Association Between Cardiorespiratory Fitness and Trend of Age-Related Rise in Arterial Stiffness in Individuals With and Without Hypertension or Diabetes
Bibliographic record
Abstract
BACKGROUND: This study aimed to investigate whether higher cardiorespiratory fitness (CRF) can modify the trend of age-related rise in arterial stiffness in individuals with and without hypertension (HTN) or diabetes. METHODS: The study included 4,935 participants who underwent maximal cardiopulmonary exercise testing with respiratory gas analysis in a health screening program. CRF was directly measured using peak oxygen uptake during the cardiopulmonary exercise test, while arterial stiffness was evaluated using brachial-ankle pulse wave velocity (baPWV). RESULTS: Participants with high CRF levels had significantly lower baPWV compared with those with low CRF levels, regardless of HTN or diabetes status (P < 0.05). The trend of baPWV increased with age, but the rate of age-related increase in baPWV was lower in individuals with moderate-to-high CRF levels compared with those with low CRF levels, regardless of HTN or diabetes status. Joint association analysis indicated that the trend of age-related increase in baPWV was the lowest in fit individuals without HTN or diabetes compared with unfit individuals with HTN or diabetes (P < 0.01). However, the trend of age-related increase in baPWV was not attenuated in fit with HTN or diabetes compared with unfit with HTN or diabetes. CONCLUSIONS: These findings suggest that higher CRF levels may mitigate the trend of age-related rise in arterial stiffness in individuals with and without HTN or diabetes. However, this attenuating trend appears more pronounced in individuals without HTN or diabetes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".