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Updated: Jan 31, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Development and validation of a risk prediction model for urinary retention after pelvic floor reconstruction: a
Shuang Hu1, Linlin Zhou1, Chengying Su1
1Department of Obstetrics and Gynecology, Chongqing Health Center for Women and Children (Women and Children's Hospital of Chongqing Medical University), No.120 Longshan Road, Yubei District, Chongqing, 401147, China.
Objectives:
To investigate and analyze the factors affecting postoperative urinary retention (POUR) after pelvic floor reconstruction, and to construct and validate a risk prediction model.
Methods:
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.
Results:
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).
Conclusions:
The nomogram model effectively predicts POUR risk, aiding early perioperative identification of high-risk patients.
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