Acute Generalized Exanthematous Pustulosis Simulating Toxic Epidermal Necrolysis
Bibliographic record
Abstract
BACKGROUND: Both acute generalized exanthematous pustulosis (AGEP) and toxic epidermal necrolysis (TEN) are adverse cutaneous reactions. Despite the fact that these 2 cutaneous reactions differ in presentation, prognosis, pathologic features, and treatment, overlap can exist between them, creating a diagnostic challenge. OBSERVATIONS: We describe a patient who presented with clinical features of both AGEP and TEN, and we summarize overlapping cases of AGEP-TEN that have been reported in the literature. It is essential to be able to differentiate between AGEP and TEN, as these conditions are clinically and morphologically distinct entities. They also differ considerably in their prognosis and treatment. CONCLUSIONS: Because overlap exists, AGEP should be considered in the differential diagnosis of widespread blistering and erosive conditions. A greater understanding of how to differentiate AGEP and TEN can lead to quicker diagnosis as well as more effective case management and treatment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".