Enteral supplementation with high-dose docosahexaenoic acid on the risk of bronchopulmonary dysplasia in very preterm infants: a collaborative study protocol for an individual participant data meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Severe bronchopulmonary dysplasia (BPD) is a well-known factor consistently associated with impaired cognitive outcomes. Regarding reported benefits on long-term neurodevelopmental outcomes, the potential adverse effects of high-dose docosahexaenoic acid (DHA) supplementation on this short-term neonatal morbidity need further investigations in infants born very preterm. This study will determine whether high-dose DHA enteral supplementation during the neonatal period is associated with the risk of severe BPD at 36 weeks' postmenstrual age (PMA) compared with control, in contemporary cohorts of preterm infants born at less than 29 weeks of gestation. METHODS AND ANALYSIS: As part of an Australian-Canadian collaboration, we will conduct an individual participant data (IPD) meta-analysis of randomised controlled trials targeting infants born at less than 29 weeks of gestation and evaluating the effect of high-dose DHA enteral supplementation in the neonatal period compared with a control. Primary outcome will be severe grades of BPD (yes/no) at 36 weeks' PMA harmonised according to a recent definition that predicts early childhood morbidities. Other outcomes will be survival without severe BPD, death, BPD severity grades, serious brain injury, severe retinopathy of prematurity, patent ductus arteriosus and necrotising enterocolitis requiring surgery, sepsis, combined neonatal morbidities and growth. Severe BPD will be compared between groups using a multivariate generalised estimating equations log-binomial regression model. Subgroup analyses are planned for gestational age, sex, small-for-gestational age, presence of maternal chorioamnionitis and mode of delivery. ETHICS AND DISSEMINATION: The conduct of each trial was approved by institutional research ethics boards and written informed consent was obtained from participating parents. A collaboration and data sharing agreement will be signed between participating authors and institutions. This IPD meta-analysis will document the role of DHA in nutritional management of BPD. Findings will be disseminated through conferences, media interviews and publications to peer-reviewed journals. PROSPERO REGISTRATION NUMBER: CRD42023431063. TRIAL REGISTRATION NUMBER: NCT05915806.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.050 | 0.084 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.019 | 0.038 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".