Clinical Study on the Intervention Effect of Scalp Clustery Accupuncture on Cognitive Function of Subcortical Arteriosclerotic Encephalopathy
Bibliographic record
Abstract
Objective To explore the effectiveness of the intervention of scalp clustery acupuncture in treating cognitive function of subcortical arteriosclerotic encephalopathy.Method Sixty patients with SAE who met inclusion and exclusion criteria were randomized into a treatment group and a control group,30 in each group.The treatment group was intervened by scalp clustery acupuncture,and the control group was by Donepezil Hydrochloride Tables.Mini-Mental State Examination(MMSE),Montreal Cognitive Assessment(MoCA),and determination of P300 latency period and amplitude were adopted for evaluation.Result The total effective rate was 83.3% in the treatment group versus 53.3% in the control group,and the difference was statistically significant(P0.01).After treatment,inner-group comparison of MMSE and MoCA scores and P300 latency period and amplitude showed significant improvements(all P0.01);after treatment,the differences between the treatment group and control group were statistically significant in comparing MMSE and MoCA scores,and P300latency period and amplitude(P0.05).Conclusion Scalp clustery accupuncture is an effective approach,which is conductive to the improvement of cognitive function of SAE.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".