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Record W4220716815 · doi:10.18773/austprescr.2022.010

The assessment of severe cutaneous adverse drug reactions

2022· review· en· W4220716815 on OpenAlex
Ana Maria Copaescu, Jason A Trublano

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAustralian Prescriber · 2022
Typereview
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsAcute generalized exanthematous pustulosisToxic epidermal necrolysisMedicineCulpritDrugDermatologyDrug allergyAdverse drug reactionDrug eruptionAllopurinolDrug reactionAdverse effectAntibioticsIntensive care medicineAllergyPharmacologyInternal medicineImmunology

Abstract

fetched live from OpenAlex

Severe cutaneous adverse drug reactions include Stevens-Johnson syndrome, toxic epidermal necrolysis and acute generalised exanthematous pustulosis. These eruptions are a type of delayed hypersensitivity reaction and can be life-threatening. The assessment of a severe cutaneous drug reaction requires a detailed clinical history and examination to identify the culprit drug and evaluate the allergy. Allopurinol, antibiotics and anticonvulsants are often implicated. Patch testing and delayed intradermal testing can assist in determining if the reaction was allergic, however there is limited evidence about the sensitivity and specificity of skin testing in severe cutaneous adverse drug reactions. If the testing is non-conclusive or negative, it is recommended to avoid the suspected culprit drug and any structurally similar drug in future. Any decision to reintroduce a drug should be made after considering the harm-benefit ratio. Caution is also needed if considering a possibly cross-reactive drug in a patient with a history of severe cutaneous adverse drug reactions.

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.

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 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 score0.947
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.084
GPT teacher head0.387
Teacher spread0.303 · 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