Predicting pulmonary hypertension in infants with bronchopulmonary dysplasia.

OBJECTIVE

Develop and validate predictive models for pulmonary hypertension (PH) in high-risk infants.

STUDY

DESIGN

We trained logistic regression (LR) and long short-term memory (LSTM) models using a multicenter cohort study of infants 22-28 weeks gestational age discharged from neonatal intensive care units from 2008 to 2020, at two timepoints: 33 weeks post-menstrual age (PMA) for infants receiving mechanical ventilation at that time, and 36 weeks PMA for infants receiving any respiratory support at that time.

RESULTS

At 33 weeks PMA (N = 2849), top LR model predictors were current fraction of inspired oxygen and birth weight. At 36 weeks (N = 20,173), top LR model predictors were current respiratory support and birth weight. Both LR and LSTM models had strong performance in the temporal validation cohort (infants discharged 2021-2022) for both timepoints.

CONCLUSION

Using available clinical variables, we developed and validated predictive models that may identify infants most at risk for PH at two timepoints.