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Exhaled Volatile Organic Compounds for Early Prediction of Bronchopulmonary Dysplasia in Infants Born Preterm

  • University of Amsterdam
  • Amsterdam Reproduction and Development
  • Vrije Universiteit Amsterdam
  • “Villa dei Fiori” Hospital
  • Amsterdam UMC location University of Amsterdam
  • Division of Neonatolgy "Villa dei Fiori" Hospital

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Objective(s): To investigate the predictive performances of exhaled breath volatile organic compounds (VOCs) for development of bronchopulmonary dysplasia (BPD) in infants born preterm. Methods: Exhaled breath was collected from infants born <30 weeks’ gestation at days 3 and 7 of life. Ion fragments detected by gas chromatography–mass spectrometry analysis were used to derive and internally validate a VOC prediction model for moderate or severe BPD at 36 weeks of postmenstrual age. We tested the predictive performance of the National Institute of Child Health and Human Development (NICHD) clinical BPD prediction model with and without VOCs. Results: Breath samples were collected from 117 infants (mean gestation 26.8 ± 1.5 weeks). Thirty-three percent of the infants developed moderate or severe BPD. The VOC model showed a c-statistic of 0.89 (95% CI 0.80-0.97) and 0.92 (95% CI 0.84-0.99) for the prediction of BPD at days 3 and 7, respectively. Adding the VOCs to the clinical prediction model in noninvasively supported infants resulted in significant improvement in discriminative power on both days (day 3: c-statistic 0.83 vs 0.92, P value .04; day 7: c-statistic 0.82 vs 0.94, P value .03). Conclusions: This study showed that VOC profiles in exhaled breath of preterm infants on noninvasive support in the first week of life differ between those developing and not developing BPD. Adding VOCs to a clinical prediction model significantly improved its discriminative performance.

Original languageEnglish
Article number113368
Pages (from-to)113368
JournalJournal of pediatrics
Volume257
Early online date1 Mar 2023
DOIs
Publication statusPublished - Jun 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • chronic lung disease
  • exhaled breath
  • prediction model
  • preterm infant

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