Related Experiment Video
Updated: Oct 15, 2025
Intratracheal Instillation of Stem Cells in Term Neonatal Rats
Published on: May 4, 2020
Construction of early risk prediction models for bronchopulmonary dysplasia in preterm infants
Insights
This study identifies key risk factors like birth weight and respiratory support for bronchopulmonary dysplasia (BPD) in preterm infants. Developed prediction models for BPD on days 7 and 14 effectively forecast infant outcomes.
Area of Science:
- Neonatal Medicine
- Pediatric Pulmonology
- Clinical Prediction Modeling
Background:
- Bronchopulmonary dysplasia (BPD) is a significant complication in preterm infants.
- Early identification of infants at high risk for BPD is crucial for timely intervention.
Purpose of the Study:
- To develop and validate risk prediction models for BPD in preterm infants.
- To identify key risk factors for BPD development on postnatal days 3, 7, and 14.
Main Methods:
- Retrospective analysis of 414 preterm infants (<32 weeks GA, <1500g BW).
- Logistic regression and ROC curve analysis to identify risk factors and evaluate model performance.
- Models constructed using variables including birth weight, asphyxia, RDS, chorioamnionitis, pneumonia, FiO2, and respiratory support.
Main Results:
- Birth weight, asphyxia, grade III-IV RDS, acute chorioamnionitis, interstitial pneumonia, FiO2, and respiratory support mode were significant risk factors for BPD.
- Prediction models for postnatal days 7 and 14 demonstrated high predictive accuracy (AUC 0.876 and 0.880, respectively).
Conclusions:
- Birth weight and specific clinical factors are key predictors of BPD.
- The developed models on postnatal days 7 and 14 provide effective tools for BPD risk prediction in preterm infants.
Objectives:
To construct risk prediction models for bronchopulmonary dysplasia (BPD) in preterm infants on postnatal days 3, 7, and 14.
Methods:
A retrospective analysis was performed on the medical data of 414 preterm infants, with a gestational age of <32 weeks and a birth weight (BW) of <1 500 g, who were admitted to the neonatal intensive care unit from July 2019 to April 2021. According to the diagnostic criteria for BPD revised in 2018, they were divided into a BPD group with 98 infants and a non-BPD group with 316 infants. The two groups were compared in terms of general status, laboratory examination results, treatment, and complications. The logistic regression model was used to identify the variables associated with BPD. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of models.
Results:
The logistic regression analysis showed that BW, asphyxia, grade III-IV respiratory distress syndrome (RDS), acute chorioamnionitis, interstitial pneumonia, fraction of inspired oxygen (FiO2), and respiratory support mode were the main risk factors for BPD (P<0.05). The prediction models on postnatal days 7 and 14 were established as logit (P7) =-2.049-0.004×BW (g) +0.686×asphyxia (no=0, yes=1) +1.842×grade III-IV RDS (no=0, yes=1) +0.906×acute chorioamnionitis (no=0, yes=1) +0.506×interstitial pneumonia (no=0, yes=1) +0.116×FiO2 (%) +0.816×respiratory support mode (no=0, nasal tube=1, nasal continuous positive airway pressure=2, conventional mechanical ventilation=3, high-frequency mechanical ventilation=4) and logit (P14) =-1.200-0.004×BW (g) +0.723×asphyxia+2.081×grade III-IV RDS+0.799×acute chorioamnionitis+0.601×interstitial pneumonia+0.074×FiO2 (%) +0.800×respiratory support mode, with an area under the ROC curve (AUC) of 0.876 and 0.880, respectively, which was significantly larger than the AUC of the prediction model on postnatal day 3 (P<0.05).
Conclusions:
BW, asphyxia, grade III-IV RDS, acute chorioamnionitis, interstitial pneumonia, FiO2, and respiratory support mode are the main risk factors for BPD and can be used to construct risk prediction models. The prediction models on postnatal days 7 and 14 can effectively predict BPD.
