Resistance exercise for optimizing cognitive function during aging: the role of individual characteristics
Bibliographic record
Abstract
Physical exercise has emerged as one of the leading non-pharmaceutical approaches to delay cognitive decline. However, the limited understanding of the mechanisms by which exercise impacts cognition and the poor description of exercise programs in late adulthood hinder the widespread use of exercise as a therapeutic or preventive approach for Alzheimer's Disease (AD), with resistance exercise (RE) being one of the understudied types of exercise. Despite their potential significance, few studies with well-characterized samples and comprehensive cognitive assessments have attempted to understand the role of key demographics and clinical variables on the effect of resistance exercise on cognition. The AGUEDA trial aims to uncover the effects of a 24-week RE intervention on cognitive performance, depending on individual participant's characteristics. The AGUEDA trial is a single-site, two-arm, single-blinded, randomized controlled trial involving 90 cognitively normal older adults (71.75 ± 3.96 years, 57% female) from Spain. Participants were randomized to a RE group (n = 46) or control group (n = 44). The exercise group performed 180 minutes/week of supervised elastic band and body weight resistance exercises for 24 weeks, while controls maintained usual activities. High adherence was observed, and no serious adverse events occurred. During this talk, we will share promising findings on the impact of exercise on executive function and cognitive subdomains such as attentional/inhibitory control, episodic memory, processing speed, visuospatial memory and working memory, with a focus on optimizing the effect based on individual participant's characteristics. Demographics and key clinical characteristics such as sex, age, education level, number of comorbidities, apolipoprotein E carrier, Amyloid burden, baseline cognitive performance of each cognitive outcome and subjective cognitive decline are explored as potential moderators of the exercise's impact on cognition. Additional mechanisms related to physical parameters are also explored as potential mediators of cognitive changes. This research demonstrates the selective potential of RE as a powerful tool in the new era of precision interventions targeting specific AD-related cognitive decline. It also provides valuable insights into optimizing benefits based on patient characteristics, necessitating a thorough exploration of the optimal types and doses of exercise before advancing to comprehensive interventions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".