Clinical efficacy of idebenone in stroke patients with mild cognitive impairment, and its effect on regional homogeneity of resting-state functional magnetic resonance imaging of the brain
Bibliographic record
Abstract
Purpose: To evaluate the clinical efficacy of Idebenone in stroke patients with mild cognitive impairment, and its effect on regional homogeneity (ReHo) of resting-state functional magnetic resonance imaging (rs-fMRI) of the brain. Methods: One hundred and twenty stroke patients with mild cognitive impairment who were admitted to the Department of Neurology of the China Rehabilitation Research Center Beijing Boai Hospital from January 2018 to January 2020 were enrolled in this study. The patients were randomly divided into control group and study group. Control group was treated with nimodipine, while the study group received a combination of nimodipine and idebenone. Results: Clinical efficacy was higher in the study group than in the control group (p < 0.05). Scores on Montreal cognitive assessment (MoCA), mini-mental state examination (MMSE), and activity of daily living scale (ADL) were significantly elevated (p < 0.05) in both groups after treatment, but scores for MoCA and ADL were significantly higher in the study group than in the control group (p < 0.05). After 6 months of treatment, there were significantly more patients with improved clinical dementia rating (CDR)in the study group than in the control group (p < 0.05). Conclusion: The use of idebenone and nimodipine for treatment of stroke patients with cognitive dysfunction leads to significant improvement in clinical outcomes, and enhancement of cognitive function and quality of life, due to improved brain function in the precuneus. However, the mechanism involved in the combination therapy-induced enhancement of cognitive function requires further investigation. Keywords: Stroke; Cognitive dysfunction; Resting-state functional magnetic resonance imaging of brain; Regional homogeneity; Quality of life
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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) | 0.001 | 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".