A nomogram to predict bronchopulmonary dysplasia in very preterm and/or very low birth weight infants with early-onset sepsis

Early-onset sepsis (EOS) may increase the risk of bronchopulmonary dysplasia (BPD) in very preterm and/or very low birth weight infants, but prediction tools tailored to this population are limited. We aimed to develop and validate a hospitalization-based model for predicting BPD in infants with EOS. This multicenter retrospective study included infants with gestational age < 32 weeks and/or birth weight < 1500 g diagnosed with EOS at three tertiary neonatal intensive care units between January 2023 and December 2024. Infants from Qilu Hospital of Shandong University and Beijing Friendship Hospital formed the development cohort (n = 255), and infants from Cangzhou Central Hospital served as the external validation cohort (n = 85). BPD was defined by the requirement for respiratory support at 36 + 0/7 weeks’ postmenstrual age. Predictors were selected using LASSO regression and entered into multivariable logistic regression to construct a nomogram. Model performance was assessed by discrimination, calibration, and Brier score, with internal validation using 1,000 bootstrap resamples. Among 340 infants, five predictors were retained in the final model: gestational age, surfactant administration, purulent meningitis, late-onset sepsis, and assisted reproductive technology. In the development cohort, the model showed good discrimination (C-index 0.785, 95% CI 0.727–0.842) and overall accuracy (Brier score 0.178). In the external validation cohort, the model demonstrated acceptable discrimination (AUC 0.772, 95% CI 0.667–0.878) and good overall accuracy (Brier score 0.191). We developed and validated a pragmatic hospitalization-based model for predicting BPD in very preterm and/or very low birth weight infants with EOS. This EOS-specific tool may support in-hospital risk stratification and targeted prevention during the NICU course. However, further validation in larger and more diverse populations is warranted before routine clinical implementation.

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Publication Details

Journal
BMC Pediatrics
Published
2026-03-27
DOI
https://doi.org/10.1186/s12887-026-06763-0
Primary Topic
Neonatal Respiratory Health Research
Type
article
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article

A nomogram to predict bronchopulmonary dysplasia in very preterm and/or very low birth weight infants with early-onset sepsis

Jialin Wen, Qianqian Jiang, Yan Li, Xiaowei Sun et al.
BMC Pediatrics
Neonatal Respiratory Health Research
article

A nomogram to predict bronchopulmonary dysplasia in very preterm and/or very low birth weight infants with early-onset sepsis

Jialin Wen, Qianqian Jiang, Yan Li, Xiaowei Sun, Rui Jing, Wenying Meng
article en

Abstract

Early-onset sepsis (EOS) may increase the risk of bronchopulmonary dysplasia (BPD) in very preterm and/or very low birth weight infants, but prediction tools tailored to this population are limited. We aimed to develop and validate a hospitalization-based model for predicting BPD in infants with EOS. This multicenter retrospective study included infants with gestational age < 32 weeks and/or birth weight < 1500 g diagnosed with EOS at three tertiary neonatal intensive care units between January 2023 and December 2024. Infants from Qilu Hospital of Shandong University and Beijing Friendship Hospital formed the development cohort (n = 255), and infants from Cangzhou Central Hospital served as the external validation cohort (n = 85). BPD was defined by the requirement for respiratory support at 36 + 0/7 weeks’ postmenstrual age. Predictors were selected using LASSO regression and entered into multivariable logistic regression to construct a nomogram. Model performance was assessed by discrimination, calibration, and Brier score, with internal validation using 1,000 bootstrap resamples. Among 340 infants, five predictors were retained in the final model: gestational age, surfactant administration, purulent meningitis, late-onset sepsis, and assisted reproductive technology. In the development cohort, the model showed good discrimination (C-index 0.785, 95% CI 0.727–0.842) and overall accuracy (Brier score 0.178). In the external validation cohort, the model demonstrated acceptable discrimination (AUC 0.772, 95% CI 0.667–0.878) and good overall accuracy (Brier score 0.191). We developed and validated a pragmatic hospitalization-based model for predicting BPD in very preterm and/or very low birth weight infants with EOS. This EOS-specific tool may support in-hospital risk stratification and targeted prevention during the NICU course. However, further validation in larger and more diverse populations is warranted before routine clinical implementation.

BMC Pediatrics
Weifang Medical University (CN), Cangzhou Central Hospital (CN), Weifang People's Hospital (CN), Beijing Friendship Hospital (CN), Qilu Hospital of Shandong University (CN)
Gender equality
Openalex Percentile: Top 4%
Neonatal Respiratory Health Research
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