Myofascial Pain in Patients Waitlisted for Total Knee Arthroplasty
Bibliographic record
Abstract
BACKGROUND: Knee pain is one of the major sources of pain and disability in developed countries, particularly in aging populations, and is the primary indication for total knee arthroplasty (TKA) in patients with osteoarthritis (OA). OBJECTIVES: To determine the presence of myofascial pain in OA patients waitlisted for TKA and to determine whether their knee pain may be alleviated by trigger point injections. METHODS: Following ethics approval, 25 participants were recruited from the wait list for elective unilateral primary TKA at the study centre. After providing informed consent, all participants were examined for the presence of active trigger points in the muscles surrounding the knee and received trigger point injections of bupivacaine. Assessments and trigger point injections were implemented on the first visit and at subsequent visits on weeks 1, 2, 4 and 8. Outcome measures included the Timed Up and Go test, Brief Pain Inventory, Centre for Epidemiologic Studies Depression Scale, State-Trait Anxiety Inventory and Short-Form McGill Pain Questionnaire. RESULTS: Myofascial trigger points were identified in all participants. Trigger point injections significantly reduced pain intensity and pain interference, and improved mobility. All participants had trigger points identified in medial muscles, most commonly in the head of the gastrocnemius muscle. An acute reduction in pain and improved functionality was observed immediately following intervention, and persisted over the eight-week course of the investigation. CONCLUSION: All patients had trigger points in the vastus and gastrocnemius muscles, and 92% of patients experienced significant pain relief with trigger point injections at the first visit, indicating that a significant proportion of the OA knee pain was myofascial in origin. Further investigation is warranted to determine the prevalence of myofascial pain and whether treatment delays or prevents TKA.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".