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Record W1943821185 · doi:10.1345/aph.1l354

Probability of Rash Related to Gabapentin Therapy in a Child

2009· article· en· W1943821185 on OpenAlexaff
Violette Gijsen, Saskia N. de Wildt, Shinya Ito

Bibliographic record

VenueAnnals of Pharmacotherapy · 2009
Typearticle
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsGabapentinRashMedicineDiscontinuationAdverse effectPopulationDermatologyAdverse drug reactionAnesthesiaInternal medicinePharmacologyDrug

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe a child who developed a skin reaction during gabapentin therapy and discuss how we evaluated the probability of an adverse drug reaction. CASE SUMMARY: An 8-year-old boy with a neurodegenerative disease of unknown origin and an epilepsy disorder developed an urticarial rash and irritability 10 and 4 days, respectively, after the start of gabapentin 20 mg/kg 3 times a day for epilepsy control. Otherwise, the child was well; no changes in other medication or diet had recently been made. After gabapentin discontinuation and administration of one dose of methylprednisolone 10 mg/kg intravenously and diphenhydramine 1 mg/kg every 4 hours via gastric tube, the rash disappeared over 3 weeks. DISCUSSION: In contrast to other antiepileptic drugs, skin reactions to gabapentin are considered uncommon. In adults, reported prevalence of rash possibly related to gabapentin range from 1% to 10%. A postmarketing surveillance study reported gabapentin treatment failure as a consequence of rash in 0.4% of 3000 patients. The product monograph does not mention rash in children. In our patient, assessment using an objective causality scale revealed that the rash was probably caused by gabapentin. CONCLUSIONS: This case, and limited literature data, suggest that gabapentin may cause rash that is severe enough to necessitate discontinuation in a small percentage of children. Further research is needed to determine the actual incidence and severity of gabapentin-related rash in this population.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.565

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.095
GPT teacher head0.411
Teacher spread0.316 · 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 designBench or experimental
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
Published2009
Admission routes1
Has abstractyes

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