Motor and autonomic concomitant health improvements with neuromodulation and exercise (MACHINE) training: a randomised controlled trial in individuals with spinal cord injury
Bibliographic record
Abstract
INTRODUCTION: Motor and autonomic dysfunctions are widespread among people with spinal cord injury (SCI), leading to poor health and reduced quality of life. Exercise interventions, such as locomotor training (LT), can promote sensorimotor and autonomic recovery post SCI. Recently, breakthroughs in SCI research have reported beneficial effects of electrical spinal cord stimulation (SCS) on motor and autonomic functions. Despite literature supporting the independent benefits of transcutaneous SCS (TSCS) and LT, the effect of pairing TSCS with LT is unknown. These therapies are non-invasive, customisable and have the potential to simultaneously benefit both sensorimotor and autonomic functions. The aim of this study is to assess the effects of LT paired with TSCS in people with chronic SCI on outcomes of sensorimotor and autonomic function. METHODS AND ANALYSIS: Twelve eligible participants with chronic (>1 year) motor-complete SCI, at or above the sixth thoracic segment, will be enrolled in this single-blinded, randomised sham-controlled trial. Participants will undergo mapping for optimisation of stimulation parameters and baseline assessments of motor and autonomic functions. Participants will then be randomly assigned to either LT+TSCS or LT+Sham stimulation for 12 weeks, after which postintervention assessments will be performed to determine the effect of TSCS on motor and autonomic functions. The primary outcome of interest is attempted voluntary muscle activation using surface electromyography. The secondary outcomes relate to sensorimotor function, cardiovascular function, pelvic organ function and health-related quality of life. Statistical analysis will be performed using two-way repeated measures Analysis of variance (ANOVAs) or Kruskal-Wallis and Cohen's effect sizes. ETHICS AND DISSEMINATION: This study has been approved after full ethical review by the University of British Columbia's Research Ethics Board. The stimulator used in this trial has received Investigation Testing Authorisation from Health Canada. Trial results will be disseminated through peer-reviewed publications, conference presentations and seminars. TRIAL REGISTRATION NUMBER: NCT04726059.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".