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Record W4312911634 · doi:10.33590/emjdermatol/10314211

Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis in Children: A Literature Review of Current Treatments

2016· review· en· W4312911634 on OpenAlexaff
Blanca R. Del Pozzo‐Magaña, Alejandro Lazo‐Langner

Bibliographic record

VenueEMJ Dermatology · 2016
Typereview
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsWestern University
Fundersnot available
KeywordsToxic epidermal necrolysisPlasmapheresisMedicineIntensive care medicineIntensive care unitDrugErythrodermaMortality rateDermatologyPediatricsSurgeryImmunologyPharmacologyAntibody

Abstract

fetched live from OpenAlex

Stevens-Johnson syndrome and toxic epidermal necrolysis are among the most concerning drug reactions affecting adults and children. Although the overall mortality has reduced substantially after the introduction of several strategies, such as prompt withdrawal of the causal drug and management of the patients in an intensive care or burn unit, these conditions continue to be associated with severe complications and a mortality rate of 1–4%. Currently, several treatment options including systemic corticosteroids, intravenous immunoglobulins, cyclosporine, tumour necrosis factor-α inhibitors, and plasmapheresis among others, have shown inconclusive benefits regarding their efficacy and safety in patients with these conditions. This review analyses the most recent literature regarding treatment options for paediatric patients with Stevens-Johnson syndrome and toxic epidermal necrolysis.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.887
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.027
GPT teacher head0.354
Teacher spread0.327 · 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 designOther design
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

Citations5
Published2016
Admission routes1
Has abstractyes

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