Knowledgebase and Lifestyle Choices in Patients with Psoriatic Arthritis
Bibliographic record
Abstract
To the Editor: Psoriatic arthritis (PsA) is a chronic inflammatory disease involving the skin and joints. It requires detection in primary care, subsequent referral, and initiation of management in secondary care and ongoing joint management. PsA has been associated with greater cardiovascular (CV) disease mortality, morbidity, and atherosclerosis1. The increased CV mortality risk has been shown to be comparable with that of rheumatoid arthritis (RA) and diabetes (risk ratio 1.74, 95% CI 1.32–2.30)2. In addition, risk factors for CV disease, such as hypercholesterolemia, impaired glucose tolerance, and obesity, have all been associated with PsA1,2,3. We sought to establish the current knowledgebase and lifestyle choices of patients with PsA managed in secondary care. This data could then guide changes to services to assist patients in reducing their risk of CV morbidity and mortality. A hundred patients diagnosed with PsA sequentially attending a rheumatology outpatient clinic completed an anonymous electronic questionnaire. Patients were asked to … Address correspondence to Dr. Anna Timmis, Imperial GP Specialty Training, Department of Primary Care and Public Health, Imperial College London, Charing Cross Campus, Reynolds Building, London W6 8RP, UK. E-mail: anna.timmis{at}doctors.org.uk
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".