Effects of neuromuscular electrical stimulation and low-level laser therapy on neuromuscular parameters and health status in elderly women with knee osteoarthritis: A randomized trial
Bibliographic record
Abstract
OBJECTIVE: To determine the effects of neuromuscular electrical stimulation and low-level laser therapy on neuromuscular parameters and health status in elderly subjects with knee osteoarthritis. DESIGN: A randomized evaluator-blinded clinical trial. SUBJECTS: Forty-five elderly women with knee osteoarthritis. METHODS: Subjects were randomized into 1 of the following 3 intervention groups: electrical stimulation group (18-32 min pulsed current, stimulation frequency 80 Hz, pulse duration 400 μs, stimulation intensity 40% of maximal isometric voluntary contraction), laser group (dose 4-6 J per point, 6 points at the knee joint) or combined group (electrical stimulation plus laser therapy). The outcomes included muscle thickness and anatomical cross-sectional area (ultrasonography), knee extensors' electrical activity (electromyography), torque (dynamometry) and health status (Western Ontario and McMaster Universities Osteoarthritis Index). All groups underwent a 4-week control period (without intervention) followed by an 8-week intervention period. RESULTS: Muscle thickness and anatomical cross-sectional area increased in the electrical stimulation and combined groups. All groups presented similar improvements in torque, electrical activity and health status. CONCLUSION: Electrical stimulation alone or in combination with laser therapy generated positive effects on all evaluated parameters. Laser therapy increased health status and electrical activity, but had no effect on muscle mass.
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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 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".