Metrifonate Enhances the Ability of Alzheimer's Disease Patients to Initiate, Organize, and Execute Instrumental and Basic Activities of Daily Living
Bibliographic record
Abstract
The objective of this analysis was to evaluate comprehensively the efficacy of metrifonate, a long-acting acetylcholinesterase inhibitor, in improving the ability of mild-to-moderate Alzheimer's disease (AD) patients to perform activities of daily living (ADLs). Alzheimer's disease patients with Mini-Mental State Examination scores of 10 to 26 were enrolled in three 26-week trials to receive once-daily placebo (n = 430) or metrifonate 30 to 60 mg (by weight, n = 650) or 60/80 mg (by weight, n = 197). Metrifonate efficacy was assessed using the Disability Assessment for Dementia scale. Data from the three studies were pooled and analyzed retrospectively. The intent-to-treat analysis (last observation carried forward) at 26 weeks demonstrated that metrifonate significantly improved the ability of AD patients to perform ADLs when compared with placebo (30-60 mg dose, delta = 3.03; P = .002; 60/80 mg dose, delta = 5.25; P = .0002). Metrifonate significantly improved the ability of the AD patients to perform instrumental ADLs, those abilities typically lost first during the disease process (30-60 mg dose, delta = 3.88, P = .002; 60/80 mg dose, delta = 5.79, P = .003). Metrifonate also tended to improve, relative to placebo, the ability of AD patients to use three levels of executive skills when performing ADLs: initiation (30-60 mg dose, delta = 3.45, P = .001; 60/80 mg dose, delta = 5.44, P = .003), planning/organization (30-60 mg dose, delta = 4.50, P = .004; 60/80 mg dose, delta = 4.89, P = .014), and effective execution (30-60 mg dose, delta = 1.80, P = .076; 60/80 mg dose, delta = 4.06, P = .030). These results indicate that metrifonate has a beneficial effect on the ADLs in mild-to-moderate AD patients.
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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".