Bibliographic record
Abstract
Fixed food eruption (FFE) is a rare cutaneous reaction characterized by the recurrence of skin lesions at the same sites following ingestion of specific food triggers. This review aims to address gaps in the literature by synthesizing findings from published cases and studies on FFE. A systematic search of the databases MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Web of Science was conducted on April 11, 2025. After screening for duplicates and excluding irrelevant studies, 32 studies were included in the review. Results showed that there was a greater prevalence of FFE documented in women (63.9%, n = 39) and patients over 18 years old (73.7%, n = 45). The most frequent offending agent identified was tonic water in 24.1% of cases (n = 15). The next most common triggers were cashew nuts and peanuts in 8.1% of cases each (n = 5). The onset of FFE was noted to be less than 4 hours after exposure in 67.2% of cases (n = 41). To diagnose FFE, the majority of studies, 78.6% (n = 48), utilized an oral challenge with the suspected agent to confirm association with the fixed eruption. Patch tests, 49.1% (n = 30), and biopsies, 21.3% (n = 13), were also frequently utilized. Negative patch tests on either previously affected or unaffected skin were also noted in 49.1% of cases (n = 30). Of note, only 29.5% (n = 18) of cases reported any form of treatment, and 72.2% (n = 13) of these reported trigger avoidance as the only form of management. To our knowledge, this is the first comprehensive review of FFE, synthesizing data on demographics, triggers, and diagnostic techniques.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".