Observed clinical efficacy in the joint treatment of memantine and aricept for the mental and behavioral symptoms of alzheimer's disease
Bibliographic record
Abstract
Objective To investigate the therapeutic effect of combination of memantine and donepezil on cognitive mental symptoms in patients with Alzheimer's disease. Methods Seventy cases elderly patients with Alzheimer's disease were randomly divided into two groups, memantine and donepezil group(treatment group) with 35 cases, donepezil hydrochloride and olanzapine group(control group) with 35 cases.Scoring in before treatment and 6, 12 weeks after treatment in application of rosa linked to Alzheimer's disease(ROSA) and the neuropsychiatric Inventory(NPI) assessment, montreal cognitive assessment scale(MoCA scale) were assessed. Results ROSA scores in before treatment and 6, 12 weeks after treatment of treatment group and control group was (75.14±17.20) points and (73.97±17.29) points, (89.77±17.14) points and (80.84±15.31) points, (100.30±14.47) points and (89.31±13.30) points, there were statistically significant differences before treatment between the two groups(P 0.05). Conclusion The combined treatment of memantine and donepezil in Alzheimer's disease can improve cognitive function and mental symptoms, communication, etc.The effect of agitation or attack than the control group is significantly different. Key words: Alzheimer’s disease; Memantine; Aricept; Relevant Outcome Scale for Alzheimer's Disease
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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 | 0.000 |
| 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) | 0.003 | 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".