Experiences From a Combined Dermatology and Rheumatology Clinic
Bibliographic record
Abstract
BACKGROUND: The Dermatology and Rheumatology Treatment Clinic is a novel multidisciplinary clinic where patients are concomitantly assessed by a rheumatologist and dermatologist. OBJECTIVES: To determine the number of patients seen in clinic, patient demographics, and most common diagnoses. METHOD: A retrospective review was performed over a 2-year period. Data collected included patient age, sex, dermatologic diagnosis, rheumatologic diagnosis, biopsies performed, and number of follow-up visits. RESULTS: A total of 320 patients were seen (78% female, 22% male). The most common rheumatologic diagnoses were systemic lupus erythematosus (18%), rheumatoid arthritis (15%), psoriatic arthritis (13%), and undifferentiated connective tissue disease (8%). The most common dermatologic diagnoses were dermatitis (17%), psoriasis (11%), cutaneous lupus (7%), various types of alopecia (6%), and infections (5%). CONCLUSIONS: Skin diagnoses were often unrelated to the underlying rheumatologic diagnosis. Rheumatologists and dermatologists can both benefit from being aware of the dermatologic conditions that rheumatologic patients are experiencing.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".