Precision Recommendations to Optimize Neurocognition [PREVENTION] Trial: Preliminary Results
Bibliographic record
Abstract
Abstract Background Alzheimer’s disease (AD) is a complex neurodegenerative condition that requires a comprehensive treatment approach. In addition to pharmacologic treatment, managing existing medical conditions and incorporating lifestyle modifications, such as diet, cognitive training, and exercise, are potentially crucial components of an effective intervention. In this study, we present preliminary results of a personalized multi‐modal intervention for AD. Methods The Precision Recommendations to Optimize Neurocognition (PREVENTION) study is an ongoing 12‐month randomized clinical trial. Fifty participants (mean age 71.9(SD = 7.2); 24 Female) with biomarker evidence of AD amyloidosis have been recruited. While both arms receive personalized data‐driven, lifestyle recommendations designed to target multiple systemic pathways implicated in AD, the active arm also receives health coaching, dietary counseling, exercise training, cognitive stimulation, and nutritional supplements. Comprehensive clinical, cognitive, neuroimaging, and genetic data are collected at baseline, and post‐intervention. Herein, we examined the effects of the intervention on global cognition (MoCA) and regional brain volumes using general linear mixed models and compare to literature values (or historical controls). Results Participants in the two groups (23 active; 27 control) did not differ significantly in demographic, cognitive, or brain imaging measures at baseline. Thirty‐one participants (16 active; 15 control) have completed the study. Within‐group 12‐month changes in MoCA (active:‐1.4(3.5); control:‐1.7(3.6)) were not significant, did not differ significantly between groups and were borderline (p = .08) less than expected rate of decline. While both groups declined significantly in hippocampal volumes, percent changes in total gray matter, entorhinal cortex, and precuneus volumes were significantly less in the active arm (Table). Conclusion In this preliminary analysis of an active multimodal lifestyle intervention paired with personalized health optimization, regional volume loss in certain key areas of interest in AD was significantly lower in the active arm compared to control; further, the decline in global cognition was not statistically significant and was attenuated for the entire cohort compared to literature values. These preliminary results in a relatively small cohort suggest the intervention may beneficially impact cognition, memory, and brain structure. Future analyses will focus on elucidating changes in the biological systems being targeted by the intervention to help uncover the underlying mechanisms.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".