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Record W2098224575 · doi:10.1542/peds.2013-1857

Use of Antihistamines After Serious Allergic Reaction to Methimazole in Pediatric Graves’ Disease

2014· article· en· W2098224575 on OpenAlexaff
Amy B. Toderian, Margaret L. Lawson

Bibliographic record

VenuePEDIATRICS · 2014
Typearticle
Languageen
FieldMedicine
TopicThyroid Disorders and Treatments
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsMedicineAntihistamineDiscontinuationGraves' diseasePropylthiouracilAntithyroid drugsAllergic reactionThyroidectomyPediatricsDiseaseAllergyThyroidDermatologySurgeryInternal medicineAnesthesiaImmunology

Abstract

fetched live from OpenAlex

Antithyroid drugs are usually considered first-line therapy for management of pediatric Graves' disease because they avoid permanent hypothyroidism, provide a chance for remission, and are less invasive than the alternatives of thyroidectomy or radioactive iodine. Methimazole (MMI) is the only antithyroid drug recommended in pediatrics due to the risk of propylthiouracil-induced liver toxicity. Allergic reactions with MMI occur in up to 10% of patients and, when mild, can be managed with concurrent antihistamine therapy. Guidelines recommend discontinuation of MMI with serious allergic reactions. We present the case of an adolescent girl with Graves' disease and a serious allergic reaction after starting MMI whose family refused radioactive iodine and was reluctant to proceed to surgery. Antihistamine therapy was successfully used to allow continued treatment with MMI. This case demonstrates extension of management guidelines for minor cutaneous allergic reactions to MMI, through the use of antihistamines for a serious allergic reaction, allowing us to continue MMI and provide treatment consistent with the family's preferences and values.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.258
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations10
Published2014
Admission routes1
Has abstractyes

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