Monitoring of peanut-allergic patients with peanut-specific IgE
Bibliographic record
Abstract
Peanut allergy affects approximately 1% of the population. Double-blind placebo-controlled food challenges are gold standard for diagnosis. Serum peanut-specific IgE (PN-IgE) is used in clinical practice as an additional diagnostic and monitoring tool. The purpose of this study was to characterize the clinical features of a peanut-allergic patient's cohort and determine the optimum frequency of measuring PN-IgE to predict the outcome of future peanut challenges. Retrospective chart review was performed of peanut-allergic patients followed up and serially tested for PN-IgE with a qualitative antibody fluorescent-enzyme immunoassay performed at the Immunology Laboratory, London Health Sciences Center, from 1997 to 2004. One hundred eighteen patients (median age at first reaction to peanut, 1.5 years; median baseline PN-IgE, 18.75) were reviewed. Younger age at first reaction and first PN-IgE measurement predicted slower decline of PN-IgE values (p < 0.001 and p = 0.044). At 2 and 5 years post-initial measurement, 12.9 and 66%, respectively, of all patients had a significant decrease of PN-IgE values. Twenty percent of the patients experienced elevation of PN-IgE levels during follow-up. For most patients with significant history of reaction to peanuts and positive skin-prick test, it is probably adequate to measure serum PN-IgE levels every 3-5 years to screen for development of tolerance and predict the outcome of future peanut challenges. More frequent measurements might be considered in older patients with lower initial PN-IgE levels.
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 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) | 0.000 | 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 | 0.000 |
| 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".