The histologic spectrum of cutaneous sarcoidosis: a study of twenty‐eight cases
Bibliographic record
Abstract
BACKGROUND: Naked sarcoidal granulomas (NSGs) are the characteristic histologic finding in sarcoidosis. This descriptive study was designed to identify the frequency of other histologic changes in cutaneous sarcoidosis. METHODS: The slides from 28 sequential biopsies previously diagnosed as sarcoidosis in patients with known systemic sarcoidosis were reviewed. RESULTS: Classic NSGs were identified in 25 biopsies (89%). Four biopsies contained tuberculoid granulomas, two with neutrophils suggesting infection (cultures negative). Five biopsies contained interstitial granulomas that resembled granuloma annulare and necrobiosis lipoidica in one case each. Additional histologic findings included birefringent foreign material in 14 biopsies (50%), focal necrosis (43%), elastophagocytosis (39%), linear peri-neural granulomas resembling leprosy (25%), increased dermal mucin (18%) and lichenoid inflammation (14%) [two with plasma cells resembling syphilis (7%)]. In all but three cases, the clinical morphology of the lesions suggested sarcoidosis. Special stains for mycobacteria and fungi were negative. CONCLUSIONS: The histologic changes in cutaneous sarcoidosis are more diverse than previously recognized. In sarcoidosis, foreign material may be a frequent nidus for cutaneous granuloma formation. Histologic examination without the clinical history could lead to a misdiagnosis of leprosy, syphilis, other infectious granulomas, rosacea, granuloma annulare, necrobiosis lipoidica, and foreign body reaction in selected cases from this series.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".