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. 2024 Jun 7;24(1):331.
doi: 10.1186/s12905-024-03171-3.

Development and validation of a prediction model for postoperative urinary retention after prolapse surgery: A retrospective cohort study

Min Ju Kim #  1 , Sungyoung Lee #  2 , So Yeon Lee  3 , Sumin Oh  4 , Myung Jae Jeon  5   6
Affiliations

Development and validation of a prediction model for postoperative urinary retention after prolapse surgery: A retrospective cohort study

Min Ju Kim et al. BMC Womens Health. .

Abstract

Background: Postoperative urinary retention (POUR), a common condition after prolapse surgery with potential serious sequelae if left untreated, lacks a clearly established optimal timing for catheter removal. This study aimed to develop and validate a predictive model for postoperative urinary retention lasting > 2 and > 4 days after prolapse surgery.

Methods: We conducted a retrospective review of 1,122 patients undergoing prolapse surgery. The dataset was divided into training and testing cohorts. POUR was defined as the need for continuous intermittent catheterization resulting from a failed spontaneous voiding trial, with passing defined as two consecutive voids ≥ 150 mL and a postvoid residual urine volume ≤ 150 mL. We performed logistic regression and the predicted model was validated using both training and testing cohorts.

Results: Among patients, 31% and 12% experienced POUR lasting > 2 and > 4 days, respectively. Multivariable logistic model identified 6 predictors. For predicting POUR, internal validation using cross-validation approach showed good performance, with accuracy lasting > 2 (area under the curve [AUC] 0.73) and > 4 days (AUC 0.75). Split validation using pre-separated dataset also showed good performance, with accuracy lasting > 2 (AUC 0.73) and > 4 days (AUC 0.74). Calibration curves demonstrated that the model accurately predicted POUR lasting > 2 and > 4 days (from 0 to 80%).

Conclusions: The proposed prediction model can assist clinicians in personalizing postoperative bladder care for patients undergoing prolapse surgery by providing accurate individual risk estimates.

Keywords: Clinical decision-making; Pelvic organ prolapse; Urinary retention.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Nomogram for predicting the risk of postoperative urinary retention > 2 days (A) and > 4 days (B). ICG, iliococcygeus suspension; PVR, postvoid residual; SCP, sacrocolpopexy; SSLF, sacrospinous ligament fixation; USLS, uterosacral ligament suspension
Fig. 2
Fig. 2
(A) Prediction performance of the proposed model. Internal validation using five-fold cross-validation (green) and split validation using the testing cohort (red). AUC, area under the curve; CI, confidence interval; POUR, postoperative urinary retention. (B) Calibration curve of the prediction model. Dots indicate observed probabilities of each bin, and the blue line represents the calibration curve. The grey shading indicates 95% confidence intervals. POUR, postoperative urinary retention
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