Efficacy of electrical acupuncture on vascular cognitive impairment with no dementia: study protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Vascular cognitive impairment with no dementia (VCIND), manifested mainly as mild impairment of concentration and executive function, is the early phase of vascular dementia (VD). Currently, there is no specific treatment for VCIND. We hypothesize that electrical acupuncture can improve the mental and motor functions of patients with VCIND. Thus, we designed this randomized controlled trial to test this hypothesis by comparing the therapeutic effect of electrical acupuncture versus sham acupuncture in patients with VCIND. METHOD/DESIGN: In this single-center 3-year study, 120 eligible patients will be recruited and randomly assigned to receive electrical acupuncture treatment (n = 60) or sham acupuncture (n = 60) for 8 consecutive weeks (24 sessions in total), with the same acupoint prescription (DU20, EX-HN3, DU24, DU17, DU26, EX-HN1, HT7, PC6, GB20, SP6). The primary assessment is the Montreal Cognitive Assessment. The secondary assessments are the Modified Barthel Index and Event-Related Potential. All outcomes will be assessed at baseline, endpoint, and follow-up at 8 and 24 weeks after the end of treatment. DISCUSSION: If the outcome confirms the effectiveness and safety of electrical acupuncture in treating VCIND, this treatment is expected to be promoted in clinical practice to treat such patients. TRIAL REGISTRATION: Chinese Clinical Trial Registry identifier: ChiCTR-IIR-17011513 ; Registered on 27 May 2017.
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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 | 0.019 | 0.017 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.050 | 0.007 |
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".