Observed Improvement in Cognition During a Personalized Lifestyle Intervention in People with Cognitive Decline
Bibliographic record
Abstract
BACKGROUND: Alzheimer's disease (AD) is a chronic condition marked by progressive objective cognitive impairment (OCI). No monotherapy has substantially altered disease progression, suggesting the disease is multifactorial and may require a multimodal therapeutic approach. OBJECTIVE: We sought to determine if cognitive function in a sample with OCI would change in response to a multimodal, individualized care plan based on potential contributors to cognitive decline (e.g., nutritional status, infection, etc.). METHODS: Participants (n = 34) were recruited from the San Diego, CA area. The multimodal intervention included lifestyle changes (i.e., movement, diet, and stress management), nutraceutical support, and medications. It was delivered pragmatically over four clinical visits, and outcome measures were gathered at four study visits, occurring at baseline, one, three, and six months (primary endpoint). Study participants received weekly phone calls for nutrition support throughout study participation. Outcome measures included the Cambridge Brain Sciences (CBS) battery, and the Montreal Cognitive Assessment (MoCA). RESULTS: At 6 months, mean MoCA scores improved from 19.6±3.1 to 21.7±6.2 (p = 0.013). Significant improvement was observed in mean scores of the CBS memory domain [25.2 (SD 23.3) to 35.8 (SD 26.9); p < 0.01] and CBS overall composite cognition score [24.5 (SD 16.1) to 29.7 (SD 20.5); p = 0.02]. All CBS domains improved. CONCLUSION: Multiple measures of cognitive function improved after six months of intervention. Our results support the feasibility and impact of a multimodal, individualized treatment approach to OCI, warranting further research.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".