Prevalence and clinical features of adverse food reactions in Portuguese children
Bibliographic record
Abstract
BACKGROUND: The prevalence of adverse food reactions (AFR) has been increasing in the western world. Clinical manifestations are diversified and it may not be possible to clinically discriminate between IgE and non-IgE mediated AFR. In Portugal, the prevalence of AFR and food allergies in children is not known. Thus, the objectives of this study were to determine the prevalence of AFR in central Portugal. METHODS: Point prevalence study in 3-11 year-old schoolchildren from Central Portugal. Food-related questionnaires, skin prick tests (SPT) with foods and determination of food-specific IgE levels were performed. RESULTS: Of 4045 schoolchildren, 2474 (61.2%) accepted to be included in the study. Global prevalence of AFR was 7.1% (95% CI 6.2-8.1), based upon the initial questionnaire, 4.6% (95% CI 3.9-5.5), based upon a confirmatory questionnaire and the prevalence of probable food allergy (IgE-associated AFR: positive history + positive SPT and/or positive specific IgE) was 1.4% (95% CI 0.9-1.9). Most frequently implicated foods were fresh fruits, fish and egg. A first episode at an earlier age, mucocutaneous and anaphylactic reactions were more frequent in IgE-associated AFR. CONCLUSIONS: The prevalence of probable food allergy in 3-11 year old Portuguese children from central Portugal is low and parents over-report its frequency. Most frequently implicated foods were fresh fruit and fish. Immediate type, polysymptomatic, and more severe reactions may commence at an earlier age and be more frequent in IgE-associated than in non-IgE associated reactions.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".