Post-operative urinary retention (POUR) score – Can incomplete bladder emptying after surgery be predicted?

Journal Article (Journal Article)

Introduction And Objectives: Post-surgical urinary retention is a significant potential adverse event which may result in prolonged hospital stay, patient discomfort and avoidable returns to the Emergency Department. While predisposing factors of urinary retention have been previously described, tools to accurately predict post-operative urinary retention (POUR) risk do not currently exist. We aimed to devise an accurate predictive score for POUR. Methods: A single center, retrospective study of patients undergoing ventral, umbilical or inguinal hernia repair between 01/2017 and 1/2018 was performed. POUR was defined as the inability to void within six hours after surgery with bladder scan or catheterized volume >400 ml. Risk factors were identified using simple and multiple logistic regressions. Akaike Information Criterion (AIC) was utilized to select the best model. Area under Receiver Operating Characteristic (AUC) curve was used to evaluate model predictive properties. Results: A total of 244 patients were included in the study. POUR was significantly associated with low body mass index (BMI) (OR 0.9, p<0.01), diabetes mellitus (DM) (OR 4.1, p = 0.02), congestive heart failure (CHF) (OR 9.5, p = 0.04), and surgery length >2 h (OR=2.9, p = 0.01). Beta blocker use was protective (OR 0.2, p = 0.02). Surprisingly, neither a previous diagnosis of benign prostate hyperplasia (OR 1.4, p = 0.6) nor male sex (OR 2.1, p = 0.2) were associated with POUR risk. The final parsimonious model with the smallest AIC was used to generate a POUR risk score = 13*(if surgery > 2 h) + 20*(if diagnosed with CHF) + 13*(if diagnosed with DM) - BMI - 15*(if taking beta blockers). Using a cutoff score of -15, patients with a POUR score greater than -15 were most likely to develop POUR. The sensitivity and specificity of the devised model were 71% and 79%, respectively. Conclusions: A model showing surgery length, CHF, diabetes, low BMI and beta blocker use predicted POUR risk. The simplistic tool may be utilized to streamline care protocols for patients with higher likelihood for POUR.

Full Text

Duke Authors

Cited Authors

  • Medairos, R; Berger, GK; Prebay, ZJ; Foss, H; O'Connor, RC

Published Date

  • September 1, 2020

Published In

Volume / Issue

  • 20 /

Electronic International Standard Serial Number (EISSN)

  • 2405-6030

Digital Object Identifier (DOI)

  • 10.1016/j.pcorm.2020.100120

Citation Source

  • Scopus