Effect of acupuncture on patients with mild cognitive impairment assessed using functional near-infrared spectroscopy on week 12 (close-out): a pilot study protocol
Bibliographic record
Abstract
BACKGROUND: Currently, there is no clearly established therapy to treat mild cognitive impairment (MCI); consequently, alternative therapies, such as acupuncture, have been attempted. In many clinical studies, the potential benefits of acupuncture for cognitive improvement have been identified in clinical outcomes; however, the mechanism remains unclear. Accordingly, this study aims to investigate the therapeutic mechanism of acupuncture therapy using functional near-infrared spectroscopy and its feasibility in treating individuals with impaired cognitive function. METHODS: This study is designed to be a prospective, two-arm, parallel clinical trial involving 24 participants. The patient group will be treated with acupuncture twice per week for 12 weeks; meanwhile, the healthy control group will not undergo acupuncture treatment. Functional near-infrared spectroscopy assessment and a working memory test will be performed at baseline and every 6 weeks to investigate the therapeutic mechanism of acupuncture. The primary outcome will be measured using the Korean version of the Montreal Cognitive Assessment. The secondary outcomes will be the Alzheimer's Disease Assessment Scale-cognitive subscale score, working memory task accuracy, response rate, response time, and hemodynamic response of the prefrontal lobe. The outcomes will be evaluated at baseline, and at 6 and 12 weeks after subject allocation. DISCUSSION: This clinical pilot trial is designed to determine the feasibility of acupuncture as an effective and safe treatment for improving cognitive function in patients with MCI. Results of this study may provide guidance for future larger-scale clinical trials. TRIAL REGISTRATION: Clinical Research Information Service (CRIS), Republic of Korea: KCT0002451. Registered September 5, 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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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".