Early Predictors of Bronchopulmonary Dysplasia in Extremely Preterm Infants

Bronchopulmonary dysplasia (BPD) remains one of the most common complications in extremely preterm infants despite advances in neonatal intensive care. Early identification of infants at high risk for BPD could facilitate individualized treatment strategies and improve long-term respiratory outcomes. However, current prediction models rely primarily on conventional clinical variables and have limited predictive accuracy. This prospective observational study aims to evaluate the predictive value of novel physiological, imaging, and biomarker-based indicators for the development of BPD in infants born before 26 weeks of gestation. Participants admitted to the neonatal intensive care units of the Medical University of Vienna will undergo non-invasive assessments during routine clinical care. These include respiratory function monitoring during neonatal transition, lung ultrasound, diaphragmatic ultrasound, targeted neonatal echocardiography, forced oscillation technique, neurally adjusted ventilatory assist-derived diaphragmatic electrical activity, electrical impedance tomography, and proteomic analyses of plasma and tracheal aspirate samples. The association between these novel indicators and respiratory disease severity will be assessed using the Respiratory Severity Score (RSS). Their ability to predict BPD will be evaluated using receiver operating characteristic (ROC) analysis and uni- and multivariable logistic regression models. Predictive performance will be assessed using the C-statistics. The primary objectives are to determine the correlation between the novel indicators and the RSS and to evaluate their diagnostic accuracy for predicting BPD. Secondary objectives include identifying the combination of indicators that provides the best prediction of BPD, evaluating longitudinal changes in respiratory and cardiovascular parameters during the neonatal period, assessing the effects of respiratory interventions and treatments on these indicators, and investi