Contralaterally Controlled Functional Electrical Stimulation Combined With Brain Stimulation for Severe Upper Limb Hemiplegia—Study Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
Background: Approximately two-thirds of stroke survivors experience chronic upper limb paresis, and of them, 50% experience severe paresis. Treatment options for severely impaired survivors are often limited. Rehabilitation involves intensively engaging the paretic upper limb, and disincentivizing use of the non-paretic upper limb, with the goal to increase excitability of the ipsilesional primary motor cortex (iM1) and suppress excitability of the undamaged (contralesional) motor cortices, presumed to have an inhibitory effect on iM1. Accordingly, brain stimulation approaches, such as repetitive transcranial magnetic stimulation (rTMS), are also given to excite iM1 and/or suppress contralesional motor cortices. But such approaches aimed at ultimately increasing iM1 excitability yield limited functional benefit in severely impaired survivors who lack sufficient ipsilesional substrate. Aim: Here, we test the premise that combining Contralaterally Controlled Functional Electrical Stimulation (CCFES), a rehabilitation technique that engages the non-paretic upper limb in delivery of neuromuscular electrical stimulation to the paretic upper limb, and a new rTMS approach that excites intact, contralesional higher motor cortices (cHMC), may have more favorable effect on paretic upper limb function in severely impaired survivors based on recruitment of spared, transcallosal and (alternate) ipsilateral substrate. Methods: In a prospective, double-blind, placebo-controlled RCT, 72 chronic stroke survivors with severe distal hand impairment receive CCFES plus cHMC rTMS, iM1 rTMS, or sham rTMS, 2X/wk for 12wks. Measures of upper limb motor impairment (Upper Extremity Fugl Meyer, UEFM), functional ability (Wolf Motor-Function Test, WMFT) and perceived disability are collected at 0, 6, 12 (end-of-treatment), 24, and 36 wks (follow-up). TMS is performed at 0, 12 (end-of-treatment), and 36 wks (follow-up) to evaluate inter-hemispheric and ipsilateral mechanisms. Influence of baseline severity is also characterized with imaging. Conclusions: Targeting of spared neural substrates and rehabilitation which engages the unimpaired limb in movement of the impaired limb may serve as a suitable combinatorial treatment option for severely impaired stroke survivors. ClinicalTrials No: NCT03870672.
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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 | 0.014 | 0.013 |
| Meta-epidemiology (narrow) | 0.007 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.050 | 0.009 |
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".