Construction and validation of a risk prediction model of intermediate cesarean section for primiparous women with failed vaginal delivery trial
10.3760/cma.j.cn114798-20230111-00046
- VernacularTitle:初产妇阴道试产失败中转剖宫产风险预测模型的构建与验证
- Author:
Fangxiang DONG
1
;
Xi CHEN
;
Shasha ZHANG
;
Yaqi FENG
;
Yanna GUAN
;
Chun YUE
;
Xueyan ZHANG
;
Jing XIN
;
Jing KONG
Author Information
1. 济宁医学院附属医院家庭化温馨产房，济宁 272001
- Keywords:
Parturition;
Caesarean section;
Primiparity;
Vaginal trial of labour;
Predicting model
- From:
Chinese Journal of General Practitioners
2023;22(10):1045-1051
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To construct and validate a prediction model for the risk of intermediate cesarean delivery for primiparous women with failed vaginal trial of labor.Methods:Clinical data of 6 128 pregnant women who gave birth in the Affiliated Hospital of Jining Medical College from January 2019 to December 2020 were collected. The puerpera was randomly divided into train set ( n=4 290) and validation set ( n=1 838). The factors influencing the conversion to cesarean section in primiparous women with failed vaginal trial of labor were analyzed with univariate and binary multivariate logistic regression, and a risk prediction model was established based on the influencing factors. The predictive power of the model was assessed by receiver operating characteristic (ROC) curve and the Hosmer-Lemeshow goodness-of-fit test in train set and validation set. Results:Among 6 128 pregnant women 1 042 cases failed in vaginal trial of labor and were transferred to cesarean section. Univariate analysis showed age, occupation, gestational weight gain, days of gestation, body temperature before delivery, fetal heart condition at delivery, fetal abdominal circumference, Bishop score, premature rupture of membranes, gestational illness, mode of induction of labor, labor analgesia, and fetal orientation were significantly associated with converting to cesarean delivery (all P<0.05). The multivariate binary logistic regression analysis showed that the age, gestational weight gain, body temperature, gestational co-morbidities, days of gestation, premature rupture of membranes, amniotic fluid contamination, induction of labor, and abnormal occipital position were independent risk factors for intermediate cesarean delivery ( OR=1.03-8.06, all P<0.05); while height, occupation, Bishop score, and labor analgesia were protective factors for intermediate cesarean delivery ( OR=0.17-0.96, all P<0.05). A risk prediction model was constructed based on the risk factors and protective factors. In train set, the area under the ROC curve(AUC) of the model was 0.902 (95% CI: 0.89-0.92, P<0.001), with the best cutoff value of 0.138, the sensitivity and specificity were 0.837 and 0.825, respectively; and the Hosmer-Lemeshow goodness-of-fit test showed P=0.192. In validation set the AUC of the model was 0.917 (95% CI: 0.90-0.93, P<0.001), and the sensitivity and specificity were 0.826 and 0.851, respectively; the total correct rate of the model was 87.21% (1 603/1 838). Conclusion:The risk prediction model of failed vaginal trial of labor in primiparous women for intermediate cesarean delivery constructed in this study has good clinical prediction efficacy and high correctness rate.
