Management of shoulder pain by UK general practitioners (GPs): a national survey
Bibliographic record
Abstract
OBJECTIVES: Studies in Canada, the USA and Australia suggested low confidence among general practitioners (GPs) in diagnosing and managing shoulder pain, with frequent use of investigations. There are no comparable studies in the UK; our objective was to describe the diagnosis and management of shoulder pain by GPs in the UK. METHODS: A national survey of a random sample of 5000 UK GPs collected data on shoulder pain diagnosis and management using two clinical vignettes that described primary care presentations with rotator cuff tendinopathy (RCT) and adhesive capsulitis (AdhC). RESULTS: Seven hundred and fourteen (14.7%) responses were received. 56% and 83% of GPs were confident in their diagnosis of RCT and AdhC, respectively, and a wide range of investigations and management options were reported. For the RCT presentation, plain radiographs of the shoulder were most common (60%), followed by blood tests (42%) and ultrasound scans (USS) (38%). 19% of those who recommended a radiograph and 76% of those who recommended a USS did so 'to confirm the diagnosis'. For the AdhC presentation, the most common investigations were blood tests (60%), plain shoulder radiographs (58%) and USS (31%). More than two-thirds of those recommending a USS did so 'to confirm the diagnosis'. The most commonly recommended treatment for both presentations was physiotherapy (RCT 77%, AdhC 71%) followed by non-steroidal anti-inflammatory drugs (RCT 58%, AdhC 74%). 17% opted to refer the RCT to secondary care (most often musculoskeletal interface service), compared with 31% for the AdhC. CONCLUSIONS: This survey of GPs in the UK highlights reliance on radiographs and blood tests in the management of common shoulder pain presentations. GPs report referring more than 7 out of 10 patients with RCT and AdhC to physiotherapists. These findings need to be viewed in the context of low response to the survey and, therefore, potential non-response bias.
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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 | 0.002 | 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) | 0.001 | 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".