The Use of Direct Immunofluorescence in Frontal Fibrosing Alopecia
Bibliographic record
Abstract
BACKGROUND: Frontal fibrosing alopecia (FFA) differs from lichen planopilaris (LPP) in many clinical aspects, but histology fails to distinguish between these entities. Direct immunofluorescence (DIF) is a diagnostic technique used for autoimmune diseases, including those affecting skin and hair. OBJECTIVE: To characterize DIF patterns in patients with FFA. METHOD: Data was collected retrospectively from FFA cases presenting to the Centre de Santé Sabouraud Hair Clinic in Paris from November 2013 to November 2014. RESULTS: Of 149 patients with FFA, 44 cases underwent DIF. Thirteen cases showed positive results with DIF. Patterns characteristic of LPP and lupus erythematosus were observed, with nearly half showing nonspecific staining. CONCLUSION: DIF patterns in patients with FFA were variable. This diagnostic technique should be used with caution in cases of cicatricial alopecia, particularly FFA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".