How does surgery compare to sham surgery or physiotherapy as a treatment for tendinopathy? A systematic review of randomised trials
Bibliographic record
Abstract
PURPOSE: To assess the effectiveness of surgery on all tendinopathies by comparing it to no treatment, sham surgery and exercise-based therapies for both mid-term (12 months) and long-term (> 12 months) outcomes. METHODS: Our literature search included EMBASE, Medline, CINAHL and Scopus. A combined assessment of internal validity, external validity and precision of each eligible study yielded its overall study quality. Results were considered significant if they were based on strong (Level 1) or moderate (Level 2) evidence. RESULTS: 12 studies were eligible. Participants had the following types of tendinopathy: shoulder in seven studies, lateral elbow in three, patellar in one and Achilles in one. Two studies were of good, four of moderate and six of poor overall quality. Surgery was superior to no treatment or placebo, for the outcomes of pain, function, range of movement (ROM) and treatment success in the short and midterm. Surgery had similar effects to sham surgery on pain, function and range of motion in the midterm. Physiotherapy was as effective as surgery both in the midterm and long term for pain, function, ROM and tendon force, and pain, treatment success and quality of life, respectively. CONCLUSION: We recommend that healthcare professionals who treat tendinopathy encourage patients to comply with loading exercise treatment for at least 12 months before the option of surgery is seriously entertained.
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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 | 0.048 | 0.154 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.026 | 0.016 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".