Efficacy, effectiveness and other patient-centered outcomes of oral immunotherapy
Bibliographic record
Abstract
Oral immunotherapy (OIT) is the medically supervised ingestion of a food allergen. Understanding of the expected outcomes of OIT allow for risk-benefit assessments for patient-centered decisions. The efficacy of OIT to achieve desensitization in children has been confirmed in multiple meta-analyses, even with vastly disparate study populations and methodologies. Most children initiated on OIT will achieve the ability to eat more allergen before experiencing an allergic reaction than if they continue to avoid their allergen. This effect is diminished without regular ingestion. Previous meta-analyses showed increased allergic reactions on OIT versus avoidance or placebo due to the dosing itself; however, a recent meta-analysis showed that peanut OIT in children did not lead to an increase in allergic reactions. Analysis of emerging data suggests that OIT may reduce reactions to accidental exposures over time. Important patient-centered outcomes, including reaction avoidance or amelioration, and psychosocial impacts and/or quality of life, and studies of more demographically representative populations are also necessary.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.012 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".