Predictors of Developmental and Respiratory Outcomes Among Preterm Infants With Bronchopulmonary Dysplasia

Abstract

Objectives: To examine the importance of perinatal and postnatal environmental factors on developmental and respiratory outcomes among preterm infants with bronchopulmonary dysplasia (BPD).Methods: Preterm infants (<32 weeks of gestation) born at a single tertiary medical center between 2012 and 2015 were included. Development was assessed at 12 months corrected age. Parents retrospectively completed a health and lifestyle questionnaire reviewing their child's health during the first 2 years of life. A linear regression model was applied to assess the effect of various perinatal and postnatal factors on development. A machine-learning algorithm was trained to assess factors affecting inhaler use.Results: Of 398 infants meeting the inclusion criteria, 208 qualified for the study: 152 (73.1%) with no BPD, 40 (19.2%) with mild BPD, and 16 (7.7%) with moderate-severe BPD. Those in the moderate-severe group were more likely to be male, have mothers who were less educated, and require longer ventilation periods and less time to regain birth weight. They were also more likely to have mothers with asthma/allergies and to have a parent who smoked. Those in the moderate-severe BPD group exhibited significantly lower developmental scores (85.2 ± 16.4) than the no-BPD group (99.3 ± 10.9) and the mild BPD group (97.8 ± 11.7, p < 0.008) as well as more frequent inhaler use (p = 0.0014) than those with no or mild BPD. In addition to perinatal factors, exposure to breast milk, income level and daycare attendance positively affected development. Exposure to cigarette smoke, allergies among family members and daycare attendance proved to be important factors in inhaler use frequency.Conclusions: Postnatal environmental factors are important in predicting and modifying early childhood outcomes among preterm infants.

Bridging the Gap: Exploring Bronchopulmonary Dysplasia through the Lens of Biomedical Informatics

“…These models navigate the intricate landscape of clinical and genetic risk factors to discern infants with BPD within research populations. Notable instances of artificial intelligence in BPD research are eloquently delineated in Table 1 [31][32][33][34][35]. Using machine learning, the authors built predictive models that incorporated clinical and genetic data (from identified risk genes).…”

Breast-feeding as protective factor against bronchopulmonary dysplasia in preterm infants

“…Bronchopulmonary dysplasia (BPD) is a chronic lung disease of the premature newborn. It is characterised by abnormal lung development provoked by factors such as mechanical ventilation, oxygen therapy or poor nutrition (1,2) . Advances in the care of premature infants and the increased survival of the most immature ones have resulted in an increased incidence of BPD, which now affects about 50 % of those born with less than 30 weeks of gestational age, according to the Vermont Oxford Network (3,4) .…”