Reducing the Effects of Ageing on Cognition with Therapeutic Intervention of an Oral Multi-Nutrient: The REACTION Pilot Trial Study Design
Bibliographic record
Abstract
BACKGROUND: Clinical benefits have been reported with a specific multinutrient intervention (Souvenaid) in Alzheimer's disease and mild cognitive impairment due to Alzheimer's disease. The effects of Souvenaid in age-related cognitive decline are not established. OBJECTIVE: To assess the feasibility of using virtual assessments to study the effects of a multinutrient on cognitive ageing. DESIGN: This is a randomized, double-blind, placebo-controlled, parallel group virtual pilot trial performed over 6 months in a single-centre. Participants are randomly allocated (1:1) to receive the specific multinutrient (Souvenaid) or an isocaloric, same tasting, placebo. SETTING: Trial visits are done virtually using secure online video communication. PARTICIPANTS: English or Spanish speaking people aged 55-89 years from all ethnic groups and considered to have age-related cognitive decline are eligible. MEASUREMENTS: Neuropyschological tests are done at baseline and after 6 months of intervention. Participants are contacted monthly by telephone to monitor safety, assess motivation and promote compliance. The primary outcome is feasibility determined by assessing recruitment rate, recruitment time, adherence rate and retention rate. A comprehensive set of neuropyschological measures will provide a broad assessment of cognitive function, including verbal memory, processing speed, and attention and executive function. Self-reported questionnaires are used to assess quality of life. CONCLUSIONS: This pilot trial will provide data to guide inform selection of participants and outcome measures in future studies in age-related cognitive decline.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".