Effectiveness of isometric exercise in the management of tendinopathy: a systematic review and meta-analysis of randomised trials
Bibliographic record
Abstract
OBJECTIVE: To systematically review and critically appraise the literature on the effectiveness of isometric exercise in comparison with other treatment strategies or no treatment in tendinopathy. DESIGN: A systematic review and meta-analysis of randomised controlled trials. DATA SOURCES: Electronic searches of Medline, Cumulative Index to Nursing and Allied Health Literature, EMBASE and Cochrane were undertaken from inception to May 2020. METHODS: . RESULTS: Ten studies were identified and included in the review, including participants with patellar (n=4), rotator cuff (n=2), lateral elbow (n=2), Achilles (n=1) and gluteal (n=1) tendinopathies. Three were of good and seven were of poor overall quality. Based on limited evidence (level 3), isometric exercise was not superior to isotonic exercise for chronic tendinopathy either immediately following treatment or in the short term (≤12 weeks) for any of the investigated outcome measures. Additionally, for acute rotator cuff tendinopathy, isometric exercise appears to be no more effective than ice therapy in the short term (limited evidence; level 3). SUMMARY: Isometric exercise does not appear to be superior to isotonic exercise in the management of chronic tendinopathy. The response to isometric exercise is variable both within and across tendinopathy populations. Isometric exercise can be used as part of a progressive loading programme as it may be beneficial for selected individuals. PROSPERO REGISTRATION NUMBER: CRD42019147179.
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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 | 0.041 | 0.098 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.032 | 0.039 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".