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Record W4405575227 · doi:10.1177/2050313x241307097

Stevens-Johnson syndrome with overlapping features of DRESS syndrome: A report of two cases

2024· article· en· W4405575227 on OpenAlexaff
Laura D Chin, Michael L. MacGillivary, Kerri Purdy, Carly Kirshen

Bibliographic record

VenueSAGE Open Medical Case Reports · 2024
Typearticle
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsDr. Georges-L.-Dumont University Hospital CentreOttawa HospitalDalhousie UniversityUniversity of Ottawa
Fundersnot available
KeywordsMedicineDermatologyEosinophiliaCarbamazepineEtanerceptDrug reactionToxic epidermal necrolysisAdverse drug reactionDiseaseRashSystemic diseaseLamotrigineDrugPathologyInternal medicineEpilepsyRheumatoid arthritisPsychiatry

Abstract

fetched live from OpenAlex

Stevens-Johnson syndrome and drug reaction with eosinophilia and systemic symptoms are severe cutaneous adverse reactions to drugs that are generally considered distinct entities. In addition to identifying the offending medication, distinguishing between these diagnoses is important, as they have differing treatment regimens and prognoses. Distinction between severe cutaneous adverse reactions, particularly in the early stages of disease, can be difficult, and overlapping conditions have been reported in the literature. We present two cases of severe cutaneous adverse reaction, one following initiation of carbamazepine and the other lamotrigine, with extensive mucosal involvement and epidermal detachment, initially diagnosed as Stevens-Johnson syndrome. Despite the use of cyclosporine and repeated doses of etanercept, both cases evolved to have significant edema of the face and extremities, palmar and plantar involvement, and rapid response to systemic corticosteroids, which is more in-keeping with drug reaction with eosinophilia and systemic symptoms. We aim to help clinicians gain awareness of Stevens-Johnson syndrome/drug reaction with eosinophilia and systemic symptoms overlap which may aid diagnosis and guide treatment.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.027
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.025
GPT teacher head0.344
Teacher spread0.319 · 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 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

Citations3
Published2024
Admission routes1
Has abstractyes

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