Efficacy of acupuncture on myofascial trigger points of quadriceps femoris in the treatment of athletes with exercise-induced knee-joint pain
Bibliographic record
Abstract
Objective To observe and evaluate the clinical efficacy of acupuncture on myofascial trigger points of quadriceps femoris in the treatment of athletes with exercise-induced knee-joint pain. Methods Fifty-six athletes with exercise-induced knee-joint pain were enrolled in the study from Shanghai University of Sport. The locations of knee-joint pain that complained by patients were considered as the referred pain. Dry needling of trigger points on quadriceps combined with self-stretching exercise were administrated for 30 s-1 min, three times each day. The McGill pain scroes and knee joint range of motion(ROM) were evaluated before and after the third and sixth time of treatment. Results The scores of McGill and knee joint range of motion were significantly improved after the third and sixth time of treatment, with significant difference (P<0.01). The total effective rate was 96.4% (54/56 cases) at 3 months after the treatment. Conclusion Dry needling of trigger points on quadriceps femoris combined with self-stretching exercise is effective in the treatment of athletes with exercise-induced knee-joint pain. Key words: Sports injury; Myofascial trigger points; Knee joint; Arthralgia; Acupuncture
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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 | 0.000 |
| 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) | 0.001 | 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".