An international survey of current management practices for polymyalgia rheumatica by general practitioners and rheumatologists
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: To explore current management practices for PMR by general practitioners (GPs) and rheumatologists including implications for clinical trial recruitment. METHODS: An English language questionnaire was constructed by a working group of rheumatologists and GPs from six countries. The questionnaire focused on: 1: Respondent characteristics; 2: Referral practices; 3: Treatment with glucocorticoids; 4: Diagnostics; 5: Comorbidities; and 6: Barriers to research. The questionnaire was distributed to rheumatologists and GPs worldwide via members of the International PMR/Giant Cell Arteritis Study Group. RESULTS: In total, 394 GPs and 937 rheumatologists responded to the survey. GPs referred a median of 25% of their suspected PMR patients for diagnosis and 50% of these were returned to their GP for management. In general, 39% of rheumatologists evaluated patients with suspected PMR >2 weeks after referral, and a median of 50% of patients had started prednisolone before rheumatologist evaluation. Direct comparison of initial treatment showed that the percentage prescribing >25 mg prednisolone daily for patients was 30% for GPs and 12% for rheumatologists. Diagnostic imaging was rarely used. More than half (56%) of rheumatologists experienced difficulties recruiting people with PMR to clinical trials. CONCLUSION: This large international survey indicates that a large proportion of people with PMR are not referred for diagnosis, and that the proportion of treatment-naive patients declined with increasing time from referral to assessment. Strategies are needed to change referral and management of people with PMR, to improve clinical practice and facilitate recruitment to clinical trials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 it