GRAded oral challenge for Drug allergy Evaluation—Delabelling described through families' voices
Bibliographic record
Abstract
BACKGROUND: Children are often diagnosed with an antibiotic allergy, with little investigation to confirm whether it is a true allergy. Recent studies support the use of oral challenges to confirm antibiotic allergy. Yet, little is known about families' perceptions of these challenges, or experiences of living with a misdiagnosis, often for many years. OBJECTIVE: To describe how families with a child previously labelled as "antibiotic allergic," but who has subsequently been delabelled, perceive the experience of misdiagnosis and subsequent delabelling. METHODS: We performed semi-structured interviews with parents whose children had recently completed a graded oral challenge for antibiotic allergy. Interview transcripts were analysed concurrently, but independently, by two investigators, using content analysis. RESULTS: A total of 15 parents (14 individual interviews; 1 mother-father dyad) participated. Children were, on average, 5.04 ± 4.5 years and were first diagnosed in infancy (mean age: 1.82 ± 1.48 years) subsequent to a rash (14/14; 100%), and commonly at a walk-in clinic (6/14; 42.9%). We identified four themes: (1) A red, raised rash results in a quick diagnosis despite a lack of testing, (2) sensitive care allays concerns, (3) delabelling brings relief, but also mystery and calls for proper diagnoses, and (4) quick diagnoses are reckless, but manageable through downward comparisons. CONCLUSION AND CLINICAL RELEVANCE: These findings underscore the importance of a careful physical examination and clinical history of the patient, but also an ongoing dialogue to support families, both of which would ideally begin at the time of initial investigation.
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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".