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Record W3202371345 · doi:10.3389/falgy.2021.725165

Home-Based Peanut Oral Immunotherapy for Low-Risk Peanut-Allergic Preschoolers During the COVID-19 Pandemic and Beyond

2021· article· en· W3202371345 on OpenAlexaff
Gilbert T. Chua, Edmond S. Chan, Lianne Soller, Victoria E. Cook, Timothy K. Vander Leek, Raymond Mak

Bibliographic record

VenueFrontiers in Allergy · 2021
Typearticle
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsUniversity of AlbertaBC Children's HospitalUniversity of British Columbia
FundersLi Ka Shing Faculty of Medicine, University of Hong KongUniversity of Hong Kong
KeywordsPeanut allergyOral immunotherapyMedicinePandemicAnaphylaxisPediatricsAllergyOral food challengePeanut butterFood allergyCoronavirus disease 2019 (COVID-19)Emergency medicineDiseaseImmunologyInternal medicineInfectious disease (medical specialty)Food science

Abstract

fetched live from OpenAlex

The coronavirus disease 2019 (COVID-19) pandemic has led to the deprioritization of non-emergency services, such as oral food challenges and the initiation of oral immunotherapy (OIT) for food-allergic children. Recent studies have suggested that home-based peanut OIT could be a safe and effective option for low-risk peanut-allergic children. In the period between September 1, 2020, and January 31, 2021, nine preschoolers with a history of mild allergic reactions to peanut underwent home-based peanut OIT. Eight of them (88.9%) completed the build-up phase at home in 11-28 weeks, tolerating a daily maintenance dose of 320 mg peanut protein. During the build-up, six patients (75.0%) reported urticaria, three (33.3%) reported gastrointestinal tract symptoms, and one (14.3%) reported oral pruritis. None of the patients developed anaphylaxis, required epinephrine, or attended emergency services related to OIT. One or two virtual follow-up visits were completed per patient during the build-up phase. Our case series shows that home-based OIT could be offered to the low-risk preschoolers during the COVID-19 pandemic when non-emergency services are limited and could be considered beyond the pandemic, especially for the families living in the rural or remote areas that may otherwise be unable to access OIT.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.602
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.285
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations23
Published2021
Admission routes1
Has abstractyes

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