Risk prediction models for vaginal delivery failure in low-risk primiparas: a systematic review
10.3760/cma.j.cn115682-20231107-01925
- VernacularTitle:低危初产妇阴道试产失败风险预测模型的系统评价
- Author:
Yuhui FANG
1
;
Shuyi ZHANG
;
Hangjia TU
;
Guijuan HE
Author Information
1. 浙江中医药大学护理学院，杭州 310053
- Keywords:
Primipara;
Low-risk;
Vaginal delivery failure;
Prediction model;
Risk assessment;
Systematic review
- From:
Chinese Journal of Modern Nursing
2024;30(25):3458-3464
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To systematically review the risk prediction model for vaginal delivery failure in low-risk primiparas, so as to provide reference for clinical practice and future research.Methods:Literature on the risk prediction model for vaginal delivery failure in low-risk primiparas was retrieved from China National Knowledge Infrastructure, WanFang Data, China Biology Medicine disc, PubMed, Embase, Cochrane Library, CINAHL, Web of Science and so on. The search period was from the establishment of the database to September 20, 2023. Two researchers independently screened literature, extracted data, and evaluated the risk of bias in the included studies.Results:A total of 10 articles were included, involving 14 models. Twelve models were constructed using Logistic regression, and the area under the receiver operating characteristic curve of the models ranged from 0.680 to 0.847. Common predictive factors of the model involved age of pregnant woman, height of pregnant woman, pre-pregnancy body mass index, gestational weight gain, gestational week, fetal birth weight, induction method, fetal biological measurements, and pre-delivery cervical Bishop score.Conclusions:The predictive performance of the vaginal delivery failure risk prediction model for low-risk primiparas is good, but the model construction method is relatively simple, and the overall bias risk is high. The model needs to be further optimized through machine learning, artificial intelligence, and other means, and extensively validated externally.
