Impact of a three-month resistance training program for elderly persons with knee osteoarthritis residing in the community of Santa Cruz, Rio Grande do Norte, Brazil
Bibliographic record
Abstract
Abstract Objective: to evaluate the impact of a three-month resistance exercise program on the pain and functionality of elderly patients with knee osteoarthritis from the city of Santa Cruz, Rio Grande do Norte. Method: a quasi-experimental study was performed with 13 elderly patients diagnosed with knee osteoarthritis, who underwent a resistance training program twice a week for 12 weeks. Pain, muscle strength, functionality, quality of life and patient satisfaction were evaluated using the following instruments: the visual analog scale, one repetition maximum testing, the Western Ontario and McMaster Universities Osteoarthritis Index, the Timed Up and Go Test, the 6-minute walk Test, the Short Form (36) Health Survey and the Likert scale. The paired T-test and ANOVA for repeated measures were used for statistical analysis. Results: the mean age of the patients was 62.0 (±10.0) years. At the end of the study, the pain, muscle strength, functional status and some areas of quality of life of the elderly had improved. Conclusion: resistance exercises were an effective and safe method of improving the pain, muscle strength, functionality and quality of life of the population studied. The elderly should be encouraged to perform supervised strength training therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".