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Predicting risk for bronchopulmonary dysplasia: selection criteria for clinical trials
R A Sinkin1, C Cox, D L Phelps
1Department of Pediatrics (Neonatology), University of Rochester Medical Center, New York 14642.
Insights
Early identification of infants at risk for bronchopulmonary dysplasia is crucial for clinical trial enrollment. Predictive models using birth weight and respiratory support accurately identify neonates needing oxygen at 28 days.
Area of Science:
- Neonatology
- Pediatric Pulmonology
- Clinical Trial Design
Background:
- Bronchopulmonary dysplasia (BPD) is a significant complication in premature infants.
- Early identification of neonates at high risk for BPD is essential for targeted interventions and clinical trial enrollment.
Purpose of the Study:
- To develop and validate predictive models for identifying neonates likely to require supplemental oxygen at 28 days.
- To stratify neonates into risk groups (low, moderate, high) for BPD development.
Main Methods:
- Logistic regression models were developed using data from 160 neonatal intensive care unit survivors.
- Predictors included birth weight, gestational age, Apgar score, and respiratory support parameters (peak inspiratory pressure, mean airway pressure).
- Models were prospectively validated on three independent datasets totaling 238 neonates.
Main Results:
- A 12-hour model predicted oxygen requirement using birth weight, gestational age, 5-minute Apgar score, and peak inspiratory pressure.
- A 10-day model used birth weight, gestational age, peak inspiratory pressure, and mean airway pressure.
- Both models accurately classified neonates into risk categories, with low-risk groups showing <10% incidence of 28-day oxygen requirement.
Conclusions:
- Logistic regression models effectively predict the need for supplemental oxygen at 28 days in neonates.
- These models facilitate early risk stratification for bronchopulmonary dysplasia, aiding clinical trial recruitment.
- Validated predictive tools can optimize resource allocation and therapeutic strategies in neonatal care.
Abstract:
Early identification of neonates in whom bronchopulmonary dysplasia is most likely to develop permits appropriate enrollment into clinical trials testing early intervention therapies for the prevention or treatment of bronchopulmonary dysplasia. Analysis of 160 neonatal intensive care unit survivors to 28 days revealed that supplemental oxygen requirement at 28 days could be predicted by a logistic regression including (1) birth weight, gestational age, 5-minute Apgar score, and peak inspiratory pressure at 12 hours for 12-hour-old neonates and (2) birth weight, gestational age, peak inspiratory pressure at 12 hours, and mean airway pressure at 10 days for 10-day-old neonates. These two regression analyses were applied prospectively to three new data sets totaling 238 neonates to test their predictive ability. Neonates were classified into low-, moderate-, or high-risk groups on the basis of their predicted probability of requiring oxygen supplementation at 28 days; low = probability of less than 25%, moderate = probability of 25% to 75%, and high = probability greater than 75%. Although these populations were demographically distinct from the original group, the regression analyses performed well. The regression analysis for 12 hours of age classified 125 neonates at low risk of whom 9% required supplemental oxygen at 28 days, and the regression analysis for 10 days classified 141 neonates at low risk of whom 7% required supplemental oxygen. The 12-hour regression analysis classified 80 neonates at moderate risk of whom 33% required supplemental oxygen at 28 days and the 10-day regression analysis classified 49 neonates at moderate risk of whom 24% required supplemental oxygen.(ABSTRACT TRUNCATED AT 250 WORDS)
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