Establishment and verification of a risk prediction model for admission sepsis in preterm infants
10.3969/j.issn.1673-9701.2025.27.007
- VernacularTitle:早产儿入院败血症风险预测模型的构建与验证
- Author:
Xinxin CAI
1
;
Xiayang WU
1
Author Information
1. 厦门市儿童医院药学部,福建厦门 361006
- Publication Type:Journal Article
- Keywords:
Preterm infants;
Sepsis;
Risk prediction model;
Nomogram;
Risk factors
- From:
China Modern Doctor
2025;63(27):32-36,45
- CountryChina
- Language:Chinese
-
Abstract:
Objective To construct a risk prediction model for admission sepsis in preterm infants,providing a basis for early clinical identification and intervention of admission sepsis.Methods Data of preterm infants admitted to Xiamen Children's Hospital from January 2020 to December 2023 were retrospectively collected and used for model construction.According to whether sepsis occurred after admission,they were divided into sepsis group(n=65)and non-sepsis group(n=394).LASSO regression combined with multivariate Logistic regression were used to screen risk factors,and a nomogram prediction model was constructed.External validation of the model was performed with 174 preterm infants admitted from January to December 2024.Results Gestational age,Apgar score ≤7 points at 10 minutes,total bilirubin,respiratory failure,and respiratory rate were identified as independent risk factors for admission sepsis in preterm infants.The area under the curve(AUC)of the training set was 0.853,and the external validation AUC was 0.937.The calibration results in the calibration curve were close to the ideal curve(Hosmer-Lemeshow test x2=6.599,P=0.580).Conclusion The prediction model developed based on seven bedside indicators demonstrates excellent performance,enabling rapid risk stratification and antimicrobial decision-making without the need for microbiological culture support.
