Characterizing high-burden rosacea subjects: a multivariate risk factor analysis from a global survey
Bibliographic record
Abstract
Objective: To characterize rosacea features suitable for identification of high-burden (HB) subjects in clinical practice.Design: Global online survey with subjects recruited using an online panel from the United States, Canada, Italy, United Kingdom, Germany and France. Subjects self-reported a physician’s diagnosis of rosacea.Measurements: HB subjects were defined as those with ≥3/4 domains (quality of life, lifestyle adaptation, time trade-off, willingness to pay) greater than the median. Group characteristics were analyzed and multivariate-logistic modeling used to investigate factors most associated with HB.Results: 710 subjects completed the survey, including 158 HB subjects. HB was observed in all self-declared rosacea severities. HB subjects were more likely to spend more time daily on skin care and experienced approximately double the impact of health problems on work productivity in the past 7 days (p < .01). In the past 12 months, HB subjects were more likely to have at least one visit to the emergency room (41.8% vs 11.2%; p < .01). In the multivariate risk analysis, factors most associated with HB included rosacea severity, impact of health problems on regular daily activities and age at first symptoms.Conclusion: Rosacea has a distinct subset of HB subjects who can be successfully characterized.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".