Clinical Effect of Electroacupuncture on Acute Sleep Deprivation and Event-Related Potential Affecting the Inhibition Control of the Brain: Study Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
Background: Acute sleep deprivation (ASD) can effect mood, attention, memory, alertness and metabolism. Especially, it is often accompanied by cognitive impairment of the brain. Acupuncture is safe and effective for improving cognitive function, but its underlying mechanism is not fully understood. In this study, an event-related potential (ERP) technique will be employed to measure the behavioral, cognitive, and physiological changes produced by electroacupuncture intervention after ASD. Methods: We will recruit 60 healthy subjects. The participants will be randomly divided into a treatment group, a control group, a sham electroacupuncture group and a blank group, at a 1:1:1:1 ratio. The primary outcome will be determined by the change from baseline to 36 h in the MoCA score. The secondary results include the amplitude and latency of ERP N2 and P3, Go-hit rates, Go-RTs, No-Go-FA rates, the WCST, the Digit Span Subtest of the WAIS, the ESS score and FS-14. The 15 healthy subjects will not receive acupuncture treatment and ASD, but will receive EEG records and cognition functions test at the beginning and end of the experiment. Electroacupuncture intervention will be performed for 30 min once every 12 h, a total of three times. ERP measurements and other tests will be performed after baseline and ASD, and the statistician and outcome evaluator will be blinded to treatment allocation. Discussion: This study is expected to investigate the effectiveness of electroacupuncture in improving cognition for ASD. Trial Registration: ChiCTR2200055999.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.042 | 0.006 |
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".