Development and validation of a risk prediction model for urinary retention after pelvic floor reconstruction: a retrospective cohort study.

Abstract

<h4>Objectives</h4>To investigate and analyze the factors affecting postoperative urinary retention (POUR) after pelvic floor reconstruction, and to construct and validate a risk prediction model.<h4>Methods</h4>This retrospective cohort study included 258 pelvic floor reconstruction patients (2023-2024) from a Southwest China tertiary hospital. Patients were classified into POUR and non-POUR groups and split 7:3 into training and internal validation cohorts. Predictors were identified through univariate analysis and multivariate logistic regression analysis to construct a Nomogram model. Receiver Operating Characteristic (ROC) curves, calibration curves, and the Hosmer-Lemeshow test evaluated the model's differentiation, calibration, goodness-of-fit, and predictive performance.<h4>Results</h4>Independent POUR risk factors were: urinary retention history (OR = 10.008, 95% CI 1.368-73.195, P = 0.023), heart disease (OR = 14.416, 95% CI 2.872-72.376, P = 0.001), number of vaginal deliveries (OR = 1.569, 95% CI 1.076-2.289, P = 0.019), and maximal urinary flow rate (OR = 0.845, 95% CI 0.76-0.94, P = 0.002). The AUC values of the training cohort and internal validation cohort were 0.812 (95% CI 0.726-0.899) and 0.822 (95% CI 0.703-0.941), respectively. Calibration curves indicated good agreement between predicted and observed values, and the Hosmer-Lemeshow test demonstrated high predictive accuracy (P > 0.05).<h4>Conclusions</h4>The nomogram model effectively predicts POUR risk, aiding early perioperative identification of high-risk patients.