Pediatric anaphylaxis: age-related symptom trends and the limited role of allergen molecules: a retrospective analysis
Bibliographic record
Abstract
BACKGROUND: Emerging evidence suggests that specific allergen molecules may influence the clinical phenotype of anaphylaxis in children, but robust data are scarce. This study aimed to rigorously test the molecule-phenotype association in a large pediatric cohort and to determine the relative influence of the sensitizing molecule versus patient age on symptom presentation. METHODS: test. Symptom frequencies across different organ systems were analyzed in relation to allergen molecules and age groups using Cochran's Q and Pearson's χ2 tests. RESULTS: The most frequent molecular triggers were Ara h 2 (18.79%), Gal d 1 (9.09%), and Ana o 3 (9.09%). While significant differences in symptom distribution were observed within individual allergen molecules (p < 0.05), no molecule-specific symptom pattern was identified. In contrast, age significantly influenced respiratory symptom prevalence, with a higher frequency in older children compared to infants (p = 0.003). A similar trend was observed for gastrointestinal symptoms (p = 0.051). CONCLUSIONS: In pediatric anaphylaxis, patient age is a more significant determinant of clinical presentation, particularly for respiratory symptoms, than the specific sensitizing allergen molecule. This suggests that clinical risk stratification and management strategies in children should prioritize age-related factors over specific molecular sensitization profiles.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".