Effect of transcranial direct current stimulation combined with transcutaneous auricular vagus nerve stimulation on poststroke cognitive impairment: a study protocol for a randomised controlled trial
Bibliographic record
Abstract
INTRODUCTION: Poststroke cognitive impairment is a common complication in stroke survivors, seriously affecting their quality of life. Therefore, it is crucial to improve cognitive function of patients who had a stroke. Transcranial direct current stimulation (tDCS) and transcutaneous auricular vagus nerve stimulation (taVNS) are non-invasive, safe treatments with great potential to improve cognitive function in poststroke patients. However, further improvements are needed in the effectiveness of a single non-invasive brain stimulation technique for cognitive rehabilitation. This study protocol aims to investigate the effect and neural mechanism of the combination of tDCS and taVNS on cognitive function in patients who had a stroke. METHODS AND ANALYSIS: In this single-centre, prospective, parallel, randomised controlled trial, a total of 66 patients with poststroke cognitive impairment will be recruited and randomly assigned (1:1:1) to the tDCS group, the taVNS group and the combination of tDCS and taVNS group. Each group will receive 30 min of treatment daily, five times weekly for 3 weeks. Primary clinical outcome is the Montreal Cognitive Assessment. Secondary clinical outcomes include the Mini-Mental State Examination, Stroop Colour Word Test, Trail Marking Test, Symbol Digit Modalities Test and Modified Barthel Index. All clinical outcomes, functional MRI and diffusion tensor imaging will be measured at preintervention and postintervention. ETHICS AND DISSEMINATION: The trial has been approved by the Ethics Committee of the First Affiliated Hospital of Yangtze University (approval no: KY202390). The results will be submitted for publication in peer-reviewed journals or at scientific conferences. TRIAL REGISTRATION NUMBER: ChiCTR2300076632.
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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 | 0.045 | 0.037 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.021 | 0.008 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.011 | 0.007 |
| Insufficient payload (model declined to judge) | 0.065 | 0.012 |
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".