Incidence of fatal food anaphylaxis in people with food allergy: a systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Food allergy is a common cause of anaphylaxis, but the incidence of anaphylaxis in food allergic people is unknown. METHODS: We undertook a systematic review and meta-analysis, using the inverse variance method. Two authors selected studies by consensus, independently extracted data and assessed study quality using the Newcastle-Ottawa assessment scale. We searched Medline, Embase, PsychInfo, CINAHL, Web of Science, LILACS and AMED between January 1946 and September 2012 and recent conference abstracts. We included registries, databases or cohort studies which described the number of food anaphylaxis cases in a defined population and time period and applied an assumed population prevalence of food allergy. RESULTS: We included data from 34 studies. There was high heterogeneity between study results, possibly due to variation in study populations, anaphylaxis definition and data collection methods. In food allergic people, medically coded food anaphylaxis had an incidence rate of 0.14 per 100 person-years (95% CI 0.05, 0.35; range 0.01, 1.28). In sensitivity analysis using different estimated food allergy prevalence, the incidence varied from 0.11 to 0.21 per 100 person-years. At age 0-19, the incidence rate for anaphylaxis in food allergic people was 0.20 (95% CI 0.09, 0.43; range 0.01, 2.55; sensitivity analysis 0.08, 0.39). At age 0-4, an incidence rate of up to 7.00 per 100 person-years has been reported. In food allergic people, hospital admission due to food anaphylaxis had an incidence rate of 0.09 (95% CI 0.01, 0.67; range 0.02, 0.81) per 1000 person-years; 0.20 (95% CI 0.10, 0.43; range 0.04, 2.25) at age 0-19 and 0.50 (0.26, 0.93; range 0.08, 2.82) at age 0-4. CONCLUSION: In food allergic people, the incidence of food allergic reactions which are coded as anaphylaxis by healthcare systems is low at all ages, but appears to be highest in young children.
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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 | 0.017 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.047 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".