Effects of high-velocity circuit resistance and treadmill training on cardiometabolic risk, blood markers, and quality of life in older adults
Bibliographic record
Abstract
The presence of cardiometabolic syndrome (CMS) confers an increased risk for cardiovascular disease (CVD) and mortality and is associated with reduced health-related quality of life (HRQoL). Although the effects of exercise on biomarkers, HRQoL, and future risk have been studied, no study has measured the effects on all three components. The present study compared the effects of steady-state, moderate-intensity treadmill training (TM) and high-velocity circuit resistance training (HVCRT) on biological markers, HRQoL, and overall CVD risk in adults with CMS and CVD risk factors. Thirty participants (22 females, 8 males) were randomly assigned to 1 of 3 groups: HVCRT, TM, or control. Participants in the exercise groups attended training 3 days/week for a total of 12 weeks. Of the 30 participants who began the study, 24 (19 females, 5 males) were included in the final analysis. Primary outcome measures included CMS criteria, hemodynamic measures, Framingham Risk Score (FRS), and HRQoL. All variables were measured pre- and post-intervention. CMS z score significantly decreased for HVCRT (p = 0.03), while there were no significant changes for TM or control. FRS significantly decreased for HVCRT compared with TM (p = 0.03) and control (p = 0.03). Significant decreases in systolic (p < 0.01) and diastolic blood pressures (p < 0.01) for HVCRT accompanied significant increases from baseline in stroke volume (p = 0.03) and end-diastolic volume (p < 0.01). Systemic vascular resistance significantly decreased (p = 0.05) for HVCRT compared with control. Emotional well-being significantly improved following HVCRT and TM compared with control (p = 0.04; p = 0.03). HVCRT represents a novel training modality that improved factors in each of the 3 components assessed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".