Effects of TENS on Pain, Disabiliy, Quality of Life and Depression in Patients with Knee Osteoarthritis
Bibliographic record
Abstract
Objective: The aim of this randomized controlled trial was to evaluate the effects of transcutaneous electrical nerve stimulation (TENS) on pain, disability, functional performance, quality of life (QoL) and depression in patients with knee osteoarthritis (OA). Materials and Methods: Forty patients with primary knee OA diagnosed according to The American College of Rheumatology criteria were randomized into groups. Patients in the Group 1 received TENS, exercise program and hot pack. Group 2 received placebo TENS, exercise program, hot pack and served as a control group. Assessment of pain (visual analog scale, VAS; Western Ontario McMaster Osteoarthritis Index, WOMAC pain score), disability and stiffness (WOMAC physical function and stiffness score), functional performance (6-minute walk distance test, 6MWD; 10 steps stairs climbing up-down time), QOL (Short Form 36, SF 36) and depression (Beck Depression Inventory, BDI) were done in all patients before and after the treatment. Treatment sessions were performed 5 days a week, for 3 weeks. Results: Both groups showed significant improvements in pain, disability, stiffness, functional performance, most of the subscores of SF 36 and depression score after the 3 weeks treatment program. The improvements in pain, WOMAC pain, disability and sub-scores of SF 36 were better in the active TENS group compared to the control group. Conclusion: The results of this study suggest that addition of TENS to hotpack and exercise program is more effective in decreasing knee pain and related disability and improving QoL in patients with knee OA. (Turk J Rheumatol 2010; 25: 116-21)
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".