Transcutaneous Electrical Nerve Stimulation Improves Walking Performance in Patients With Intermittent Claudication
Bibliographic record
Abstract
The purpose of this study was to investigate the effects of 2 types of transcutaneous electrical nerve stimulation (TENS) on walking distance and measures of pain in patients with peripheral arterial disease (PAD) and intermittent claudication (IC). In a phase 2a study, 40 participants with PAD and IC completed a graded treadmill test on 2 separate testing occasions. Active TENS was applied to the lower limb on the first occasion; and placebo TENS, on the second. The participants were divided into 2 experimental groups. One group received high-frequency TENS; and the other, low-frequency TENS. Measures taken were initial claudication distance, functional claudication distance, and absolute claudication distance. The McGill Pain Questionnaire (MPQ) vocabulary was completed at the end of the intervention, and the MPQ-Pain Rating Index score was calculated. Four participants were excluded from the final analysis because of noncompletion of the experimental procedure. Median walking distance increased with high-frequency TENS for all measures (P < .05, Wilcoxon signed rank test, all measures). Only absolute claudication distance increased significantly with low-frequency TENS compared with placebo (median, 179-228; Ws = 39; z = 2.025; P = .043; r = 0.48). No difference was observed between reported median MPQ-Pain Rating Index scores: 21.5 with placebo TENS and 21.5 with active TENS (P = .41). Transcutaneous electrical nerve stimulation applied to the lower limb of the patients with PAD and IC was associated with increased walking distance on a treadmill but not with any reduction in pain. Transcutaneous electrical nerve stimulation may be a useful adjunctive intervention to help increase walking performance in patients with IC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".