Clinical efficacy and safety of nicergoline combined with oxiracetam in the treatment of vascular cognitive impairment.
Bibliographic record
Abstract
As a α1-adrenergic receptor antagonist, nicergoline can induce vasodilation and increase arterial blood flow. Its clinical application can effectively prevent and treat cognitive impairment and reduce cognitive decline and comprehensively improve patients' daily living ability and social function. The clinical efficacy of nicergoline combined with oxiracetam in the treatment of vascular cognitive impairment after stroke was analyzed. 120 patients with cognitive impairment after stroke were randomly divided into nicergoline group and Experience group. They were treated with nicergoline and nicergoline combined with oxiracetam respectively. Both groups were treated for one month. Montreal Cognitive Assessment Scale (MoCA) was used to evaluate the cognitive function of the two groups before and after treatment, and the clinical efficacy was compared. The results showed that the average score of MoCA in the combined group was (5.97±2.06), higher than that in the nicergoline group (3.53±1.44). The change of MoCA score was the most significant. There was significant difference between the nicergoline group and the combined group (t=4.21, P<0.01). The combined group had the highest effective rate and the total effective rate was 93.3%. Conclusion: Nicergoline and oxiracetam are effective drugs in the treatment of vascular cognitive impairment (VCI). The combined use of nicergoline and oxiracetam is better than that of nicergoline alone. The combined use of nicergoline and oxiracetam can significantly improve the severity of symptoms and quality of life in patients with vascular cognitive impairment after stroke. The clinical effect is definite.
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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 | 0.001 |
| 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 | 0.001 |
| 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".