Risk Factors for Severe Respiratory Morbidity at 2 Years of Life in Children Born Extremely Preterm With Bronchopulmonary Dysplasia
Bibliographic record
Abstract
BACKGROUND: Bronchopulmonary dysplasia (BPD), defined as need for oxygen/respiratory support at 36 weeks gestational age (GA) is associated with increased risk of post-prematurity respiratory disease (PRD). We hypothesize that BPD, higher pCO2, and pulmonary hypertension (PH) before NICU discharge will predict PRD. OBJECTIVES: (1) Identify clinical factors before NICU discharge associated with PRD by 2 years of age; (2) Identify clinical factors associated with emergency room (ER) visits by 2 years of age; (3) Compare predictive performance for PRD of individual and multivariable clinical factors. METHODOLOGY: Children born < 29 weeks GA with ≥ 1 echocardiogram before NICU discharge at two tertiary centers were included. Retrospective chart review included clinical factors at NICU discharge, ER visits, and respiratory-related hospitalizations by 2 years. Analysis of predictors included logistic regression and ROC. RESULTS: We included 125 premature infants, of whom 53 (42%) had BPD, and 24 (19%) experienced PRD. All who experienced PRD had BPD. More severe BPD (OR: 96.1, CI: 12.4, 12, 383), but not hypercapnia or PH, were associated with PRD. On ROC analysis, combination of BPD severity, pCO2 and PH demonstrated 70% chance of PRD (AUC: 0.68 (95% CI: 0.55, 0.81). Presence of ≥ 2 factors had sensitivity of 50% and specificity of 97% for prediction of PRD. Children with BPD had 2.6 times as many ER visits as those without. CONCLUSION: Combination of BPD severity, pCO2, and PH best predicted PRD. Identifying extremely preterm infants at high risk of developing PRD can guide counseling of families and early intervention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".