Predicting the likelihood of bronchopulmonary dysplasia in premature neonates

ABSTRACT

Introduction: Bronchopulmonary dysplasia (BPD) is the most common serious pulmonary morbidity in premature infants. Despite ongoing advances in neonatal care, the incidence of BPD has not improved. A potential explanation for this phenomenon is the limited ability for accurate early prediction of the risk of BPD. BPD continues to represent a therapeutic challenge and no single effective therapy exists for this condition.

Areas covered: Here, we review risk factors of BPD derived from clinical data, biological fluid biomarkers, respiratory management data, and scientific advancements using ‘omics’ technologies, and their ability to predict the pathogenesis of BPD in preterm neonates. Risk factors and biomarkers were identified via literature search with a focus on the last 5 years of data.

Expert opinion: The most accurate predictive tools utilize risk factors that encompass a variety of categories. Numerous predictive models have been proposed but suffer from a lack of adequate validation. An ideal model should include multiple, easily measurable variables validated across a heterogeneous population. In addition to evaluating recent BPD prediction models, we suggest approaches to enhance future models.

KEYWORDS:

• Lung
• hyperoxia
• ventilation

Article highlights

• The rates of BPD, the most common chronic lung disease in infants, have largely remained unchanged or even increased slightly.

• One possible explanation for the above is the limited ability to accurately predict the risk of BPD early in life, which could potentially allow for deployment of early targeted therapeutic strategies.

• Risk factors of BPD are derived from clinical data, biological fluid biomarkers, respiratory management data, and ‘omics’ technologies.

• Currently, clinical data/biomarkers and/or respiratory variables probably offer the best predictive models for BPD.

• Predictive models for BPD are limited by lack of adequate validation.

• The advent of ‘omics’ technologies allows data to be gathered from both genetic and environmental factors that influence the pathogenesis of BPD.

• Improvement in predictive modeling of BPD, with the insight gained from data gathered from ‘omics’ technologies, would allow early and accurate identification of infants who could potentially benefit from focused therapy.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This paper was not funded.