Management of Generalized Vitiligo in Adolescent with Tofacitinib: Clinical Case
Bibliographic record
Abstract
Background. Vitiligo is a depigmenting skin disease characterized by selective loss of melanocytes leading to development of typical white spots. There are various theories on vitiligo etiology: genetic, autoimmune, neurogenic, autoinflammatory, oxidative stress theory, and many others. Generally accepted dominant role is given to the concept of its autoimmune nature. Vitiligo management traditionally includes different methods of phototherapy, topical and systemic glucocorticoids (GC), and calcineurin inhibitors. Recently, Janus kinase inhibitors (JAK) have shown its efficacy in treatment of vitiligo. Clinical case description. 13-year-old male adolescent has complaints of hypopigmentation areas on the skin of face, trunk and limbs that appeared after active solar insolation during summer vacation. Dermatologist has determined a diagnosis of vitiligo according to clinical picture. Topical GC of the 3rd activity class were used for treatment, as well as course of local narrow-band medium-wave photodynamic therapy (311 nm, No. 30) with no significant effect. The patient was admitted to the dermatology department of Research Institute of Pediatrics and Children’s Health in Petrovsky National Research Centre of Surgery where therapy with JAK inhibitor, tofacitinib, was initiated due to inefficacy of previous treatment and the generalized form of the disease. Conclusion. Management of vitiligo with JAK inhibitors, in particular tofacitinib, is a promising method and it can lead to significant clinical effect with safety profile comparable to conventional therapies for this pathology.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".