Effect of active TENS versus de-tuned TENS on walking capacity in patients with lumbar spinal stenosis: a randomized controlled trial
Bibliographic record
Abstract
Lumbar spinal stenosis (LSS) leads to diminished blood flow to the spinal nerves causing neurogenic claudication and impaired walking ability. Animal studies have demonstrated increased blood flow to the spinal nerves and spinal cord with superficial para-spinal electrical stimulation of the skin. The aim of this study was to assess the effectiveness of active para-spinal transcutaneous electrical nerve stimulation (TENS) compared to de-tuned TENS applied while walking, on improving walking ability in LSS. This was a two-arm double-blinded (participant and assessor) randomized controlled trial. We recruited 104 participants 50 years of age or older with neurogenic claudication, imaging confirmed LSS and limited walking ability. The primary measure was walking distance measured by the self-paced walking test (SPWT) and the primary outcome was the difference in proportions among participants in both groups who achieved at least a 30% improvement in walking distance from baseline using relative risk with 95% confidence intervals. The active TENS group (n = 49) received para-spinal TENS from L3-S1 at a frequency of 65–100 Hz modulated over 3-s intervals with a pulse width of 100–200 usec, and turned on 2 min before the start and maintained during the SPWT. The de-tuned TENS group (n = 51) received similarly applied TENS for 30 s followed by ramping down to zero stimulus and turned off before the start and during the SPWT. Study funded by The Arthritis Society ($365,000 CAN) and salary support for Carlo Ammendolia funded by the Canadian Chiropractic Research Foundation ($500,000 CAN over 5 years). From August 2014 to January 2016 a total of 640 potential participants were screened for eligibility; 106 were eligible and 104 were randomly allocated to active TENS or de-tuned TENS. Both groups showed significant improvement in walking distance but there was no significant difference between groups. The mean difference between active and de-tuned TENS groups was 46.9 m; 95% CI (− 118.4 to 212.1); P = 0.57. A total of 71% (35/49) of active TENS and 74% (38/51) of de-tuned TENS participants achieved at least 30% improvement in walking distance; relative risk (RR), 0.96; 95% CI, (0.7 to 1.2) P = 0.77. Active TENS applied while walking is no better than de-tuned TENS for improving walking ability in patients with degenerative LSS and therefore should not be a recommended treatment in clinical practice. ClinicalTrials.gov ID: NCT02592642 . Registration October 30, 2015.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".