Oropharyngeal swelling following a ragweed sublingual immunotherapy
Bibliographic record
Abstract
Abstract Background: Sublingual immunotherapy (SLIT) is widely accepted as a safe and effective treatment for allergic rhinitis. Despite severe local and systemic reactions following SLIT are reported to be rare, it is important for patients to be educated and monitored for potential risks throughout treatment. This report presents the first documented case of severe oropharyngeal swelling following SLIT, which necessitated epinephrine treatment and termination of therapy, representing a previously unreported severe local reaction. Case Presentation: A 30-year-old man with a history of severe seasonal allergic rhinoconjunctivitis and shellfish allergy presented with severe allergic reaction to ragweed SLIT (Ragwitek). The patient had previously received grass subcutaneous immunotherapy and birch SLIT, both of which were well tolerated. On day 9 of Ragwitek SLIT, the patient experienced oropharyngeal swelling, dyspnea, and dysphagia within minutes following administration of therapy, which required epinephrine treatment to alleviate symptoms. The patient had also experienced upper respiratory tract infection symptoms a few days prior which may have exacerbated the severity of the reaction. Conclusions: This case highlights an occurrence of a rare severe local reaction following SLIT and emphasizes the importance of patient education and close monitoring, especially in those presenting with recurrent local swelling following SLIT. In addition, counselling these patients about the potential risk of oropharyngeal swelling and consideration for prescribing an epinephrine autoinjector is recommended.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".