Cocaine‐related retiform purpura: evidence to incriminate the adulterant, levamisole
Bibliographic record
Abstract
The term 'cocaine-induced pseudovasculitis' was coined to encompass a constellation of clinical and laboratory findings which mimics a systemic vasculitis but lacks confirmatory evidence of vasculitis on biopsy. Antineutrophil cytoplasmic antibodies reacting with human neutrophil elastase (HNE) have been reported to distinguish the cocaine-related syndrome from a true autoimmune vasculitis. Published cases of retiform purpura related to cocaine use are rare and an etiologic role for levamisole, a common adulterant of cocaine, has been postulated. We describe two female patients aged 39 and 49 years with cocaine-related retiform purpura, mainly affecting the legs. The initial clinical and serological profile in case 1 led to a suspicion of anti-phospholipid syndrome and in case 2 to Wegener's granulomatosis with an unexplained associated neutropenia. Skin biopsies revealed a mixed pattern of leukocytoclastic vasculitis and microvascular thrombosis in case 1 and pure microvascular thrombosis in case 2. Identification of anti-HNE antibodies in both patients linked their disease to cocaine. The mixed vasculopathic pattern in case 1 and the associated neutropenia in case 2, both known adverse effects of levamisole, point to this as the true etiologic agent. Urine toxicology shortly after a binge of cocaine use in each case was positive for levamisole.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".