Predicting Time to Recovery From Acute Urinary Retention in Hospitalized Patients: Development and Validation of a Clinical Prediction Model

Purpose: Acute urinary retention (AUR) is a common complication in hospitalized patients with unpredictable recovery times. We aimed to develop and validate a clinical prediction model for recovery from AUR within 14 days.Methods: A prospective cohort study was conducted from March 2024 to July 2025 at a tertiary care center. Adult patients (n=126) with AUR were enrolled upon urological consultation. Males with prostate volume >30 g were excluded. Patients underwent standardized voiding trials every 3–4 days, with success defined as postvoid residual <100 mL. Multivariable logistic regression was used to identify predictors of recovery within 14 days.Results: The cohort comprised 84 males (66.7%) and 42 females (33.3%), mean age 71.9±14.2 years. Overall, 81.7% achieved successful voiding within 14 days. The prediction model demonstrated excellent discrimination (area under the curve [AUC], 0.83; 95% confidence interval [CI], 0.76–0.90) with 4 independent predictors: age <70 years (OR, 4.11; 95% CI, 2.18–7.76; P=0.008), male sex (OR, 9.09; 95% CI, 4.35–19.01; P<0.001), postoperative etiology (OR, 4.38; 95% CI, 2.26–8.48; P=0.004), and retention volume ≤450 mL (OR, 4.55; 95% CI, 2.17–9.52; P=0.017). Bootstrap validation confirmed model stability (optimism-corrected AUC=0.81).Conclusions: Our clinical prediction model reliably identifies patients at risk for prolonged urinary retention using 4 simple bedside parameters. Implementation may optimize catheter management strategies and improve patient outcomes through risk-stratified care pathways.