Effectiveness and safety of allergen immunotherapy in patients with allergic rhinitis complicated by rheumatic autoimmune diseases: a case series study
Bibliographic record
Abstract
BACKGROUND: Allergen immunotherapy (AIT) is the only treatment that has modified the natural history of allergic diseases. However, since its overall effect on the immune system has not been elucidated, AIT is either absolutely or relatively contraindicated in patients with rheumatic autoimmune diseases (RADs). Therefore, there have been no long-term observations of patients with RADs receiving AIT; thus, the effectiveness and safety of AIT in these patients remain unclear. METHODS: This was a single-center retrospective observational study. RAD patients receiving AIT for allergic rhinitis at our institution were selected. Changes in the activity of RAD patients were investigated for 2 years from baseline, including those who discontinued AIT. The effectiveness of AIT was also investigated using the Japan Allergic Rhinitis Standard Quality of Life Questionnaire. RESULTS: Thirteen patients with RADs were enrolled in the study. All patients received sublingual immunotherapy, of which four discontinued AIT owing to adverse events. Among all patients, the symptoms of RADs in three patients worsened during the observation period; however, none of them were causally related to AIT. Most of the adverse events associated with AIT were mild, in which only one patient required drug intervention due to worsening rhinitis symptoms. In the nine patients who were able to continue AIT, their eye and nasal symptom scores showed a significant improvement from 1.67 (1.5-2.0) at baseline to 0.67 (0-1.17) in the 2nd year of treatment (p = 0.0141). CONCLUSIONS: AIT is a safe and effective treatment modality for patients with allergic rhinitis complicated by RADs.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".