Cannabis-fruit/vegetable syndrome: an unusual case without pollen co-sensitization
Bibliographic record
Abstract
Abstract Background: Cannabis use has become increasingly popular since its legalization. In 2022, 19% of Canadians over 16 years of age report using cannabis within the past 30 days1. Cannabis is associated with an extensive spectrum of cross-reactivity with fruits and vegetables through a phenomenon known as cannabis-fruit/vegetable syndrome2. While most patients are co-sensitized with cross-reactive pollen, we present a unique case of cannabis-fruit/vegetable syndrome without birch pollen co-sensitization. Case Presentation: Since 2021, a 26-year-old female with intermittent cannabis smoking began noticing IgE mediated symptoms when eating previously tolerated fruits within the birch pollen family. Her first instance was with fresh cherries where she instantly experienced ocular/throat pruritus and generalized urticaria. In 2022, she had similar reactions to fresh peaches and raspberries. Concurrently, she began experiencing immediate ocular/throat pruritus with Cannabis sativa but not with Cannabis indica. Her fresh fruit skin test was positive to nectarine (10mm), plum (6mm), raspberry (12mm), blackberry (6mm), and both Cannabis sativa (7mm) and indica (11mm). Her environmental panel was negative to common grass, tree and weed pollens. She was prescribed an epinephrine autoinjector given her systemic symptoms. Conclusion: Multiple potential allergens including non-specific lipid transfer proteins (nsLTP), thaumatin-like protein, ribulose-1,5-bisphosphate carboxylase oxygenase, and oxygen evolving enhancer protein are thought to be contributors to cannabis allergies3. Of these, nsLTP is a pan-allergen found ubiquitously throughout the plant kingdom, potentially explaining cross activities between cannabis, fruits, and vegetables. Our case of cannabis-fruit/vegetable syndrome in an otherwise non-atopic individual is interesting as her skin testing showed no reaction against common pollens, specifically birch, a well-known aeroallergen to cross-react with cherries, peaches, and plums. These findings suggest the patient became sensitized to fruits through cannabis use. With increasing cannabis accessibility, more awareness in the medical community is necessary on allergic implications of cannabis use.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".