Effect of extensively hydrolyzed casein vs. conventional formula on the risk of asthma and allergies: The TRIGR randomized clinical trial
Bibliographic record
Abstract
BACKGROUND: The role of hydrolyzed infant formulas in the prevention of asthma and allergies remains inconsistent. We tested whether extensively hydrolyzed casein formula compared to conventional cow's milk-based formula prevented asthma, allergic rhinitis, or atopic eczema. METHODS: In the randomized double-blind Trial to Reduce IDDM in Genetically at Risk (TRIGR), comparing extensively hydrolyzed to standard cow's milk-based infant formula during the first 6-8 months of life, we assessed the effect of the intervention on the incidence of asthma, allergic rhinitis, and eczema when the children were 9- to 11-years old. The asthma, allergic rhinitis, and eczema occurrence was assessed using online standardized and validated ISAAC questionnaire. Of the 1106 children who participated in this Ancillary study, 560 had been randomized to the experimental (extensively hydrolyzed casein formula) and 546 to the control arm (cow's milk-based formula). RESULTS: The risk of persistent asthma, allergic rhinitis, or atopic eczema did not differ by treatment, the hazard ratios (95% CI) being 1.00 (0.66-1.52), 0.95 (0.66-1.38), and 0.89 (0.70-1.15), respectively, in the intention-to-treat analysis. Neither were there any differences in the per-protocol analysis. CONCLUSIONS: Extensively hydrolyzed casein formula did not protect from asthma, rhinitis, or eczema in this population carrying genetic risk for type 1 diabetes.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".