Prevalence of rosacea in the general population of Germany and Russia – The <scp>RISE</scp> study
Bibliographic record
Abstract
BACKGROUND: There is an unmet need for general population-based epidemiological data on rosacea based on contemporary diagnostic criteria and validated population survey methodology. OBJECTIVE: To evaluate the prevalence of rosacea in the general population of Germany and Russia. METHODS: General population screening was conducted in 9-10 cities per country to ensure adequate geographic representation. In Part I of this two-phase study, screening of a representative sample of the general population (every fifth person or every fifth door using a fixed-step procedure on a random route sample) was expedited with use of a questionnaire and algorithm based on current diagnostic criteria for rosacea. Of the subjects that screened positive in the initial phase, a randomly selected sample (every third subject) t`hen underwent diagnostic confirmation by a dermatologist in Part II. RESULTS: A total of 3052 and 3013 subjects (aged 18-65 years) were screened in Germany and Russia respectively. Rosacea prevalence was 12.3% [95%CI, 10.2-14.4] in Germany and 5.0% [95%CI, 2.8-7.2] in Russia. The profile of subjects with rosacea (75% women; mean age of 40 years; mainly skin phototype II or III, majority of subjects with sensitive facial skin) and subtype distribution were similar. Overall, 18% of subjects diagnosed with rosacea were aged 18-30 years. Over 80% were not previously diagnosed. Within the previous year, 47.5% of subjects had received no rosacea care and 23.7% had received topical and/or systemic drugs. Over one-third (35% Germany, 43% Russia) of rosacea subjects reported a moderate to severe adverse impact on quality of life. CONCLUSION: Rosacea is highly prevalent in Germany (12.3%) and Russia (5.0%). The demographic profile of rosacea subjects was similar between countries and the majority were previously undiagnosed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".