Investigating the effects of percussion massage therapy on pain, functionality, muscle diameter, and proprioception in ındividuals with ACL reconstruction: a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Percussion massage therapy (PMT) integrates traditional massage with vibration therapy. This study examined the effects of adding PMT to a structured exercise program for individuals who underwent surgery after an anterior cruciate ligament (ACL) injury. METHODS: A total of 24 individuals aged 18-40 were included in the study. Participants were divided into the PMT and structured exercise groups (SEG). The SEG group received a progressive neuromuscular exercise program, and the PMT group received the same structured exercise program and PMT. Range of motion (ROM) was assessed using the Goniometer Pro smartphone application, joint position sense (JPS) was measured goniometer, pain intensity was evaluated with the Visual Analog Scale (VAS), functionality was assessed using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), balance was measured with the Berg Balance Scale, quality of life was evaluated using the Short Form-36 (SF-36), and muscle diameter was measured via ultrasonography. RESULTS: Significant improvements were observed in all parameters in both groups post-treatment (p < 0.05). The PMT group showed superior results compared to the SEG group in ROM, JPS (60°), pain, functionality, balance, and quality of life (particularly in the general health perception sub-parameter of SF-36) (p < 0.05). CONCLUSIONS: The findings of this study suggest that incorporating PMT, a novel approach in the literature, into the rehabilitation program following ACL reconstruction could be effective. PMT could be an alternative treatment method that can be used in conjunction with exercise programs in ACL rehabilitation. TRIAL REGISTIRATION: NCT06185231.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".