Resistance Training for Medial Compartment Knee Osteoarthritis and Malalignment
Bibliographic record
Abstract
PURPOSES: 1) To evaluate the effects of a 12-wk high-intensity knee extensor and flexor resistance training program on strength, pain, and adherence in patients with advanced knee osteoarthritis and varus malalignment and 2) to generate pilot data for change in dynamic knee joint load, patent-reported outcomes, and self-efficacy after training. METHODS: Fourteen patients (48.35 +/- 6.51 yr) with radiographically confirmed medial compartment knee osteoarthritis and varus malalignment of the lower limb were recruited from a surgical waiting list for high tibial osteotomy. Participants completed a high-intensity isokinetic resistance training program three times per week for 12 wk. Knee extensor and flexor strength were assessed every third week, whereas pain and adherence were recorded at every training session. The external knee adduction moment during the gait, the 6-min-walk test, the Knee Injury and Osteoarthritis Outcome Score (KOOS), and the Arthritis Self-Efficacy Scale (ASES) were also evaluated before and after training. RESULTS: Significant improvements in knee extensor and flexor strength were observed without increases in pain during or after training. Adherence to the high-intensity program was high. No significant changes were observed for dynamic knee joint load or the KOOS. There was a significant increase in the function subscale of the ASES only. CONCLUSIONS: These findings suggest that patients with advanced knee osteoarthritis and malalignment can experience substantial gains in strength after a high-intensity resistance training program without concomitant increases in pain, adverse events, or compromised adherence. These findings provide support for future clinical trials with longer-term outcomes.
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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 | 0.001 |
| 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) | 0.002 | 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".