A Prediction Nomogram for Moderate‐to‐Severe Bronchopulmonary Dysplasia in Chinese Very Preterm Infants With Respiratory Distress: A Multi‑Center Prospective Study

Moderate-to-severe bronchopulmonary dysplasia (msBPD) is a prevalent and severe condition in very preterm infants, contributing to long-term respiratory issues. Developing a predictive model specific to the Chinese population could support early intervention. This research focused on determining risk factors and developing a predictive model for msBPD in very preterm infants with respiratory distress, following the 2018 National Institute of Child Health and Human Development criteria. A prospective multicenter study was conducted across 26 tertiary neonatal intensive care units (NICUs) in China from March 2020 to March 2022. Infants born at < 32 weeks' gestation, admitted within 72 h of birth with a respiratory score ≥ 5, were enrolled. Infants were assigned at random to either a training cohort (800 infants from 18 NICUs) or an external validation cohort (397 infants from 8 NICUs). Predictive factors were identified using multivariate logistic regression and Lasso regression, leading to the development of a prediction nomogram. Key independent predictors included birth weight, surfactant use, early pulmonary hypertension, duration of invasive mechanical ventilation, and necrotizing enterocolitis (Stages II-III). The model demonstrated high accuracy in the training cohort (AUC = 0.844) with good calibration (Hosmer-Lemeshow test, p = 0.247). Independent validation showed consistent discrimination (AUC = 0.849) and calibration (Hosmer-Lemeshow test, p = 0.333), while decision curve analysis confirmed clinical benefit. The developed nomogram-based model offers reliable early msBPD risk assessment in very preterm infants, supporting timely clinical interventions within Chinese NICUs.

Authors

Institutions

Publication Details

Journal
Biotechnology and Applied Biochemistry
Published
2025-02-23
DOI
https://doi.org/10.1002/bab.2718
Primary Topic
Neonatal Respiratory Health Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Prediction Nomogram for Moderate‐to‐Severe Bronchopulmonary Dysplasia in Chinese Very Preterm Infants With Respiratory Distress: A Multi‑Center Prospective Study

Lizhong Du, Yuan Shi, Guannan Bai, Chenhong Wang et al.
1 links
Biotechnology and Applied Biochemistry
Neonatal Respiratory Health Research
article

A Prediction Nomogram for Moderate‐to‐Severe Bronchopulmonary Dysplasia in Chinese Very Preterm Infants With Respiratory Distress: A Multi‑Center Prospective Study

Lizhong Du, Yuan Shi, Guannan Bai, Chenhong Wang, Zheng Chen, Liping Shi
article en

Abstract

Moderate-to-severe bronchopulmonary dysplasia (msBPD) is a prevalent and severe condition in very preterm infants, contributing to long-term respiratory issues. Developing a predictive model specific to the Chinese population could support early intervention. This research focused on determining risk factors and developing a predictive model for msBPD in very preterm infants with respiratory distress, following the 2018 National Institute of Child Health and Human Development criteria. A prospective multicenter study was conducted across 26 tertiary neonatal intensive care units (NICUs) in China from March 2020 to March 2022. Infants born at < 32 weeks' gestation, admitted within 72 h of birth with a respiratory score ≥ 5, were enrolled. Infants were assigned at random to either a training cohort (800 infants from 18 NICUs) or an external validation cohort (397 infants from 8 NICUs). Predictive factors were identified using multivariate logistic regression and Lasso regression, leading to the development of a prediction nomogram. Key independent predictors included birth weight, surfactant use, early pulmonary hypertension, duration of invasive mechanical ventilation, and necrotizing enterocolitis (Stages II-III). The model demonstrated high accuracy in the training cohort (AUC = 0.844) with good calibration (Hosmer-Lemeshow test, p = 0.247). Independent validation showed consistent discrimination (AUC = 0.849) and calibration (Hosmer-Lemeshow test, p = 0.333), while decision curve analysis confirmed clinical benefit. The developed nomogram-based model offers reliable early msBPD risk assessment in very preterm infants, supporting timely clinical interventions within Chinese NICUs.

Biotechnology and Applied BiochemistryVol. 72(4)
Children's Hospital of Zhejiang University (CN), Children's Hospital of Chongqing Medical University (CN), Chongqing Medical University (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 95%
Neonatal Respiratory Health Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.