Update on Stevens–Johnson Syndrome and Toxic Epidermal Necrolysis: Diagnosis and Management
Bibliographic record
Abstract
Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are the most severe cutaneous adverse reactions that are typically drug-induced in adults. Both SJS and TEN have high morbidity and mortality rates. SJS/TEN imposes clinical challenges for physicians managing patients suffering from this condition, both because it is rare and because it is a rapidly progressing systemic disease with severe cutaneous, mucosal, and systemic manifestations. Although many cases of SJS/TEN have been reported in the literature, there is no consensus regarding diagnostic criteria or treatment. Significant progress has been made in understanding its genetic predisposition and pathogenesis. This review is intended to provide physicians with a comprehensive but practical SJS/TEN roadmap to guide diagnosis and management. We review data on pathogenesis, reported precipitating factors, presentation, diagnosis, and management SJS/TEN focusing on what is new over the last 5 years.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".