Presentation Authors: Robert Medairos*, Garrett Berger, Zachary Prebay, Halle Foss, Joy Liu, Sergey Tarima, Robert O'Connor, Milwaukee, WI
Introduction: Urinary retention is a significant adverse event after surgery which predisposes patients to increased hospital stay and avoidable returns to the Emergency Department. Though risk factors of urinary retention have been previously described, tools to accurately predict risk for POUR 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 12/2017 was performed. POUR was defined as inability to void post-operatively with bladder scan or catheterized volume >400 ml. Possible POUR risk factors included demographics, body mass index (BMI), social history, past medical history, home medication history, surgery time, and volume of fluids administered during surgery. Simple and multiple logistic regressions were performed to identify associated risk factors. AIC (Akaike Information Criterion) was used to select the best model. Area under Receiver Operating Characteristic curve (AUC) was used to evaluate modelâ€™s predictive properties. Analyses were performed using SAS version 9.4 (SAS Institute), and level of significance was considered at P < 0.05.
Results: A total of 244 patients were included in the study. In unadjusted analyses, POUR was significantly associated with beta blocker use (OR 0.2, p=0.02), decreased BMI (OR 0.9, p < 0.01), diabetes mellitus (OR 4.1, p=0.02), congestive heart failure (OR 9.5, p=0.04), and surgery length >2 hours (OR=2.9, p=0.01). Surprisingly, neither benign prostate hyperplasia (OR 1.4, p=0.6) nor male gender (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 > 2Hrs) + 20*(if CHF) + 13*(if DM) - BMI - 15*(if taking beta blockers). The model shows 81% AUC. A 1 unit increase in score value is associated with a 10% increase of POUR odds. 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 was devised showing surgery length, congestive heart failure, diabetes, low BMI and beta blocker use predicted POUR risk. The simplistic tool could be utilized to aid in care protocols for patients with higher risk for POUR. A validation cohort to test accuracy will help further validate the potential accuracy and impact of these findings.