Identifying effect modifiers of systemic hydrocortisone treatment initiated 7-14 days after birth in ventilated very preterm infants on long-term outcome:Secondary analysis of a randomised controlled trial
Bibliographic record
Abstract
Objective To explore clinical effect modifiers of systemic hydrocortisone in ventilated very preterm infants for survival and neurodevelopmental outcome at 2 years’ corrected age (CA). Design Secondary analysis of a randomised placebo-controlled trial. Setting Dutch and Belgian neonatal intensive care units. Patients Infants born <30 weeks’ gestational age (GA), ventilator-dependent in the second week of postnatal life. Intervention Infants were randomly assigned to systemic hydrocortisone (cumulative dose 72.5 mg/kg; n=182) or placebo (n=190). Main outcome measures The composite of death or neurodevelopmental impairment (NDI) at 2 years’ CA and its components. Candidate effect modifiers (GA, small for GA, respiratory index, sex, multiple births, risk of moderate/severe bronchopulmonary dysplasia or death) were analysed using regression models with interaction terms and subpopulation treatment effect pattern plots. Results The composite outcome was available in 356 (96.0%) of 371 patients (one consent withdrawn). For this outcome, treatment effect heterogeneity was seen across GA subgroups (<27 weeks: hydrocortisone (n=141) vs placebo (n=156), 54.6% vs 66.2%; OR 0.61 (95% CI 0.38 to 0.98); ≥27 weeks: hydrocortisone (n=30) vs placebo (n=31), 66.7% vs 45.2%; OR 2.43 (95% CI 0.86 to 6.85); p=0.02 for interaction). This effect was also found for the component death (<27 weeks: 20.1% vs 32.1%; OR 0.53 (95% CI 0.32 to 0.90); ≥27 weeks: 28.1% vs 16.1%; OR 2.04 (95% CI 0.60 to 6.95); p=0.049 for interaction) but not for the component NDI. No differential treatment effects were observed across other subgroups. Conclusion This secondary analysis suggests that in infants <27 weeks’ GA, systemic hydrocortisone may improve the outcome death or NDI, mainly driven by its component death. There was insufficient evidence for other selected candidate effect modifiers.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".