Idiopathic guttate hypomelanosis treated with 308-nm excimer light and topical bimatoprost
Bibliographic record
Abstract
Idiopathic guttate hypomelanosis (IGH) is an acquired pigmentary disorder that is characterized by the presence of multiple hypopigmented macules on the shins and forearms. Albeit asymptomatic, it can cause considerable cosmetic anxiety. The pathogenesis is not fully understood and to date, there have been no successful treatments. We report a case of a 48-year-old female who presented with an 8-year history of multiple hypopigmented macules on both legs, typical of IGH. She previously failed to respond to topical pimecrolimus. She received targeted phototherapy with an excimer lamp (308 nm, 250-480 mJ), and a small patch was treated once daily with topical bimatoprost, in addition to the excimer lamp. After five sessions, better improvement was noted on the combination treatment patch; she received combination treatments for further six sessions. Good repigmentation has been achieved on the smaller macules. The larger depigmented macules continue to improve with further treatments. A combination of excimer light with topical bimatoprost appears to be a promising potential treatment option for IGH, a condition where management options are otherwise limited.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".