Using TENS to Enhance Therapeutic Exercise in Individuals with Knee Osteoarthritis
Bibliographic record
Abstract
Transcutaneous electrical nerve stimulation (TENS) facilitates quadriceps voluntary activation in experimental settings. Augmenting therapeutic exercise (TE) with TENS may enhance the benefits of TE in individuals with knee osteoarthritis (KOA) and quadriceps voluntary activation failure (QVAF). PURPOSE: This study aimed to determine the effect of TENS + TE on patient-reported function, quadriceps strength, and voluntary activation, as well as physical performance compared with sham TENS + TE (Sham) and TE alone in individuals with symptomatic KOA and QVAF. METHODS: Ninety individuals participated in a double-blinded randomized controlled trial. Everyone received 10 standardized TE sessions of physical therapy. TENS + TE and Sham groups applied the respective devices during all TE sessions and throughout activities of daily living over 4 wk. The Western Ontario and McMaster University Osteoarthritis Index (WOMAC), quadriceps strength, and voluntary activation, as well as a 20-m walk test, chair-stand test, and stair-climb test were performed at baseline, after the 4-wk intervention (post 1) and at 8 wk after the start of the intervention (post 2). Mixed-effects models were used to determine between-group differences between baseline and post 1, as well as baseline and post 2. RESULTS: Improvements in WOMAC subscales, quadriceps strength, and voluntary activation, 20-m walk times, chair-stand repetitions, and stair-climb time were found at post 1 and post 2 compared with baseline for all groups (P < 0.05). WOMAC Pain and Stiffness improved in the TENS + TE group compared with TE alone at post 1 (P < 0.05); yet, no other between-group differences were found. CONCLUSIONS: TE effectively improved patient-reported function, quadriceps strength, and voluntary activation, as well as physical performance in individuals with symptomatic KOA and QVAF, but augmenting TE with TENS did not improve the benefits of TE.
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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 | 0.001 |
| 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".