Erythema multiforme, Stevens–Johnson syndrome and toxic epidermal necrolysis: a comparative review
Bibliographic record
Abstract
BACKGROUND: Human erythema multiforme (EM) and Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS/TEN) are separate conditions. There is no consensus on classification criteria for the eponymous diseases in animals. RESULTS: Animal EM is very different from 90% of human EM, which is herpes virus associated (HAEM). Animals lack acrally distributed, typical raised targets. Unlike canine parvovirus 'EM', HAEM is not an active infection. Animal EM is often attributed to drugs, but this is rarely proved. Conversely, human and animal SJS/TEN are almost identical, life-threatening disorders of epidermal necrosis and detachment, typically triggered by drugs (occasionally by infectious agents). Both EM and SJS/TEN are mediated by cytotoxic lymphocyte responses against altered keratinocytes (infectious agents or drugs). Apoptosis results from direct cytotoxicity or through soluble mediators, namely Fas ligand, granzymes, perforin and granulysin. Diagnosis in humans is clinicopathological, with emphasis on clinical lesions; histopathology confirms the pathological process as interface (cytotoxic) dermatitis. Human EM is self-limiting; only recurrent and rare persistent cases require antiviral/immunosuppressive therapies. Drug-induced EM responds to drug withdrawal. Idiopathic canine EM (>40%) is usually chronic, refractory to treatment and may represent heterogeneous conditions. Early identification and removal of the causative drug and high-quality supportive care are critical in SJS/TEN. Mortality rate is nevertheless high. CONCLUSIONS AND CLINICAL IMPORTANCE: (1) Histopathological lesions do not reliably differentiate EM, SJS and TEN. (2) A multicentre study to develop a consensus set of clinical criteria for EM and SJS/TEN in animals is overdue. (3) No adjunctive therapies, including intravenous immunoglobulin and ciclosporin, have met evidence-based standards.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".