Clinical manifestations and treatment outcomes in prurigo pigmentosa (Nagashima disease): A systematic review of the literature
Bibliographic record
Abstract
BACKGROUND: Prurigo pigmentosa (PP) is a rare inflammatory dermatosis characterized by pruritic erythematous papules that coalesce to form a reticulate pattern. PP is often misdiagnosed, and patients are treated with ineffective therapies. Although the majority of reports about PP are from East Asia, patients of all backgrounds can be affected. OBJECTIVES: To perform a systematic review of reported PP cases with the purpose of summarizing the clinical presentation and treatment of PP. METHODS: MEDLINE and Embase were searched for original articles describing PP. We identified 115 studies from 24 countries representing 369 patients to include in the analysis. RESULTS: Of the 369 patients included in the analysis, the mean age was 25.6 years (range: 13-72 years) with 72.1% (266 of 369) female. Risk factors or aggravating factors were described in 52.3% (193 of 369) of patients and included dietary changes (25.5%, 94 of 369), friction (8.4%, 31 of 369), sweat (7.6%, 28 of 369), and ketonuria (5.1%, 19 of 369). Of those patients who experienced PP following dietary changes, 40.4% (38 of 94) started a ketogenic diet. Minocycline monotherapy was the most frequently prescribed treatment for PP (20.9%, 77 of 369), achieving complete resolution in 48.1% (37 of 77) of patients. CONCLUSIONS: PP is sometimes associated with ketogenic diets and can be effectively managed with oral tetracyclines.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".