Therapeutic effect of atorvastatin plus nimodipine on mild cognitive impairment in patients with cerebral small vessel disease
Bibliographic record
Abstract
Objective To investigate the therapeutic effect of atorvastatin plus nimodipine on mild cognitive impairment in patients with cerebral small vessel disease.Methods Eighty-eight patients with cerebral small vessel were divided into two groups according to different treatment methods,with 44 patients in each group.Observation group was treated with atorvastatin plus nimodipine,and control group was treated with nimodipine,for 6months as one course.The therapeutic effect,the adverse reaction,the levels of total cholesterol(TC),triacylglycerol(TG),low density lipoprotein-cholesterol(LDL-C)and high density lipoprotein-cholesterol(HDL-C)were compared between two groups.The changes of Montreal Cognitive Assessment(MoCA)scores and activities of daily living(ADL)were observed.Results The total effective rate was 95.45%in observation group,significantly higher than that in control group(72.73%)(P0.01),and there was no significant difference in the incidence of adverse reaction between two groups(9.09%,4.55%)(P0.05).The levels of TC,TG and LDL-C decreased after treatment((4.71±0.88),(1.97±0.40),(2.37±0.47)mmol/L)in comparison with those before treatment((5.80±0.95),(2.58±0.62),(3.36±0.76)mmol/L)in observation group(P0.01),and lower than those in control group after treatment((5.49±0.83),(2.42±0.49),(3.22±0.63)mmol/L)(P0.01).The scores of MoCA and ADL were higher after treatment in observation group(21.70±3.73,67.39±10.03)than those in control group(19.73±2.83,62.16±9.55)(P0.05).Conclusion Atorvastatin plus nimodipine can achieve a satisfactory effect on mild cognitive impairment in patients with cerebral small vessel disease,with mild adverse reaction.
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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) | 0.001 | 0.001 |
| 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".