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Prediction of bronchopulmonary dysplasia by postnatal age in extremely premature infants
Matthew M Laughon1, John C Langer, Carl L Bose
1Department of Pediatrics, University of North Carolina, Chapel Hill, North Carolina 27599-7596, USA. matt_laughon@med.unc.edu
Insights
Identifying risk factors for bronchopulmonary dysplasia in extremely premature infants is crucial for prognosis and treatment. A new web-based tool accurately predicts BPD risk using readily available clinical data.
Area of Science:
- Neonatal Medicine
- Pediatric Pulmonology
- Clinical Epidemiology
Background:
- Identifying risk factors for bronchopulmonary dysplasia (BPD) in extremely premature infants aids in prognosis, preventive strategies, and clinical trial stratification.
- Early identification of BPD risk is essential for optimizing care in vulnerable neonates.
Purpose of the Study:
- To identify risk factors for bronchopulmonary dysplasia (BPD) and mortality in extremely premature infants based on postnatal day.
- To determine which risk factors enhance predictive accuracy for BPD.
- To develop a web-based clinical estimator for predicting BPD or death risk.
Main Methods:
- Infants (23-30 weeks' gestation) from the Neonatal Research Network Benchmarking Trial (2000-2004) were assessed.
- Models for BPD risk were developed and validated at six postnatal ages.
- Predictive accuracy was evaluated using the C statistic, incorporating gestational age, birth weight, race, sex, respiratory support, and FiO2.
Main Results:
- Prediction of BPD risk improved with advancing postnatal age, with C statistics ranging from 0.793 on Day 1 to 0.854 on Day 28.
- Gestational age was the strongest predictor on Postnatal Days 1 and 3.
- Type of respiratory support became the strongest predictor from Postnatal Day 7 to Day 28.
- A web-based risk estimator is available at https://neonatal.rti.org.
Conclusions:
- The probability of developing bronchopulmonary dysplasia (BPD) in extremely premature infants can be accurately determined.
- A limited set of readily available clinical information is sufficient for accurate BPD risk prediction.
- The developed web-based tool offers a practical method for assessing BPD risk in clinical settings.
Rationale:
Benefits of identifying risk factors for bronchopulmonary dysplasia in extremely premature infants include providing prognostic information, identifying infants likely to benefit from preventive strategies, and stratifying infants for clinical trial enrollment.
Objectives:
To identify risk factors for bronchopulmonary dysplasia, and the competing outcome of death, by postnatal day; to identify which risk factors improve prediction; and to develop a Web-based estimator using readily available clinical information to predict risk of bronchopulmonary dysplasia or death.
Methods:
We assessed infants of 23-30 weeks' gestation born in 17 centers of the Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network and enrolled in the Neonatal Research Network Benchmarking Trial from 2000-2004.
Measurements And Main Results:
Bronchopulmonary dysplasia was defined as a categorical variable (none, mild, moderate, or severe). We developed and validated models for bronchopulmonary dysplasia risk at six postnatal ages using gestational age, birth weight, race and ethnicity, sex, respiratory support, and Fi(O(2)), and examined the models using a C statistic (area under the curve). A total of 3,636 infants were eligible for this study. Prediction improved with advancing postnatal age, increasing from a C statistic of 0.793 on Day 1 to a maximum of 0.854 on Day 28. On Postnatal Days 1 and 3, gestational age best improved outcome prediction; on Postnatal Days 7, 14, 21, and 28, type of respiratory support did so. A Web-based model providing predicted estimates for bronchopulmonary dysplasia by postnatal day is available at https://neonatal.rti.org.
Conclusions:
The probability of bronchopulmonary dysplasia in extremely premature infants can be determined accurately using a limited amount of readily available clinical information.