ArticlePeerJ2025
Development of a risk prediction model for postpartum stress urinary incontinence: a multicenter retrospective longitudinal study in Indonesia.
Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Magnitude and factors associated with urinary incontinence among postpartum women in Northwest Ethiopia.Maternal health, neonatology and perinatology · 2026Article
- Long-term course and predictors of postpartum urinary incontinence: a three-year cohort in Portuguese women.World journal of urology · 2026Article
- Development of an interpretable machine learning model for predicting stress urinary incontinence following the delivery of a first child.BMC pregnancy and childbirth · 2026Article
- Clinical outcomes of pelvic floor muscle training, electrical stimulation, and magnetic stimulation in women with postpartum stress urinary incontinence: a retrospective cohort study.BMC women's health · 2026Article
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Authors and funding
6 authors.
Funding
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Abstract
Background: The prevalence of urinary incontinence (UI) during pregnancy and the postpartum period can have significant negative impacts, including on the quality of life and economic burden for affected women. Objective: The objective of this study was to develop risk-predictive models for postpartum stress urinary incontinence (SUI) among women in Indonesia. Methods: Between January 2023 and March 2023, 430 postpartum women, aged 18 years or older, who were admitted to two study hospitals in Indonesia, were enrolled in this study. Telephone follow-up was conducted at six weeks postpartum to assess the presence of SUI. The Least Absolute Shrinkage and Selection Operator (LASSO) method was utilized to identify the relevant variables, and generalized linear models (GLM) were employed to establish predictive models for postpartum SUI. The models were internally validated using a bootstrapping method with 1,000 resamplings to assess discrimination and calibration. Results: The analysis included 430 participants, among whom the prevalence of postpartum SUI was found to be 21% (90 out of 430). The predictive model for postpartum SUI included pre-pregnancy body mass index (BMI), Kegel exercises, constipation, fetal weight, SUI during pregnancy, and mode of delivery. The models demonstrated satisfactory calibration, as indicated by the Hosmer-Lemeshow test ( Conclusion: This study successfully developed predictive models for SUI among postpartum women in Indonesia. The implementation of this model may serve as a valuable tool for identifying high-risk individuals at post-delivery stages, aiding in the prevention and management of postpartum SUI.
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