SynthesisBMC women's health2025
Risk prediction models for stress urinary incontinence after pelvic organ prolapse (POP) surgery: a systematic review and meta-analysis.
Synthesis in BMC women's health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Comparative Analysis of Logistic Regression and Machine Learning Algorithms for Predicting De Novo Stress Urinary Incontinence or Symptomatic Worsening Following Pelvic Floor Reconstruction: A Multicenter Study.International journal of women's health · 2026Article
- Correction: Risk prediction models for stress urinary incontinence after pelvic organ prolapse (POP) surgery: a systematic review and meta-analysis.BMC women's health · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors.
Funding
Abstract
objectiveTo systematically evaluate existing developed and validated predictive models for stress urinary incontinence after pelvic floor reconstruction.
methodsRelevant literature in PubMed, Embase, Web of Science, Cochrane Library, OVID, China National Knowledge Infrastructure(CNKI), Wan Fang Database, VIP database and Chinese Biomedical Literature Service System (SinoMed) were search from inception to 1 March 2024. Literature screening and data extraction were performed independently by two researchers. The chosen study's statistics included study design, data sources, outcome definitions, sample size, predictors, model development, and performance. The Predictive Modelling Risk of Bias Assessment Tool (PROBAST) checklist was used to assess risk of bias and applicability.
resultsA total of 7 studies containing 9 predictive models were included. All studies had a high risk of bias, primarily due to retrospective design, small sample sizes, single-center trials, lack of blinding, and missing data reporting. The meta-analysis revealed moderate heterogeneity (I² = 68.8%). The pooled AUC value of the validated models was 0.72 (95% CI: 0.65, 0.79), indicating moderate predictive ability.
conclusionThe prediction models evaluated demonstrated moderate discrimination, but significant bias and methodological flaws. The meta-analysis revealed moderate heterogeneity (I² = 68.8%) among the included studies, reflecting differences in study populations, predictors, and methods, which limits the generalizability of the findings. Despite these challenges, these models highlight the potential to identify high-risk patients for targeted interventions to improve surgical outcomes and reduce postoperative complications. The findings suggest that by integrating these models into clinical decision-making, clinicians can better tailor surgical plans and preoperative counseling, thereby improving patient satisfaction and reducing the incidence of postoperative stress urinary incontinence. Future research should follow TRIPOD and PROBAST principles, focus on addressing sources of heterogeneity, improve model development through robust designs, large sample sizes, comprehensive predictors, and novel modelling approaches, and validate tools that can be effectively integrated into clinical decision-making to manage stress urinary incontinence after pelvic floor reconstruction.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.