Updates on Pityriasis Rubra Pilaris: A Scoping Review
Bibliographic record
Abstract
Pityriasis rubra pilaris (PRP) is a rare, inflammatory papulosquamous skin disease with unknown exact etiology. Historically, PRP has been challenging to diagnose, especially during the acute phase, and to treat, due to its unclear pathogenesis. To better inform clinical practice, a literature review was conducted employing a broad search strategy to capture PRP-related published studies between January 1, 2012 to October 31, 2022. Two hundred twenty-one studies were identified, which were categorized into 9 themes: (1) potential causes and triggering factors, (2) comorbidities, (3) diagnostic difficulties, (4) genetics, (5) clinical manifestations and laboratory values, (6) treatment, (7) treatment-related adverse events, (8) quality of life, and (9) other. COVID-19 infection, COVID-19 vaccination, and malignancy were the most commonly reported potential triggering factors. Misdiagnosis is very common during the early acute stages. Pathogenesis and genetic studies have further implicated caspase recruitment domain family member 14 (CARD14) mutations in the development of familial PRP (Type V) and have underlined the overlap between psoriasis and PRP. To date, there are currently no specific and validated scoring systems or tools to assess the severity of PRP. While large, randomized trials are still lacking, biologic agents remain the most effective therapy.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".