Dermoscopy in vitiligo: diagnosis and beyond
Bibliographic record
Abstract
BACKGROUND: Vitiligo is essentially a clinical diagnosis, and dermoscopy may aid in noninvasive confirmation of diagnosis by excluding other clinically simulating hypopigmentary conditions. More importantly, dermoscopy is rapidly gaining ground as an important adjunct tool to evaluate disease activity. AIM: To study the dermoscopic features of vitiligo and ascertain their correlation with disease activity. METHODS: Retrospective analysis of dermoscopy of 60 cases suffering from vitiligo was undertaken. Dermoscopy was performed using Dermlite II hybrid m dermatoscope at 10× magnification in polarized mode, and photographs were captured by Apple iphone 6. Variables assessed in the dermoscopic evaluation included perifollicular changes, perilesional changes, altered pigmentary network, and presence of specific features such as the starburst appearance, comet tail appearance, leukotrichia, telangiectasia, and any new findings. RESULTS: Sixty patients with stable, progressive, or repigmenting vitiligo were retrospectively studied. While perifollicular depigmentation (PFD) was predictive of stable vitiligo, perifollicular pigmentation (PFP) was characteristic of active disease. Starburst appearance, altered pigment network, and comet tail appearance, were also noted, and these were typical of progressive vitiligo. A new dermoscopic feature, the 'tapioca sago' appearance (sabudana), was observed in the skin adjacent to the vitiligo lesion only in patients with progressive vitiligo. CONCLUSION: Dermoscopy is useful in assessing the stage of evolution and the status of disease activity in vitiligo. The most useful dermoscopic clues are observed in the perifollicular region, since progressive lesions display perifollicular pigmentation and stable/remitting lesions display perifolliclar depigmentation.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".