P4‐070: A PROGRAM OF PRE‐SYMPTOMATIC EVALUATION OF EXPERIMENTAL OR NOVEL TREATMENTS FOR ALZHEIMER'S DISEASE (PREVENT‐AD): DESIGN, METHODS, AND PERSPECTIVES
Bibliographic record
Abstract
Brain changes in Alzheimer's disease (AD) occur decades before appearance of the first symptoms of dementia. This pre-symptomatic stage of AD presents an opportunity to test interventions that can slow the disease process and thereby delay the onset of dementia. Efficiency of this work is enhanced by enrolling persons who have a first-degree relative with AD dementia.We describe a program in such subjects designed to test whether specific interventions will likely delay dementia onset. Our new Centre for Studies on Prevention of AD (StoP-AD) is assembling such a high-risk cohort and testing effects of potential prevention strategies in pre-symptomatic individuals. The Centre's first intervention trial will examine the effects of the nonsteroidal anti-inflammatory drug naproxen over two years. Endpoints include neuropsychological measures, sensory faculties (olfaction / central auditory processing), classic AD biomarkers in cerebrospinal fluid (CSF), and structural and functional magnetic resonance imaging (MRI). To date, we have evaluated 361 people for eligibility, enrolling 192. Of these, 118 are in the naproxen trial while 74 others undergo annual observations pending possible enrollment in future trials. APOE, BDNF, HMGR Intron M and BChE K genotypes have been determined for 177 participants. Some 40% of those enrolled in the naproxen trial have agreed to a series of four lumbar punctures (LPs), and 100 LPs have been assayed to data for concentrations of total tau, P-tau, Aβ1-40 and A β 1-42. MRI and fMRI modalities include fine structural analysis, regional volumes, resting state connectivity, regional cerebral blood flow (ASL), white matter pathology and task-based fMRI. Data are managed using an adaptation of the LORIS database. Early analyses of baseline data suggest that many of the endpoints correlate with age and, more importantly, with one-another (suggesting a common underlying driver or drivers independent of age). We offer the first description of a new Centre's study design and progress to date. A second trial, now in planning, will evaluate effects of an inducer of synthesis of the cholesterol transport protein apoE, which promotes neural regeneration and repair.
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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 | 0.016 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".