Myofascial Pain as an Unseen Comorbidity in Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: This review aimed to identify, summarize, and appraise the evidence supporting the coexistence of myofascial pain (MPS) and trigger points (MTrP) in osteoarthritis (OA), and the effectiveness of MTrPs treatments in OA-related pain and physical function outcomes. METHODS: Three databases were searched from inception to June 2022. We included observational and experimental studies to fulfill our 2 study aims. Two independent reviewers conducted 2-phase screening procedures and risk of bias using checklist tools for cross-sectional, quasi-experimental, and randomized control trials. Patient characteristics, findings of active and latent MTrPs in relevant muscles, treatments, and pain and physical function outcomes were extracted from low-risk bias studies. RESULTS: The literature search yielded 2898 articles, of which 6 observational and 7 experimental studies had a low bias risk and the data extracted. Active MTrPs in knee OA patients was more evident in the quadriceps and hamstring muscles than in healthy individuals. Dry needling on active MTrPs improved pain and physical function in the short term compared with sham treatment in hip OA patients. In knee OA, dry needling on latent or active MTrPs improved pain and functional outcomes compared with sham needling but did not result in better pain and physical outcomes when combined with a physical exercise program. DISCUSSION: The presence of active versus latent MTrPs seems to be a more sensitive discriminating feature of OA given that latent is often present in OA and healthy individuals. Dry needling on active MTrPs improved pain and physical function in the short term compared with sham treatment in hip OA patients. However, the small sample size and the few number of studies limit any firm recommendation on the treatment. REGISTRY: The study protocol was prospectively registered in Open Science Framework (https://doi.org/10.17605/OSF.IO/8DVU3).
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".