Renal pelvis urine Gram stain as a traditional, but new marker in predicting postoperative fever and stone culture positivity in percutaneous nephrolithotomy: an observational, prospective, non-randomized cohort study
WORLD JOURNAL OF UROLOGY(2020)
摘要
Purpose The aim of this study was to evaluate the diagnostic value of renal pelvis urine Gram staining (RPUGS) in predicting postoperative fever and renal stone culture (RSC) positivity in percutaneous nephrolithotomy (PCNL). Methods Totally 141 consecutive patients undergoing PCNL for renal stone were included between January 2018 and December 2019. The RPUGS and renal pelvis urine culture (RPUC) were performed using urine sample from renal collecting system, while RSC was performed using stone fragments. Patients were divided into two groups as Group 1 ( n = 119) without postoperative fever (< 38 °C) and Group 2 ( n = 22) with postoperative fever (≥ 38 °C). Stone culture and Gram staining models were created for predicting postoperative fever using constant covariates of the presence of residual stone, hydronephrosis, and stone burden. Results A significantly higher number of patients in Group 2 had RPUGS, RSC, and RPUC positivity ( p < 0.001, for each). The sensitivity, specificity, positive predictive value, and negative predictive value of RPUGS in predicting postoperative fever were 72.7%, 89.9%, 57.1%, and 94.7%, respectively. It was observed that both models had similar predictive values and diagnostic performances. Although RSC and RPUGS had a similar diagnostic value in predicting postoperative fever in univariable analysis, both were found to be independent predictors in multivariable analysis (OR: 10.6, 95% CI 4.07–27.9, p < 0.001 and OR: 15.0, 95% CI 5.4–41.2, p < 0.001, respectively). Conclusions In conclusion, RPUGS is as effective as RSC in predicting fever after PCNL. We recommend RPUGS during PCNL to manage post-PCNL infectious complications.
更多查看译文
关键词
Complications,Gram stain,Infections,Nephrolithiasis,Percutaneous nephrolithotomy,Stone culture
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要