Decision tree model predicts live birth after surgery for moderate-to-severe intrauterine adhesions

• Published in: BMC pregnancy and childbirth Vol. 22; no. 1; p. 78
• Main Authors: Zhu, Ru, Duan, Hua, Xu, Wenbin, Wang, Sha, Gan, Lu, Xu, Qian, Li, Jinjiao
• Format: Journal Article
• Language: English
• Published: England BioMed Central 29.01.2022; BMC
• Subjects: Adhesion; Adult; Amenorrhea; Cervix; Decision making; Decision Trees; Endocrine therapy; Endometrium; Female; Fertility; Humans; Hysteroscopic adhesiolysis; Hysteroscopy; Infertility; Intrauterine adhesion; Live Birth - epidemiology; Logistic Models; Menstruation; Obstetrics; Patients; Predictive Value of Tests; Pregnancy; Pregnancy Complications - surgery; Pregnancy Rate; Reproductive technologies; Retrospective Studies; Sample size; Surgery; Tissue Adhesions - surgery; Ultrasonic imaging; Uterine Diseases - surgery; Uterus; Variables; Womens health; Pregnancy; Intrauterine adhesion; Hysteroscopic adhesiolysis
• ISSN: 1471-2393; 1471-2393
• DOI: 10.1186/s12884-022-04375-x

After 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). A 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. Within 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). The 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.