Prevalence of Myofascial Trigger Points in Patients with Mild to Moderate Painful Knee Osteoarthritis: A Secondary Analysis
Bibliographic record
Abstract
Objective: To determine the prevalence of myofascial trigger points (MTrPs) and the correlation between the number of MTrPs and pain and function in patients presenting knee pain osteoarthritis (OA). Methods: This was a secondary analysis of data from a cross-sectional study. The prevalence of MTrPs located in tensor fasciae latae, hip adductors, hamstrings, quadriceps, gastrocnemius, and popliteus muscles was studied in 114 patients (71 men and 43 women) with knee OA. Pain and functionality were assessed with a numerical pain rating scale (NPRS), the Western Ontario, McMaster Universities Osteoarthritis Index (WOMAC) score, the Barthel Index, and the timed up and go test. Results: The prevalence of latent MTrPs was detected via palpation and was estimated to be 50%, 35%, 25%, 29%, 33%, and 12% for tensor fasciae latae, hip adductors, hamstrings, quadriceps, gastrocnemius, and popliteus muscles, respectively. The prevalence of active MTrPs was estimated to be 11%, 17%, 30%, 18%, 25%, and 17% for tensor fasciae latae, hip adductors, hamstrings, quadriceps, gastrocnemius, and popliteus muscles, respectively. Pain was measured with the NPRS scale and was poorly correlated with the prevalence of latent MTrPs (r = 0.2; p = 0.03) and active MTrPs (r = 0.23; p = 0.01) in the hamstrings. Disability was moderately correlated with the number of latent MTrPs in the tensor fasciae latae muscle (Barthel, r = 0.26; p = 0.01 and WOMAC, r = 0.19; p = 0.04). Conclusions: This secondary analysis found that the prevalence of the MTrPs varied from 11% to 50% in different muscles of patients with mild to moderate painful knee osteoarthritis. Pain was correlated poorly with the prevalence of latent and active MTrPs in the hamstring muscles, and disability correlated moderately with the number of latent MTrPs in tensor fasciae latae.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".