Comparison on clinical efficacy between oxiracetam and piracetam in treatment of elderly cognitive dysfunction after cerebral hemorrhage
Bibliographic record
Abstract
Objective To compare the clinical efficacy and safety between oxiracetam and piracetam in the treatment of elderly cognitive dysfunction after cerebral hemorrhage. Methods Elderly cerebral hemorrhage patients(104 cases) who came to Zhongye Worker Hospital in Shanghai from February 2012 to December 2013 were randomly divided into control and treatment groups, and there were 52 cases in each group. The patients in the control group were po administered with Piracetam Tablets, 4 tablets/time, three times daily. The patients in the treatment group were po administered with Oxiracetam Capsules, 2 capsules/time, three times daily. The patients in the two groups were treated for 6 months. Cognitive function was assessed by Montreal cognitive assessment(MoCA) scale, minimum mental state examination(MMSE) activities and daily living(ADL) before and after the treatment. Results After the treatment, project scores of MoCA and MMSE scales were significantly improved, and the difference was statistically significant before and after the treatment in the same group(P 0.05). After the treatment, the executive function and calculation scores of MoCA scale in the treatment group were higher than those in the control group, while immediate recall force, computing power, language ability, and total scores of MMSE scale were higher than those in the control group, and there were differences between the two groups(P 0.05). There was no difference on the incidence of adverse drug reactions(ADR) between the two groups. Conclusion Compared with piracetam, oxiracetam can effectively improve the cognitive dysfunction of elderly patients after cerebral hemorrhage, and have good clinical efficacy and safety with less ADR.
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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 | 0.001 | 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 | 0.000 |
| 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".