Urologists are optimistic surgeons: prevalence and predictors of discordance between intraoperative stone-free rate and cross-sectional imaging evaluation after vacuum-assisted mini-percutaneous nephrolithotomy

泌尿科医生是乐观的外科医生:真空辅助微创经皮肾镜取石术后术中结石清除率与横断面影像学评估结果不一致的发生率和预测因素

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Abstract

PURPOSE: To assess how accurate are urologists in predicting stone-free status (SFS) after vacuum-assisted mini-PCNL (vamPCNL) compared to computed tomography (CT) and clinical predictors of discordant SFS. METHODS: Data from 235 patients who underwent vamPCNL were analysed. Patient's demographics, stones' characteristics and operative data were recorded. SFS was evaluated intraoperatively by the treating urologist (iSFS) and with non-contrast CT 3 months after vamPCNL (ctSFS). SFS was defined as no residual stones. Stone complexity was scored with the Guy's score. Descriptive statistics and logistic regression models were used to identify clinical factors associated with discordant SFS (namely iSFS not confirmed at CT). RESULTS: iSFS and ctSFS were 88.5% and 65.5%, respectively, with 54 (23%) cases resulting in discordant evaluation of SFS between the surgeon and CT imaging. Patients with discordant SFS had larger stone volume (p < 0.001), higher rate of multiple stones (p = 0.03) and higher rate of multiple calyceal groups affected by stones (p < 0.001) than those with concordant SFS. The use of flexible ureteroscopes to look for residual stones after lithotripsy was more frequently reported in cases with concordant SFS (p = 0.001). Multivariable logistic regression analysis revealed that stones in > 2 calyceal groups (OR 10.2, p < 0.001), Guy's score II (OR 5.8, p < 0.01) and not using flexible ureteroscopes after lithotripsy (OR 2.9, p = 0.02) were independent predictors of discordant SFS. CONCLUSION: One out of five patients is erroneously considered SF after vamPCNL. Urologist should carefully evaluate patients with multiple calyceal stones and consider using flexible ureteroscopes to complete lapaxy of migrated fragments in order to improve their prediction of SFS.

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