Which is the Appropriate Frequency of TENS in Managing Knee Osteoarthritis: High or Low Frequency?
Bibliographic record
Abstract
Aim: To clarify the optimal Transcutaneous Electrical Nerve Stimulation (TENS) frequency in managing pain and functional deficiency and the efficacy of low frequency (LF) and high frequency (HF) -TENS on pain and functional status in patients with knee osteoarthritis (OA). Material and Method: Ninety-three female patients with symptomatic knee OA were enrolled in this study. All the patients were randomly divided sham or LF or HF-TENS groups with five sessions/week of physical therapy as 20 minutes hot pack, 5 minutes therapeutic ultrasonography, and exercise program. Pain on the Visual Analog Scale (VAS) in rest and motion, durations of walk, climbing up and down stairs and pain, stiffness, function and total scores of Western Ontario and McMaster Universities osteoarthritis index (WOMAC) were assessed at baseline, after therapy and 4 weeks after the therapy. Results: The VAS pain in rest and motion were found to be significantly different for each therapy group within the three visits (p
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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) | 0.000 | 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 | 0.001 | 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".