Cardiorespiratory Fitness and Cognitive Function are Positively Related Among Participants with Mild and Subjective Cognitive Impairment
Bibliographic record
Abstract
BACKGROUND: By 2030, about 74 million people will be diagnosed with dementia, and many more will experience subjective (SCI) or mild cognitive impairment (MCI). As physical inactivity has been identified to be a strong modifiable risk factor for dementia, exercise and physical activity (PA) may be important parameters to predict the progression from MCI to dementia, but might also represent disease trajectory modifying strategies for SCI and MCI. OBJECTIVE: A better understanding of the relationship between activity, fitness, and cognitive function across the spectrum of MCI and SCI would provide an insight into the potential utility of PA and fitness as early markers, and treatment targets to prevent cognitive decline. METHODS: 121 participants were stratified into three groups, late MCI (LMCI), early MCI (EMCI), and SCI based on the Montreal Cognitive Assessment (MoCA). Cognitive function assessments also included the Trail Making Test A+B, and a verbal fluency test. PA levels were evaluated with an interviewer-administered questionnaire (LAPAQ) and an activity monitor. An incremental exercise test was performed to estimate cardiorespiratory fitness and to determine exercise capacity relative to population normative data. RESULTS: ANCOVA revealed that LMCI subjects had the lowest PA levels (LAPAQ, p = 0.018; activity monitor, p = 0.041), and the lowest exercise capacity in relation to normative values (p = 0.041). Moreover, a modest correlation between MoCA and cardiorespiratory fitness (r = 0.25; p < 0.05) was found. CONCLUSION: These findings suggest that during the earliest stages of cognitive impairment PA and exercise capacity might present a marker for the risk of further cognitive decline. This finding warrants further investigation using longitudinal cohort studies.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".