Research on the Prediction Model of Full-term Neonatal Mortality
10.11969/j.issn.1673-548X.2025.06.025
- VernacularTitle:足月新生儿死亡预测模型的研究
- Author:
Mingming ZHANG
1
;
Meng ZHANG
1
;
Xin ZHANG
1
Author Information
1. 221009 徐州市中心医院
- Publication Type:Journal Article
- Keywords:
Term neonatal;
High risk factors;
Mortality;
Prediction model
- From:
Journal of Medical Research
2025;54(6):138-142
- CountryChina
- Language:Chinese
-
Abstract:
Objective Develop a prediction model for full-term neonatal mortality and conduct internal validation.Methods 86 full-term newborns who died in the pediatric department of Xuzhou Central Hospital from January 1,2015 to December 31,2023 were selected.According to the sample estimation method,135 full-term infants who were hospitalized during the same period were randomly selected as the control group.Clinical data such as maternal and child birth history,blood routine within 24hours after birth,coagulation function,arterial carbon dioxide pressure(PaCO2),and serum total bilirubin were collected.Using single factor analysis,stepwise regres-sion,and multiple Logistic regression analysis to screen possible predictive factors and establish a predictive model.The receiver operating characteristic(ROC)curve was used to evaluate the discriminative power of the model,and Hosmer Lemeshow was used to test the calibra-tion of the evaluation model.Bootstrap method was used for internal validation.Results Amniotic fluid contamination(OR=3.818,95％CI:1.009-14.447,P=0.048),coagulation dysfunction(OR=12.981,95％CI 3.732-45.152,P＜0.001),gynecological inflamma-tory diseases(OR=7.203,95％CI:1.216-42.659,P=0.03),mechanical ventilation(OR=54.451,95％CI:12.913-229.619,P＜0.001),PCO2(OR=1.131,95％CI:1.055-1.212,P=0.001),and serum lactate(OR=4.540,95％CI:2.561-8.046,P＜0.001)are independent influencing factors of full-term infant mortality,which can predict the occurrence of neonatal mortality in full-term infants(sensitivity 75.8％,specificity 87.0％,AUC=0.814).The Hosmer Lemeshow test showed that the model had good consis-tency with the actual occurrence probability of full-term neonatal mortality in clinical practice(x2=3.787,P=0.876).After internal validation by Bootstrap,the model had good discrimination(AUC=0.849).Conclusion A predictive model for mortality risk factors can be established based on maternal pregnancy history and clinical data within 24hours after full-term birth,which helps to make clinical decisions in advance.
