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Introduction: First external validation of the Bladder Complexity Score (BCS) for predicting complex transurethral resection of bladder tumours (TURBT). Methods: For BCS calculation, TURBTs performed at our institution between January 2018 and December 2019 were reviewed for the presence of preoperative characteristics listed in the Bladder Complexity Checklist (BCC). Receiver operating characteristics (ROC) analysis was used for BCS validation. To establish a modified BCS (mBCS) with maximum area under the curve (AUC), multivariable logistic regression (MLR) analysis was performed with all BCC-characteristics for different definitions of complex TURBT. Results: 723 TURBTs were included in statistical analyses. Cohort’s mean BCS was 11.2 ± 2.4 points (range: 5.5–22 points). In ROC analysis, BCS could not predict complex TURBT (AUC 0.573 [95% CI: 0.517–0.628]). MLR identified tumour size (OR 2.662, p < 0.001), and tumour number > 10 (OR 6.390, p = 0.032) as sole predictors for the modified endpoint of complex TURBT defined as a procedure meeting > 1 criterion: incomplete resection, surgery > 1 h, intraoperative complication, postoperative complications Clavien-Dindo ≥ III. mBCS increased the prediction to an AUC of 0.770 (95% CI: 0.667–0.874). Conclusion: In this first external validation, BCS remained an insufficient predictor of complex TURBT. mBCS requires reduced parameters, is more predictive and easier to apply in clinical practice.

Introduction: Perioperative antibiotic prophylaxis (AP) is common in radical prostatectomy (RP). Yet there is no standard recommendation in international guidelines due to poor evidence. It is of great importance that these perioperative AP are sufficiently checked and systemically validated. The objective of this study was to determine whether a “single-shot” (single-use) perioperative AP yields equivalent results compared to a multiday prophylaxis in RP regarding postoperative wound infections and urinary tract infections. Methods: 376 patients treated by RP at the University Medical Centre Mannheim, from 2014 to 2016, were included in this retrospective study. RP was performed either in a robotic-assisted or open manner. One group received an intravenous dose of perioperative AP with either ciprofloxacin or levofloxacin, continued by an oral dose of AP with ciprofloxacin or levofloxacin until catheter removal, while the other group received a single-shot intravenous perioperative AP with either ciprofloxacin or cefuroxime. Results: There was no significant difference regarding the occurrence of postoperative infections between both AP regimes (p = 0.5). Age, body mass index, and ASA classification did not differ significantly between both groups (p > 0.25). Except for surgery time (p < 0.05), perioperative parameters, such as the preoperative presence of germ-free urine culture, length of hospital stay, catheter time, drain lay time, Gleason score, and TNM stadium, did not differ significantly. Conclusion: The present study shows that perioperative single-shot AP does not entail any disadvantage compared to the multiday AP in terms of postoperative infections after RP.

Introduction: The aim of this study was to assess the value of computed tomography (CT)-based radiomics of perinephric fat (PNF) for prediction of surgical complexity. Methods: Fifty-six patients who underwent renal tumor surgery were included. Radiomic features were extracted from contrast-enhanced CT. Machine learning models using radiomic features, the Mayo Adhesive Probability (MAP) score, and/or clinical variables (age, sex, and body mass index) were compared for the prediction of adherent PNF (APF), the occurrence of postoperative complications (Clavien-Dindo Classification ≥2), and surgery duration. Discrimination performance was assessed by the area under the receiver operating characteristic curve (AUC). In addition, the root mean square error (RMSE) and R2 (fraction of explained variance) were used as additional evaluation metrics. Results: A single feature logit model containing “Wavelet-LHH-transformed GLCM Correlation” achieved the best discrimination (AUC 0.90, 95% confidence interval [CI]: 0.75–1.00) and lowest error (RMSE 0.32, 95% CI: 0.20–0.42) at prediction of APF. This model was superior to all other models containing all radiomic features, clinical variables, and/or the MAP score. The performance of uninformative benchmark models for prediction of postoperative complications and surgery duration were not improved by machine learning models. Conclusion: Radiomic features derived from PNF may provide valuable information for preoperative risk stratification of patients undergoing renal tumor surgery.

Objectives: The objective of this study was to compare open partial nephrectomy (OPN) and robotic-assisted PN (RAPN) based on a propensity score-matched sample and to test the Comprehensive Complication Index (CCI) as an end point for complications. Methods: Patients undergoing PN from 2010 to 2018 at a university care center were included. OPN and RAPN cases were matched in a 2:1 ratio using propensity score-matching with age, gender, BMI, RENAL score, and tumor size as confounders. The primary end point was complications measured with the CCI as continuous score (0–100, 100 indicating death). Results: Data of 570 patients were available. After matching, both cohorts (OPN = 166; RAPN = 83) showed no baseline differences. For the primary end point, CCI, RAPN was superior (RAPN 2.6 ± 7.9 vs. OPN 8.7 ± 13.9; p < 0.001). Additionally, RAPN was superior for length of stay (RAPN 6.5 ± 4.0 vs. OPN 7.4 ± 3.5 days; p < 0.001), hemoglobin drop (RAPN 2.8 ± 1.4 vs. OPN 3.8 ± 1.6 g/dL; p < 0.001), and drop of glomerular filtration rate (RAPN 11.4 ± 14.2 vs. OPN 19.5 ± 14.3 mL/min; p < 0.001). OPN had shorter operating times (RAPN 157 ± 43 vs. OPN 143 ± 45 min; p = 0.014) and less ischemia (RAPN 13% vs. OPN 28%; p = 0.016). Conclusions: RAPN provides superior short-term results regarding overall complications without compromising renal function for small and less complex tumors. However, OPN remains an important option for more complex and larger tumors.

Introduction: To compare RENAL, preoperative aspects and dimensions used for an anatomical (PADUA) classification, and Mayo Adhesive Probability (MAP) scores with the respective intraoperative findings and surgeon’s assessment in predicting surgical outcome of patients undergoing partial nephrectomy. Methods: Data of 150 eligible patients treated at the University Medical Center Mannheim between 2016 and 2018 were analyzed. Tumors were radiologically and intraoperatively assessed by PADUA, RENAL, and MAP scores and surgeon’s assessment. Correlations and regression models were created to predict ischemia time (IT), major complications, and Trifecta (negative surgical margin, IT < 25 min, and absence of major complications). Results: There were strong correlations between radiological and intraoperative RENAL (r = 0.68; p < 0.001) and PADUA scores (r = 0.72; p < 0.001). Radiological RENAL, PADUA, and MAP scores and surgeon’s assessment were independent predictors of Trifecta (OR = 0.71, p = 0.015; OR = 0.77, p = 0.035; OR = 0.65, p = 0.012; OR = 0.40, p = 0.005, respectively). IT showed significant associations with radiological RENAL, PADUA, and surgeon’s assessment (OR = 1.41, p = 0.033; OR = 1.34, p = 0.044; OR = 3.04, p = 0.003, respectively). MAP score proved as only independent predictor of major complications (OR = 2.12, p = 0.002). Conclusion: Radiologically and intraoperatively assessed scores correlated well with each other. Intraoperative nephrometry did not outperform radiological scores in predicting outcome confirming the value of the existing systems. MAP score correlates well with surgeon’s assessment of perirenal fat and major complications underlining the importance of perirenal fat characteristics.