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

Authors :
Kim, Min Ju
Lee, Sungyoung
Lee, So Yeon
Oh, Sumin
Jeon, Myung Jae
Source :
BMC Women's Health. 6/7/2024, Vol. 24 Issue 1, p1-7. 7p.
Publication Year :
2024

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14726874
Volume :
24
Issue :
1
Database :
Academic Search Index
Journal :
BMC Women's Health
Publication Type :
Academic Journal
Accession number :
177743477
Full Text :
https://doi.org/10.1186/s12905-024-03171-3