A case-control study of food hyper-sensitivity, timing of weaning and family history of allergies in young children with atopic dermatitis
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to investigate the relationship between food hypersensitivity and atopic dermatitis (AD) in young children. MATERIAL AND METHODS: In a case-control design, 28 patients < 3 years old, with AD and 28 age-matched healthy children were included in the study. A detailed medical history of allergies and timing of weaning was obtained. Children underwent skin tests (prick and patch) to evaluate food hypersensitivity. The status of DA and food allergies in the study participants was investigated 4 years later. RESULTS: There were more children with positive skin tests for food hypersensitivity among cases than controls, OR 4.2 (95%CI 1.3 to 13.4). In contrast, there were no differences in the number of children with positive family history of allergic diseases or weaned at < or = 6 months of age between groups. Four years later, out of the 28 original cases, the state of AD was investigated in 13 (46.4%) infants. Of them, 11 followed an exclusion diet; 6 (46.1%) remained with AD. Of 28 original controls, 15 (51.7%) infants were investigated 4 years later; only one case developed AD. CONCLUSIONS: Young children who had hypersensitivity to cow's milk, hen egg, wheat, fish, soy, or legumes were found to have a higher risk of AD. Positive family history of allergies and early weaning were not found to be relevant risk factors.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".