Effect Of Squat Exercises Associated With Whole Body Vibration In Elderly With Knee Osteoarthritis
Bibliographic record
Abstract
Knee osteoarthritis (OA) is a major cause of chronic disability in elderly. An inflammatory process, marked by increased levels of both pro and anti-inflammatory cytokines, is frequently observed on patients with osteoarthritis. However, we do not know if squat exercises associated with whole body vibration can modify plasma cytokines and physical function in elderly PURPOSE: To investigate the effects of the squat exercise associated with whole body vibration in plasma inflammatory markers and physical function in elderly with knee OA. METHODS: The volunteers were randomized into three groups: (GP) performed the squat exercise in combination with vibration exercise, (GA) performed the squat without vibration and (CG) control group. The intervention groups (GP and GA) performed a training program consisting of squat exercises with or without whole body vibration three times/week on alternate days for 12 weeks. Peripheral blood samples were collected from 32 elderly with knee OA, determined by clinical and radiographic examinations, before and after training. The soluble receptors for TNF-α (sTNFR1 and sTNFR2) were analyzed by ELISA. The Western Ontario and McMaster University Osteoarthritis Index (WOMAC) questionnaire was used for assessing self-reported physical function, pain and stiffness.To evaluate physical and functional performance, we used the 6-minute walk test, the Berg scale, and the gait speed test. For all variables analyzed, we used the delta (post - pre value = delta) and differences between groups were tested using One-Way ANOVA with Tukey post hoc. RESULTS: Significant differences only were found between the delta (post - pre intervention) of CG and PG, as demonstrated by decreased plasma levels of sTNFR1 and sTNFR2 (p <0.001 and p <0.05, respectively), improvement of balance (p <0. 05), decreased self-reported pain (p <0.05) and increase the speed and distance traveled (p <0.05 and <0.001 respectively) after 12 weeks training squat exercise in combination with vibration exercise. CONCLUSION: These results indicate that adding vibration to squat exercises training in elderly with knee osteoarthritis can help to reduction inflammatory biomarkers and that changes in these concentrations may improve physical function. Supported by FAPEMIG, CNPq
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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) | 0.001 | 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".