4.7 Article

Prediction of Bronchopulmonary Dysplasia by Postnatal Age in Extremely Premature Infants

Journal

Publisher

AMER THORACIC SOC
DOI: 10.1164/rccm.201101-0055OC

Keywords

bronchopulmonary dysplasia; prematurity; low-birth-weight infant

Funding

  1. National Institutes of Health
  2. Eunice Kennedy Shriver National Institute of Child Health and Human Development
  3. Neonatal Research Network's Benchmarking Study
  4. Surfactant Positive Airway Pressure and Pulse Oximetry Trial in Extremely Low Birth Weight Infants (SUPPORT) [NCT233324]
  5. National Institute of Child Health and Human Development [1K23HD060040-01, DHHS-1R18AE000028-01]
  6. National Institute of Child Health and Human Development Neonatal Research Network
  7. Barbara Stoll
  8. Waldemar Carlo
  9. Seetha Shankaran
  10. Michele Walsh
  11. Krisa Van Meurs
  12. Neil Finer
  13. Rosemary Higgins
  14. Abhik Das
  15. Roger Faix
  16. Michael Cotten

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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 sixpostnatal ages usinggestational age, birth weight, race and ethnicity, sex, respiratory support, and FIO 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. AWeb-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.

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