Effects of rosuvastatin in combination with nimodipine in patients with mild cognitive impairment caused by cerebral small vessel disease
Bibliographic record
Abstract
BACKGROUND: To investigate the clinical efficiency and safeness of the combination of rosuvastatin and nimodipine in treating mild cognitive impairment of cerebral small vessel disease (CSVD) patients. METHODS: A total of 120 patients with mild cognitive impairment caused by CSVD were divided randomly into two groups: an observation group and a control group, each of which had 60 patients. In the observation group, patients were given rosuvastatin in combination with nimodipine, and other patients were given nimodipine in the control group. For the two groups, the course of treatment was six months. Before and after treatments, levels of total cholesterol (TC), triacylglycerol (TG), low density lipoprotein-cholesterol (LDL-C), high density lipoprotein-cholesterol (HDL-C), MMP-9 and high sensitivity C reactive protein (hs-CRP) were measured. Montreal Cognitive Assessment (MoCA) and activities of daily living (ADL) were also evaluated. Incidence of adverse reactions were compared between two groups. RESULTS: The levels of TG, TC and LDL-C were decreased after treatment in the observation group (P<0.01), and these after-treatment levels were lower than the control group. Additionally, after treatment, the levels of MMP-9 and hs-CRP were significant lower in the observation group than the control group. The MoCA and ADL scores were higher in the observation group than the control group after treatment (P<0.05). Moreover, the overall effective rate were higher in the observation group (91.7%) than the control group (65.0%) (P<0.01), while there was no significant difference of the rate of adverse reactions between the observation group and the control one (10.0% vs. 8.3%) (P>0.05). CONCLUSIONS: The combination of rosuvastatin and nimodipine was safe and effective in treating mild cognitive impairment of CSVD patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".