Observational studyBMC pregnancy and childbirth2022
Decision tree model predicts live birth after surgery for moderate-to-severe intrauterine adhesions.
Observational study in BMC pregnancy and childbirth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The epidemiology, clinical burden, and prevention of intrauterine adhesions (IUAs) related to surgically induced endometrial trauma: a systematic literature review and selective meta-analyses.Human reproduction update · 2025Pooled it
- Intrauterine adhesion in ultrasound-guided manual vacuum aspiration (USG-MVA) versus electric vacuum aspiration (EVA): a randomised controlled trial.BMC pregnancy and childbirth · 2024Trial
- Development of a one-step office hysteroscopic lightweight artificial intelligence application for subfertility risk stratification of intrauterine adhesions.Fundamental research · 2026Article
- Prognostic Factors and Predictive Models for Reproductive Outcomes in Patients with Intrauterine Adhesions: A Review.International journal of women's health · 2026Review
- Visualized hysteroscopic artificial intelligence fertility assessment system for endometrial injury: an image-deep-learning study.Annals of medicine · 2025Article
- Enhancing exosome stability and delivery with natural polymers to prevent intrauterine adhesions and promote endometrial regeneration: a review.Journal of nanobiotechnology · 2025Review
- Developing and validating a prediction model of live birth in patients with moderate-to-severe intrauterine adhesions: a new approach with endometrial morphology measurement by 3D transvaginal ultrasound.Quantitative imaging in medicine and surgery · 2024Article
- Artificial intelligence-driven prognostic system for conception prediction and management in intrauterine adhesions following hysteroscopic adhesiolysis: a diagnostic study using hysteroscopic images.Frontiers in bioengineering and biotechnology · 2024Article
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Authors and funding
7 authors.
Funding
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Abstract
backgroundAfter treatment of intrauterine adhesions, the rate of re-adhesion is high and the pregnancy outcome unpredictable and unsatisfactory. This study established and verified a decision tree predictive model of live birth in patients after surgery for moderate-to-severe intrauterine adhesions (IUAs).
methodsA retrospective observational study initially comprised 394 patients with moderate-to-severe IUAs diagnosed via hysteroscopy. The patients underwent hysteroscopic adhesiolysis from January 2013 to January 2017, in a university-affiliated hospital. Follow-ups to determine the rate of live birth were conducted by telephone for at least the first postoperative year. A classification and regression tree algorithm was applied to establish a decision tree model of live birth after surgery.
resultsWithin the final population of 374 patients, the total live birth rate after treatment was 29.7%. The accuracy of the model was 83.8%, and the area under the receiver operating characteristic curve (AUC) was 0.870 (95% CI 7.699-0.989). The root node variable was postoperative menstrual pattern. The predictive accuracy of the multivariate logistic regression model was 70.3%, and the AUC was 0.835 (95% CI 0.667-0.962).
conclusionsThe decision tree predictive model is useful for predicting live birth after surgery for IUAs; postoperative menstrual pattern is a key factor in the model. This model will help clinicians make appropriate clinical decisions during patient consultations.
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