Effects of Different Strength Training on Muscle Architecture: Clinical and Ultrasonographic Evaluation in Knee Osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Different strengthening exercises are generally prescribed to overcome the undesirable effects of decreased muscular function on the osteoarthritic joint. Although a few studies have shown the effects of strengthening on the muscle structure in healthy individuals, the literature lacks relevant data concerning knee osteoarthritis. OBJECTIVE: To evaluate the effects of different exercises on quadriceps muscle strength and structure in persons with knee osteoarthritis. DESIGN: A randomized controlled study. SETTING: Physical medicine and rehabilitation department of a university hospital. POPULATION: Sixty-one patients with knee osteoarthritis were randomly assigned into 6 exercise groups (isometric right/left, isotonic right/left, isokinetic right/left). METHODS: Subjects were evaluated for pain and functional status with use of the visual analog pain scale, Western Ontario and McMaster Universities Arthritis Index, 50-step walking, and single-leg stance tests before and after 15 sessions of physical therapy. Isokinetic tests were performed at 60° per second. Ultrasonographic measurements for pennation angle, fascicle length, and muscle thickness were performed from the vastus lateralis muscles bilaterally. RESULTS: Increased knee extensor strength was observed bilaterally in the isometric group (P < .01). In the same group, fascicle length and muscle thickness on the strengthened side (P < .01) and fascicle length on the contralateral side (P < .05) were increased. In the isokinetic group, muscle thickness bilaterally and fascicle length on the contralateral side increased (all P < .05). In the isotonic group, muscle thickness increased bilaterally (P < .05). CONCLUSION: These findings showed that isometric quadriceps training resulted in bilateral strengthening and that accompanying increase in muscle thickness and fascicle length in the same group was consistent with the strength improvement. In this study we evaluated the effects of different strength training on muscle strength and architecture in patients with knee osteoarthritis by using isokinetic measurements and ultrasound. Our results suggest that exercises may influence the muscle architecture in patients with knee osteoarthritis. To our knowledge, this study is the first to demonstrate the effects of cross-education on 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".