Association Between Muscle Trigger Points, Ongoing Pain, Function, and Sleep Quality in Elderly Women With Bilateral Painful Knee Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: The objectives of this study were to investigate if referred pain elicited by active trigger points (TrPs) reproduced the symptoms in individuals with painful knee osteoarthritis (OA) and to determine the relationship between the presence of active TrPs, intensity of ongoing pain, function, quality of life, and sleep quality in individuals with painful knee OA. METHODS: Eighteen women with bilateral painful knee OA, aged 79 to 90 years, and 18 matched controls participated. Muscle TrPs were bilaterally explored in several muscles of the lower extremity. Trigger points were considered active if the elicited referred pain reproduced knee symptoms, and TrPs were considered latent if the elicited pain did not reproduce symptoms. Pain was collected with a numerical pain rate scale (0-10), function was assessed with Western Ontario and McMaster Universities, quality of life was assessed with the Medical Outcomes Study Short Form 36 questionnaire, and sleep quality was determined with the Pittsburgh Sleep Quality Index. RESULTS: Women with knee OA exhibited a greater number of active TrPs (mean, 1 ± 1; P < .001) but similar number of latent TrPs (mean, 4 ± 2) than healthy women (mean, 4 ± 3; P = .613). A greater number of active TrPs were associated with higher intensity of ongoing pain (r = 0.605; P = .007). Higher intensity of ongoing knee pain was associated with lower physical function (P < .05). CONCLUSIONS: The referred pain elicited by active TrPs in the lower extremity muscles contributed to pain symptoms in painful knee OA. A higher number of active TrPs was associated with higher intensity of ongoing knee pain.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".