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Record W4295037733 · doi:10.1111/cea.14225

Information needs of patients considering oral immunotherapy for food allergy

2022· review· en· W4295037733 on OpenAlexaff
Douglas P. Mack, Matthew Greenhawt, Paul Turner, Richard L. Wasserman, Mariam Hanna, Marcus Shaker, Sarah W. Hughes, Pablo Rodríguez del Río

Bibliographic record

VenueClinical & Experimental Allergy · 2022
Typereview
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsMcMaster University
FundersMedical Research Council
KeywordsMedicineFood allergyOral immunotherapyHealth careAllergyFamily medicineNursing

Abstract

fetched live from OpenAlex

While the historic management of food allergy includes avoidance strategies and allergic reaction treatment, oral immunotherapy (OIT) approaches have become more commonly integrated into therapeutic approaches. International guidelines, phase 3 trials and real-world experience have supported the implementation of this procedure. However, OIT is an elective, rarely curative procedure with inherent risks that necessitates an increased degree of health literacy for the patients and families. Families assume the responsibility of amateur healthcare providers to ensure the daily safe administration of the allergenic food. As such, it is incumbent upon physicians to ensure that families are prepared for this role. A thorough educational and shared decision-making approach is necessary during the counselling and consent process to adequately inform the families. Educated discussion about the efficacy and patient-centred effectiveness, therapeutic alternatives and family goals is required to align physician and patient expectations. A frank discussion about the struggles, practical challenges, risks and contraindications can help to develop an understanding of the risk mitigation strategies employed to maintain safety. Physicians should develop a proactive approach to educate families about this, at times, burdensome procedure. This educational approach should encourage ongoing support starting prior to consent through the maintenance visits. By preparing families for their unique management role, physicians can help ensure the safe and successful integration of OIT into the therapeutic offering for the management of food allergies.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
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)0.0020.000

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 head0.146
GPT teacher head0.442
Teacher spread0.295 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations35
Published2022
Admission routes1
Has abstractyes

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