<scp>PROspective</scp> Meta‐analysis Of Trials of Initial Oxygen in preterm Newborns (<scp>PROMOTION</scp>): Protocol for a systematic review and prospective meta‐analysis with individual participant data on initial oxygen concentration for resuscitation of preterm infants
Bibliographic record
Abstract
BACKGROUND: Clinicians favour low oxygen concentrations when resuscitating preterm infants immediately after birth despite inconclusive evidence to support this practice. Prospective meta-analysis (PMA) is a novel approach where studies are identified as eligible for inclusion in the meta-analysis before their results are known. AIMS: To explore whether high (60%) or low (30%) oxygen is associated with greater efficacy and safety for the initial resuscitation (immediately after birth) of preterm infants born at <29 weeks' gestation. METHODS: We will conduct a prospective meta-analysis (PMA) with individual participant data (IPD). We will perform a systematic search to identify ongoing RCTs including infants <29 weeks' gestation randomised to high (60%) or low (30%) oxygen for initial resuscitation after birth. IPD will be sought for all infants randomised for the purpose of meta-analysis. We will employ a one-stage random-effects approach to IPD meta-analysis. Potential heterogeneity and the differential effect of high or low oxygen will be explored through subgroup and interaction analyses. The primary outcome of this study is all-cause mortality prior to hospital discharge. There will be a follow-up analysis of neurodevelopmental outcomes once available. RESULTS/CONCLUSION: The results of neonatal outcomes at hospital discharge are expected by 2025, and neurodevelopmental outcomes by 2027.
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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 | 0.018 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.004 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".