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Record W2772149914 · doi:10.1177/1203475417746148

Toxic Epidermal Necrolysis Spectrum Management at Sunnybrook Health Sciences Centre: Our Multidisciplinary Approach After Review of the Current Evidence

2017· review· en· W2772149914 on OpenAlexaffabout
Alexandra Mereniuk, Alejandra Jaque, Marc G. Jeschke, Neil H. Shear

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2017
Typereview
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsToxic epidermal necrolysisMedicineMultidisciplinary approachGuidelineBroad spectrumMultidisciplinary teamHealth careFamily medicineIntensive care medicineDermatologyNursingPathology

Abstract

fetched live from OpenAlex

Toxic epidermal necrolysis spectrum (TENS) is a rare yet severe adverse drug reaction associated with a high mortality rate. Beyond supportive care, there is still no established therapy for TENS, although recent meta-analyses and UK guideline recommendations have attempted to offer a review of relevant literature on this difficult topic. As most directed treatments lack clear consensual evidence, care centres often resort to establishing their own strategies. As Canada's largest adult burn centre and the provincial reference centre for most burn patients in Ontario, our team at the Ross Tilley Burn Centre, in collaboration with the Department of Dermatology at Sunnybrook Health Sciences Centre, Toronto, Canada, has managed over 60 confirmed cases of TENS over the past 2 decades. We would like to share our management, experience, and present our treatment protocol that we recently established by a collaborative multidisciplinary team approach to help guide treatment of these complex patients not only in Canada but worldwide.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.826
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.001
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 head0.170
GPT teacher head0.422
Teacher spread0.252 · 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

Citations7
Published2017
Admission routes2
Has abstractyes

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