Short-term effects of neuromuscular electrical stimulation and ultrasound therapies on muscle architecture and functional capacity in knee osteoarthritis: a randomized study
Bibliographic record
Abstract
OBJECTIVE:: To determine the effects of ultrasound therapy and neuromuscular electrical stimulation (NMES) application on the muscle architecture and functional capacity in patients with knee osteoarthritis. DESIGN:: A randomized study. SUBJECTS:: A total of 60 patients with knee osteoarthritis. INTERVENTIONS:: Participants were randomized into one of the following two intervention groups, five days a week, for three weeks: the combination of NMES application, hot pack, and exercise therapy was applied to the NMES group. The combination of therapeutic ultrasound, hot pack and exercise therapy was applied to the ultrasound therapy group. MAIN MEASURES:: Subjects were evaluated for pain and functional capacity with the use of the visual analog pain scale (VAS), Western Ontario and McMaster Universities Arthritis Index (WOMAC), and 15 meter walking test. The muscle architecture (muscle thickness, pennation angle and fascicle length) was assessed from vastus lateralis and quadriceps femoris muscles bilaterally by ultrasonography. RESULTS:: Two groups presented significant improvements in all outcome measures before and after treatment ( P < 0.01). There were significant improvements in VAS rest pain ( P < 0.05), VAS activity pain ( P < 0.05), WOMAC pain ( P < 0.05), WOMAC stiffness score ( P < 0.05), and WOMAC physical function ( P < 0.05) for the ultrasound therapy group in comparison to the NMES group. NMES group exhibited more increases in the muscle thickness and fascicle length values when compared to ultrasound therapy group ( P < 0.05). CONCLUSION:: Ultrasound therapy appears to be an effective treatment in reducing pain and improving functional capacity. NMES application has more effects on the muscle architecture.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".