Risk factors for severe reactions in food allergy: Rapid evidence review with meta‐analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This rapid review summarizes the most up to date evidence about the risk factors for severe food-induced allergic reactions. We searched three bibliographic databases for studies published between January 2010 and August 2021. We included 88 studies and synthesized the evidence narratively, undertaking meta-analysis where appropriate. Significant uncertainties remain with respect to the prediction of severe reactions, both anaphylaxis and/or severe anaphylaxis refractory to treatment. Prior anaphylaxis, an asthma diagnosis, IgE sensitization or basophil activation tests are not good predictors. Some molecular allergology markers may be helpful. Hospital presentations for anaphylaxis are highest in young children, yet this age group appears at lower risk of severe outcomes. Risk of severe outcomes is greatest in adolescence and young adulthood, but the contribution of risk taking behaviour in contributing to severe outcomes is unclear. Evidence for an impact of cofactors on severity is lacking, although food-dependent exercise-induced anaphylaxis may be an exception. Some medications such as beta-blockers or ACE inhibitors may increase severity, but appear less important than age as a factor in life-threatening reactions. The relationship between dose of exposure and severity is unclear. Delays in symptom recognition and anaphylaxis treatment have been associated with more severe outcomes. An absence of prior anaphylaxis does not exclude its future risk.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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 it