ArticleFrontiers in pediatrics2025
Interpretable machine learning model for comparing and validating three diagnostic criteria for bronchopulmonary dysplasia in predicting value of respiratory prognosis of preterm infants: a retrospective cohort study.
Article in Frontiers in pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Gestational age-specific metabolic biomarkers for early prediction of bronchopulmonary dysplasia following standardized enteral feeding.Journal of perinatology : official journal of the California Perinatal Association · 2026Article
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9 authors.
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Abstract
Background: Comparison and validation of the predictive value of three diagnostic criteria for bronchopulmonary dysplasia for respiratory prognosis of preterm infants with gestational age <32 weeks. Methods: This retrospective cohort study was conducted to collect clinical data of 397 preterm infants. On the basis of the follow-up results, the enrolled population was divided into a respiratory adverse outcome group and a normal outcome group. The 2001 NICHD, the 2018 NICHD, and the 2019 NRN criteria were used to diagnose and grade BPD in preterm infants. The dataset was randomly divided, with 70% used for model training and 30% used for model validation. The extreme gradient boosting machine learning algorithm was used for model training. Furthermore, the SHapley additive exPlanation analysis method was utilized to visually interpret the results of the machine learning model. Results: A total of 397 preterm infants were included. In the training set, prediction models based on the 2001 NICHD, 2018 NICHD, and 2019 NRN criteria achieved AUC values of 0.747, 0.804, and 0.789, with corresponding accuracies of 0.740, 0.765, and 0.765. In the test set, the respective AUC values were 0.694, 0.747, and 0.752, and accuracies were 0.750, 0.800, and 0.750. Based on the DeLong's method, comparisons of ROC curves between the training and test sets revealed that both the 2018 NICHD and 2019 NRN criteria demonstrated significantly higher AUC than the 2001 NICHD criteria (training set: Conclusions: Both the 2018 NICHD and 2019 NRN criteria for BPD show better and similar predictive values for respiratory adverse outcomes in preterm infants, and both are superior to the 2001 NICHD criteria. The top two factors affecting the respiratory prognosis of preterm infants are the severity of BPD and early invasive mechanical ventilation.
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