Risk Factors Analysis and Predictive Model Development for Postpartum Hem-orrhage in Gestational Diabetes Mellitus
10.3969/j.issn.1003-6946.2025.11.013
- VernacularTitle:妊娠期糖尿病发生产后出血的危险因素分析及预测模型建立
- Author:
Ning HAN
1
;
Yizhan WANG
1
;
Xinyuan CHANG
1
Author Information
1. 郑州大学第三附属医院妇产科,河南 郑州 450052
- Publication Type:Journal Article
- Keywords:
Gestational diabetes mellitus;
Postpartum hemorrhage;
Risk factors;
Nomogram
- From:
Journal of Practical Obstetrics and Gynecology
2025;41(11):928-934
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To identify the risk factors for postpartum hemorrhage(PPH)in patients with gestational diabetes mellitus(GDM)and to develop and validate a predictive model.Methods:A retrospective study was conducted on GDM patients who delivered at The Third Affiliated Hospital of Zhengzhou University between Janu-ary 2021 and December 2023.A total of 137 GDM patients with PPH were included in the case group,and 190 GDM patients without PPH were included in the control group.Univariate analysis and multivariate Logistic regres-sion analysis were used to identify independent risk factors for PPH in GDM patients.Anomogram prediction mod-el was subsequently constructed.The predictive performance of the model was evaluated by the Hosmer-Leme-show goodness-of-fit test,receiver operating characteristic(ROC)curve,Bootstrap resampling method,and deci-sion curve analysis(DCA).Results:Univariate analysis revealed statistically significant differences between the two groups in multiple factors(P<0.05),including age≥35 years,pre-pregnancy body mass index(BMI)≥24 kg/m2,suboptimal glycemic control,assisted reproduction,gestational anemia,polyhydramnios,macrosomia,acute chorioamnionitis,gestational hypertension,prenatal fasting blood glucose(FBG),prenatal glycosylated he-moglobin(HbA1c),fibrinogen(FIB),postpartum blood loss,dystocia,neonatal admission to ICU,neonatal Apgar score at 1 minute,and Apgar score at 5 minutes.Multivariate Logistic regression analysis indicated that age≥35 years,pre-pregnancy BMI≥24 kg/m2,suboptimal glycemic control,gestational anemia,macrosomia,polyhydram-nios,and elevated prenatal HbA1c levels were independent risk factors for PPH(OR>1,P<0.05),while elevat-ed FIB levels were identified as a protective factor for PPH(OR<1,P<0.05).The nomogram demonstrated good calibration(Hosmer-Lemeshow test:χ2=6.367,DF=8,P=0.606).The area under the ROC curve(AUC)was 0.821(95%CI 0.774-0.868),with a sensitivity of 71.5%and a specificity of 83.7%,indicating good discrimi-native ability of the model.Internal validation using the Bootstrap resampling method showed a C-index of 0.821,suggesting good consistency and predictive accuracy.DCA curve further confirmed that the model had favorable clinical application value.Conclusions:age≥35 years,pre-pregnancy BMI≥24 kg/m2,suboptimal glycemic con-trol,gestational anemia,macrosomia,polyhydramnios,and elevated prenatal HbA1c levels are independent risk factors for PPH in GDM patients,while elevated FIB levels are identified as an independent protective factor.The constructed prediction model for PPH in GDM patients exhibits good discriminative ability,calibration,and predic-tive performance,demonstrating high clinical application value.
