A Comprehensive, Multi-Modal Strategy to Mitigate Alzheimer’s Disease Risk Factors Improves Aspects of Metabolism and Offsets Cognitive Decline in Individuals with Cognitive Impairment
Bibliographic record
Abstract
BACKGROUND: Alzheimer's disease (AD) is a chronic condition that progresses over time. While several therapeutic approaches have been developed, none have substantially altered disease progression. One explanation is that the disease is multi factorial. OBJECTIVE: Using the Affirmativ Health Personal Therapeutic Program (PTPr), we sought to determine whether a comprehensive and personalized program could improve cognitive and metabolic function in individuals diagnosed with subjective cognitive impairment, mild cognitive impairment, and early stage AD. METHODS: 35 individuals submitted blood samples and Montreal Cognitive Assessment (MoCA) scores, and answered intake questions. Individuals and caregivers participated in a four-day immersion program, which included Personal Therapeutic Plans (PTP), consultations with clinical practitioners, and explanations of the PTPr and PTP. Participants had follow-up by telemonitoring, with repeat blood sample analysis, updates regarding lifestyle choices, current medications and supplements, and MoCA testing at least once between 3 and 12 months after the PTPr. RESULTS: By comparing baseline to follow-up testing, we determined several risk factor scores, including blood glucose and insulin levels, and levels of vitamins B12, D3, and E, improved either in the entire participant pool or specifically in individuals with measures outside the normal range for specific factors. MoCA scores were stabilized in the entire participant pool and significantly improved in individuals scoring 24 or less at baseline. CONCLUSION: Our findings provide evidence that a comprehensive and personalized approach designed to mitigate AD risk factors can improve risk factor scores and stabilize cognitive function, warranting more extensive and placebo-controlled clinical studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".