化的列线图预测模型可改善对RIRS后发生脓毒症或脓毒症进展为感染性休克风险患者的早期识别。
