Does more granular data equal better bronchopulmonary dysplasia prediction?

Advances in perinatal and neonatal care have substantially improved survival of infants born extremely preterm. 1 Unfortunately, these gains have not been matched by comparable reductions in the burden of bronchopulmonary dysplasia (BPD), with incidence remaining largely unchanged, reflecting both the increased survival of infants at highest risk, and the paucity of effective preventive strategies. 2 Systemic corticosteroids reduce the risk of BPD in those with a higher risk profile, 3 but clinicians remain cautious in their use due to potential long-term harm and difficulty in accurately assigning risk. While early treatment (<7 days of age) carries an increased risk of adverse neurodevelopmental outcomes and gastrointestinal perforation, 4 the evidence suggests a more favorable risk-benefit balance when treatment is reserved for infants beyond 7 days who are at high risk of BPD. 5 , 6 This presents a challenge: how do clinicians prospectively identify infants at high risk of BPD with appropriate precision at an early stage to guide timely and appropriate treatment?