Rosacea treatments: Current standards and additional options
Bibliographic record
Abstract
Abstract Background Rosacea, a chronic facial and ocular inflammatory disease, is readily visible with consequential adverse psychosocial impacts. Progress in epidemiology, pathophysiology, treatments, psychosocial and quality of life impact has led to improved outcomes. Additionally, there has been a transition to updated clinical criteria for diagnosis and classification, the phenotype approach, based on rosacea‐associated features. Objective Our objective was to identify current evidence‐based standards of treatment for rosacea highlighting recently approved interventions and including innovative options. Methods Reviews establishing current standards of care published over the past three years and English language clinical studies of rosacea treatment from 2018‐ March 2021 were included. In addition to pivotal trials, the latter were also selected based on innovation and practicality of the intervention. Results In addition to treatments identified in guidelines and systematic reviews, additional options derive from use in other dermatological conditions ‐ such as botulinum toxin, hydroxychloroquine, photodynamic therapy, radiofrequency with or without microneedling ‐ or from other medical conditions, such as artemether and sumatriptan. Conclusion We provide a template of longitudinal care for rosacea based on features divided into current standards and additional options. The latter may provide the impetus for further research and development to provide options with greater efficacy, longer remissions and/or lower risk of adverse events to improve outcomes in patients with rosacea.
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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 | 0.016 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| 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".