Update on trichoscopy: Integration of the terminology by systematic approach and a proposal of a diagnostic flowchart
Bibliographic record
Abstract
Trichoscopy represents a non-invasive diagnostic modality widely used in daily practice. Despite the common perception that this technique has been fairly established, some key issues remain to be addressed. Complexity and inconsistency in terminology in past literature are likely to confuse investigators when they are recording, reporting, and retrieving the findings. In addition, a diagnostic algorithm adopting sufficiently integrated and updated findings is not readily available. By adopting a systematic review approach, this review attempted to redefine major trichoscopic findings and integrate their synonyms individually into the most frequently used terms besides identifying and discussing terms which potentially cause confusion. The findings are categorized into five subgroups: hair shaft, follicular, perifollicular, scalp findings, and hair distribution pattern abnormalities. The calculation of sensitivities and positive predictive values of such redefined findings was conducted by reviewing the descriptions in the past literature on major hair diseases, including alopecia areata, androgenetic alopecia/female pattern hair loss, telogen effluvium, trichotillomania, lichen planopilaris, frontal fibrosing alopecia, central centrifugal cicatricial alopecia, discoid lupus erythematosus, folliculitis decalvans, tinea capitis, and dissecting cellulitis, to confirm the diagnostically meaningful findings for representative diseases. This attempt redefined, for instance, yellow dots, short vellus hairs, exclamation mark hairs, black dots, and broken hairs as the findings of diagnostic significance for alopecia areata and hair diameter diversity, peripilar sign, and focal atrichia for androgenetic alopecia/female pattern hair loss. An updated diagnostic flowchart is proposed with the instructions to maximize its usefulness. Current limitations and future perspectives of trichoscopy as well as other emerging non-invasive diagnostic modalities for hair diseases are also discussed.
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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 | 0.062 | 0.125 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.047 | 0.025 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".