北京大学学报(医学版) ›› 2018, Vol. 50 ›› Issue (3): 507-513. doi: 10.3969/j.issn.1671-167X.2018.03.019

• 论著 • 上一篇    下一篇

经皮肾镜取石术后尿脓毒血症的相关危险因素及预测模型

刘余庆,卢剑,郝一昌,肖春雷△,马潞林   

  1. (北京大学第三医院泌尿外科, 北京100191)
  • 出版日期:2018-06-18 发布日期:2018-06-18
  • 通讯作者: 肖春雷 E-mail:pku3uro@aliyun.com

Predicting model based on risk factors for urosepsis after percutaneous nephrolithotomy

LIU Yu-qing, LU Jian, HAO Yi-chang, XIAO Chun-lei△, MA Lu-lin   

  1. (Department of Urology, Peking University Third Hospital, Beijing 100191, China)
  • Online:2018-06-18 Published:2018-06-18
  • Contact: XIAO Chun-lei E-mail:pku3uro@aliyun.com

摘要: 目的:对经皮肾镜取石术(percutaneous nephrolithotomy,PCNL)治疗上尿路结石术后发生尿脓毒血症的围手术期相关因素进行分析,根据其中的独立危险因素,建立预测术后尿脓毒血症风险的列线图模型。方法:回顾性分析2013年1月至2016年12月北京大学第三医院泌尿外科405例接受一期PCNL患者的临床资料。根据术后是否发生尿脓毒血症将患者分为两组,通过单因素和多因素Logistic回归分析评价患者发生尿脓毒血症的独立风险因素,根据回归系数绘制相应的列线图预测模型。结果: 405例患者PCNL手术均获成功,其中32例(7.9%)术后发生尿脓毒血症,多因素Logistic回归分析结果显示,与术后尿脓毒血症相关的独立风险因素包括:糖尿病史(OR=4.511,P=0.001)、较高结石负荷(OR=2.588,P=0.043)、较长手术时间(OR=2.353,P=0.036)、较高灌注速度(OR=5.862,P<0.001)以及感染性结石成分(OR=2.677,P=0.036)。列线图模型在建模样本中的一致性系数(concordance index,C-index)为0.834,在验证样本中的Cindex为0.802,表现出良好的符合度。结论:糖尿病史、较高结石负荷、较长手术时间、较高术中灌注速度以及感染性结石成分是一期PCNL治疗上尿路结石术后尿脓毒血症的独立风险因素,根据上述临床独立风险因素建立的列线图有助于预测术后尿脓毒血症的风险。

关键词: 肾造口术, 经皮, 尿路结石症, 脓毒症, 危险因素, 列线图

Abstract: Objective: To analyze the potential perioperative risk factors that affect the development of urosepsis following percutaneous nephrolithotomy (PCNL) for upper urinary tract calculi with a regression model, and to develop a nomogram for predicting the probability of postoperative urosepsis after PCNL according to the identified independent risk factors. Methods: We retrospectively analyzed the clinical data from consecutive 405 cases of upper urinary tract calculi treated by one-phase PCNL between January 2013 and December 2016 in our clinical department. According to whether the patients developed urosepsis or not after the surgery, the patients were divided into two groups. Perioperative risk factors that could potentially contribute to urosepsis were compared between the two groups. By a Logistic regression model, univariate and multivariate statistical analyses were carried out for the occurrence of postoperative urosepsis, to identify the independent risk factors affecting the development of postoperative urosepsis. From this model, a nomogram was built based on regression coefficients. Results: The PCNL procedures of the 405 cases were performed successfully, and there were 32 cases that developed urosepsis after the PCNL, and the incidence of urosepsis was 7.9% (32/405). A multivariate Logistic regression model was built, excluding the factors with values of P>0.05 in the univariate analysis. Multivariable Logistic regression analysis identified the following factors as independent risk factors for urosepsis after PCNL: diabetes mellitus history (OR=4.511, P=0.001), larger stone burden (OR=2.588, P=0.043), longer operation time (OR=2.353, P=0.036), increased irrigation rate (OR=5.862, P<0.001), and infectious stone composition (OR=2.677, P=0.036). The nomogram based on these results was well fitted to predict a probability, and the concordance index (C-index) was 0.834 in the nomogram model sample and 0.802 in the validation sample. Conclusion: Diabetes mellitus history, higher stone burden, longer operation time, increased intraoperative irrigation rate, and infectious stone composition are identified as independent risk factors to affect the development of urosepsis after one-phase percutaneous nephrolithotomy for upper urinary tract calculi. A nomogram based on these perioperative clinical independent risk factors for urosepsis could be used to predict the risk of urosepsis following PCNL.

Key words: Nephrostomy, percutaneous, Urolithiasis, Sepsis, Risk factors, Nomograms

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