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Objective To assess the utility of clinical predictors of persistent respiratory morbidity in extremely low gestational age newborns (ELGAN). Study Design We enrolled ELGAN (<29 weeks’ gestation) at ≤7 postnatal days and collected antenatal and neonatal clinical data through 36 weeks’ post-menstrual age. We surveyed caregivers at 3, 6, 9 and 12 months corrected age to identify post-discharge respiratory morbidity, defined as hospitalization, home support (oxygen, tracheotomy, ventilation), medications, or symptoms (cough/wheeze). Infants were classified as post-prematurity respiratory disease (PRD, the primary study outcome), if respiratory morbidity persisted over ≥2 questionnaires. Infants were classified with severe respiratory morbidity if there were multiple hospitalizations, exposure to systemic steroids or pulmonary vasodilators, home oxygen after 3 months or mechanical ventilation, or symptoms despite inhaled corticosteroids. Mixed effects models generated with data available at one day (perinatal) and 36 weeks’ postmenstrual age were assessed for predictive accuracy. Results Of 724 infants (918±234g, 26.7±1.4 weeks’ gestational age) classified for the primary outcome, 68.6% had PRD; 245/704 (34.8%) were classified as severe. Male sex, intrauterine growth restriction, maternal smoking, race/ethnicity, intubation at birth, and public insurance were retained in perinatal and 36-week models for both PRD and respiratory morbidity severity. The perinatal model accurately predicted PRD (c-statistic 0.858). Neither the 36-week model nor the addition of bronchopulmonary dysplasia (BPD) to the perinatal model improved accuracy (0.856, 0.860); c-statistic for BPD-alone was 0.907. Conclusion Both BPD and perinatal clinical data accurately identify ELGAN at risk for persistent and severe respiratory morbidity at one year. Trial registration ClinicalTrials.gov: NCT01435187

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Purpose: Conduct an individual-level analysis of hospital utilization during the first year of life to test the hypothesis that community material deprivation increases healthcare utilization. Methods: We used a population-based perinatal data repository based on linkage of electronic health records (EHR) from regional delivery hospitals to subsequent hospital utilizations at the region's only dedicated children's hospital. Zero-inflated Poisson and Cox proportional hazards regression models were used to quantify the causal role of a census tract based deprivation index on the total number, length, and time until hospital utilizations during the first year of life. Results: After adjusting for any neonatal intensive care unit (NICU) admission, chronic complex conditions, race and ethnicity, insurance status, birth season, and very low birth weight we found that a 10% increase in the deprivation index caused a 1.032 fold increase (95% CI: [1.025, 1.040]) in post initial hospitalization length of stay, a 1.011 fold increase (95% CI: [1.002, 1.021]) in number of post initial hospital encounters, and 1.022 fold increase (95% CI: [1.009, 1.035]) in hazard for hospitalization utilization during the first year of life. Conclusions: Interventions designed to reduce material deprivation and income inequalities could significantly reduce infant hospital utilization.