医学
代谢综合征
感染性休克
输尿管镜检查
逻辑回归
碎石术
内科学
泌尿系统
糖尿病
回顾性队列研究
外科
败血症
肥胖
输尿管
内分泌学
作者
Junxiu Hao,Zhiyong Du,Zhiqiang Bo,Huimin Zhang,Xiuyun Wang
出处
期刊:Surgical Infections
[Mary Ann Liebert]
日期:2024-01-24
卷期号:25 (2): 140-146
被引量:1
摘要
Background: To investigate retrospectively whether metabolic syndrome (MetS) of flexible ureteroscopy (fURS) lithotripsy can be used to predict post-operative infection. Patients and Methods: After screening, 1,110 patients who received fURS lithotripsy for upper urinary tract stones in our center between January 2015 and December 2022 were analyzed retrospectively. Patients were divided into MetS-positive group and MetS-negative group. Post-operative infection was divided into fever, urosepsis, and septic shock. Relevant data during the peri-operative period were collected. Univariable and multivariable logistic regression analyses were adopted to estimate the impact of metabolic syndrome on post-operative infection in patients undergoing fURS lithotripsy. Results: Among the 1,110 patients, 427 tested positive for MetS, whereas 683 tested negative. Eighty-eight patients suffered from fever (67 patients in the MetS-positive group and 21 in the MetS-negative group). Forty-nine patients had urosepsis (29 patients in the MetS-positive group and 20 in the MetS-negative group), of whom seven patients developed septic shock. No patient developed multiple organ failure or died because of infection. The prevalence of post-operative infections in the MetS-positive group was higher than that in the MetS-negative group (p < 0.001). Multivariable logistic regression analyses showed that diabetes mellitus, MetS-positive, positive urine culture, and longer operation time were positively correlated with post-operative fever. Positive MetS, positive urine culture, and longer operation time were strongly correlated with post-operative urosepsis. Conclusions: Metabolic syndrome was found to be associated with post-operative infection in patients undergoing fURS lithotripsy, suggesting it can serve as a predictive factor.
科研通智能强力驱动
Strongly Powered by AbleSci AI