Pellegrino Paloma, Scherer Thomas Paul, Wettstein Marian Severin, Baumgartner Melanie, Eberli Daniel, Poyet Cédric, Bieri Uwe
Department of Urology, University Hospital of Zurich, University of Zurich, Zurich, Switzerland.
Department of Surgery, Division of Urology, University of Toronto, Toronto, Canada.
Int Urol Nephrol. 2025 Sep 2. doi: 10.1007/s11255-025-04734-5.
Postoperative bleeding is a known complication following transurethral resection of bladder tumors (TURBT). Although factors like tumor size and anticoagulant use are associated with increased bleeding risk, no validated prediction tool currently exists. This study aimed to determine predictors and develop a clinical tool for preoperative bleeding risk assessment.
We conducted a retrospective analysis of patients undergoing TURBT at the University Hospital of Zurich between January 2016 and November 2022. Bleeding events were defined by four criteria: hemoglobin drop of ≥ 4 g/dl, need for transfusion, gross hematuria requiring prolonged irrigation, or surgical revision for bleeding during hospitalization or within 2 weeks after dischargement.
During this time period, 447 TURBTs were performed, of which 54 (12.1%) were associated with a bleeding event. Univariable logistic regression identified five significant predictors (p value < 0.05): HAS-BLED score, high-risk alcohol consumption, use of oral anticoagulant and/or platelet aggregation inhibitors, and bridging therapy. In the multivariable logistic regression model, only high-risk alcohol consumption and platelet aggregation inhibitors remained statistically significant (p value < 0.05). All predictors had positive coefficients, indicating increased bleeding risk. A nomogram was developed based on these variables to assist in preoperative risk assessment. The model showed good calibration (Brier score = 0.097) and strong overall fit (Likelihood Ratio Test: χ = 31.08, df = 5, p < 0.0001).
We developed a predictive model for bleeding risk after TURBT. This tool may support perioperative management, by raising awareness of risk factors for bleeding complications and enabling tailored interventions for at-risk patients.
术后出血是经尿道膀胱肿瘤切除术(TURBT)后已知的并发症。尽管肿瘤大小和抗凝剂使用等因素与出血风险增加有关,但目前尚无经过验证的预测工具。本研究旨在确定预测因素并开发一种用于术前出血风险评估的临床工具。
我们对2016年1月至2022年11月在苏黎世大学医院接受TURBT的患者进行了回顾性分析。出血事件由四个标准定义:血红蛋白下降≥4 g/dl、需要输血、需要长时间冲洗的肉眼血尿,或在住院期间或出院后2周内因出血进行手术修正。
在此期间,共进行了447例TURBT,其中54例(12.1%)与出血事件相关。单因素逻辑回归确定了五个显著预测因素(p值<0.05):HAS - BLED评分、高危饮酒、使用口服抗凝剂和/或血小板聚集抑制剂以及桥接治疗。在多因素逻辑回归模型中,只有高危饮酒和血小板聚集抑制剂仍具有统计学意义(p值<0.05)。所有预测因素的系数均为正值,表明出血风险增加。基于这些变量开发了一个列线图以辅助术前风险评估。该模型显示出良好的校准(Brier评分 = 0.097)和较强的整体拟合度(似然比检验:χ = 31.08,df = 5,p < 0.0001)。
我们开发了一种TURBT术后出血风险的预测模型。该工具可通过提高对出血并发症风险因素的认识并为高危患者提供量身定制的干预措施,来支持围手术期管理。