Clinical Effect of Cerebellar Fastigial Nucleus Electrical Stimulation in the Treatment of Vascular Cognitive Impairment of Varying Degrees
Bibliographic record
Abstract
Objective To investigate the clinical effects of cerebellar fastigial nucleus electrical stimulation(FNS) in the treatment of vascular cognitive impairment(VCI)of varying degrees.Methods 60 VCI patients admitted to our hospital from January 2009 to June 2011 were selected.The patients were divided into vascular cognitive impairment but no dementia(VCIND group) and vascular dementia(VaD group) with each group 30 cases.All the patients were given FNS treatment on the basis of conventional treatment.The event-related potentials P300(ERP-P300) and Montreal cognitive assessment(MoCA)of all patients were observed and compared before and after the treatment.Results After treatment,the scores of MoCA and the latency period and amplitude of ERP-P300 of the VCIND group showed statistically significant differences compared with those before the treatment(t=18.58,26.88,10.06,P0.01).The scores of MoCA and the latency period and amplitude of ERP-P300 of the VaD group also showed statistically significant differences compared with those before the treatment(t=2.54,2.81,2.81,P0.01).The differences of the scores of MoCA and the latency period and amplitude of ERP-P300 between VCIND group and VaD group were statistically significant(t=9.81,20.12,30.16,P0.01).Conclusion FNS can improve cognitive function of VCI patients and is more effective for VCIND patients.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".