The health and economic outcomes of early egg introduction strategies
Bibliographic record
Abstract
BACKGROUND: Studies suggest early egg introduction (EEI) in the first year of life is associated with reduced risk of developing egg allergy. No US recommendations exist regarding optimally implementing EEI. METHODS: Using simulation and Markov modelling over a 20-year horizon, we explored optimal EEI strategies applied to US, European and Canadian populations, comparing screening of high-risk infants (skin prick testing [SPT] or serum-specific IgE[sIgE]) before introducing cooked egg at 6 months of life vs egg introduction at home, without screening, for all infants. RESULTS: A no-screen approach dominated egg SPT screening of high-risk infants with early-onset eczema. Base model per-patient incremental costs of SPT were $6865 US dollars (USD), 6801 euros and $10 610 Canadian dollars (CAD). For egg sIgE screening in primary care settings, base model incremental costs were $16 722 USD, 18 072 euros and $28 193 CAD. As the simulation concluded 2.5% were egg allergic without screening vs 9.5%, 12% and 21.4% of children undergoing SPT, delayed introduction or sIgE screening. Incremental societal costs from screening reached $2 009 351 175 USD for SPT and $4 894 445 790 USD for sIgE testing. In sensitivity analyses, if the risk of reaction with initial egg ingestion was ≥22.5%, SPT before EEI became a preferred strategy. A no-screen approach dominated both EEI of raw pasteurized egg and delayed cooked egg introduction approaches. CONCLUSIONS: Assuming initial reaction rates < 22.5%, a no-screening EEI cooked egg approach has superior health and economic benefits in terms of number of egg allergy cases prevented and total healthcare costs vs screening testing.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".