Predicting Postpartum Urinary Retention After Vaginal Delivery

Objectives: Postpartum urinary retention (PPUR), or the inability to void within 6 hours after birth, is estimated to affect 1.7% to 17.9% of all deliveries. Unrecognized PPUR may result in considerable morbidity, such as bladder distension injury, long-term voiding dysfunction and bladder rupture. We aimed to develop a predictive model of PPUR among patients who had a vaginal delivery.

Methods: We developed a predictive model using birth data from a single academic tertiary care institution. The cases included patients who were diagnosed with PPUR between January 1, 2019 and October 31, 2022 and controls matched by gestational age, mode of delivery, and delivery date (+/- 7 days). The case-control ratio was 1:2. Data was abstracted from the patients’ electronic medical records and the following variables were evaluated: parity (nulliparity), operative vaginal delivery, maternal race (Asian), labor induction, episiotomy, perineal laceration (3rd and 4th degree), BMI, and prolonged 2nd stage of labor (>4 hours). Models were created using Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression. A bootstrap sample was generated to repeat this process multiple times (n=1000 times) for the process of internal validation. Selection of the final predictor variables were chosen based on representation in at least 60% of the bootstrap samples. Logistic regression was then used to evaluate model predictive ability via the area under the curve (AUC) and explained variance of the selected models.

Results: The predictive model was developed from 152 observations (76 cases, 76 controls). Risk factors for PPUR included nulliparity, operative vaginal delivery, Asian maternal race, labor induction, episiotomy, higher order perineal laceration, BMI, and prolonged second stage of labor. A model utilizing nulliparity (OR 3.06 [95% CI, 1.76-5.34]), operative vaginal delivery (OR 6.63 [95% CI, 2.64-16.68]), and Asian maternal race (OR 2.64 [95% CI, 1.17-5.94]) provided an AUC of 0.8 (0.73, 0.86) and an explained variance of 29.7% (Table 1). Adding labor induction did not improve the predictability of the model (p=0.18).

Conclusions: Our study identified three variables (nulliparity, operative vaginal delivery, and Asian maternal race) that, in combination, can be used to identify patients at risk for PPUR. Using a validated predictive model may help by targeting certain patients with prophylactic measures to prevent this complication. External validation studies will be considered in subsequent research.