Effects of Diet Control and Telemedicine-Based Resistance Exercise Intervention on Patients with Obesity and Knee Osteoarthritis: A Randomized Control Trial
Bibliographic record
Abstract
This study investigated the effects of home-based nutritional and telemedicine-based resistance exercise interventions on improving body composition, blood biochemistry, and lower-limb functional performance. In total, 66 obese patients with mild-to-moderate knee osteoarthritis were randomly divided into a diet control group (D), elastic band resistance exercise group (E), and diet control plus elastic band exercise group (D + E). Each group was supervised by a clinical dietitian and follow-up was conducted via telephone calls or a communication application to track the participants’ progress. After 12 weeks of intervention, the D (p < 0.001) and D + E (p < 0.001) groups achieved significant weight loss. The D + E group exhibited a significant reduction in body fat relative to the D (p = 0.019) and E (p = 0.012) groups. Compared with the D (p = 0.002) and E (p = 0.019) groups, the D + E group achieved significant improvements in the timed up-and-go test and Western Ontario and McMaster Universities Osteoarthritis total scale. The D + E group experienced significant improvements in total cholesterol (p = 0.001), low-density lipoprotein cholesterol (p = 0.01), and triglyceride levels (p = 0.007) relative to other groups. In conclusion, individual diet control intervention combined with telemedicine-based resistance exercise intervention significantly improved the body composition, blood biochemistry, and lower-limb functional performance of the investigated population with comorbid conditions.
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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) | 0.003 | 0.002 |
| 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".