Effect of Otago Exercises versus Square-Stepping Exercises on Balance, Fall, and Functional Activities in Geriatric Individuals with Knee Osteoarthritis
Bibliographic record
Abstract
A BSTRACT Background: Osteoarthritis (OA) is a chronic degenerative joint disease that leads to disability. The prevalence of symptomatic knee OA is approximately 22% to 39% in India, which causes significant morbidity and impairment in elderly individuals. Objective: To study the effects of Otago exercise versus square-stepping exercises (SSEs) on balance, fall, and functional activities in geriatric individuals with OA knee. Methods: A study was carried out at Pune among 40 geriatric individuals with age over 65 years. The individuals were assigned at random to the Otago exercise group or SSE. Both groups performed exercises for 40–45 min for 10 days. The primary outcome was balance, which was measured by the Berg Balance Scale and Limits of Stability test. The secondary outcomes were risk of fall, measured by the Morse fall scale and functional activity, measured by the Western Ontario and McMaster Universities Arthritis Index (WOMAC) scale. Results: Both the groups showed significant differences post intervention within the groups ( P < 0.05). Between-group analysis showed that the Otago exercise group showed a higher mean difference in the primary outcomes that is in the Berg Balance Scale (19.25 > 15.24) and limits of stability. The SSE group showed a higher mean difference in Morse fall scale (18.81 > 8.8) and WOMAC scale (18.81 > 8.8). Conclusion: The study concluded that, in older patients with OA knee, Otago exercise is more successful at enhancing balance but SSE is more effective at enhancing fall risk and functional activity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".