Effect of ketotifen premedication on adverse reactions during peanut oral immunotherapy
Bibliographic record
Abstract
BACKGROUND: Oral immunotherapy (OIT) has shown promise in inducing desensitization for food allergy. However, there are safety concerns regarding the frequency and severity of adverse events during food OIT. OBJECTIVE: To evaluate the effect of Ketotifen premedication on adverse reactions during peanut OIT. METHODS: A randomized single blind placebo controlled pilot study was performed. Peanut OIT was performed using a previously published protocol. Ketotifen was up-titrated to 2 mg twice daily over two weeks (week -2 to 0), followed by a peanut OIT initial escalation day (day 1). Ketotifen was administered from week 0-4 of peanut OIT; reactions to peanut OIT doses were recorded by clinic staff and subject diary. RESULTS: Six subjects (median age 10 years, peanut IgE >100kUA/L) were enrolled, 4 randomized to Ketotifen, 2 to placebo. The most common side effect of Ketotifen was fatigue (9% during up-titration). The rate of reaction per peanut OIT dose was lower for subjects on ketotifen (K) compared to placebo (P) during initial escalation on day 1 (K: 22% (8/36) vs. P: 67% (12/18)); week 0-4 build-up doses (K: 75% (3/4) vs. P: 100% (2/2)); and week 0-4 home doses (K: 50% (54/108) vs. P: 82% (27/33)). The rate of gastrointestinal symptoms per peanut OIT dose was also lower for subjects on ketotifen during initial escalation on day 1 (K: 17% (6/36) vs. P: 61% (11/18)); week 0-4 build-up doses (K: 75% (3/4) vs P: 100% (2/2)); and week 0-4 home doses (K: 46% (50/108) vs. P: 82% (27/33)). CONCLUSIONS: Ketotifen premedication is well tolerated and reduces the rate of gastrointestinal symptoms during peanut OIT. These findings require confirmation in a larger study of Ketotifen premedication used throughout peanut OIT. CLINICAL TRIALS NUMBER: NCT0162515.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".