A Comparison of Accelerometer Cut-Points among Individuals with Coronary Artery Disease
Bibliographic record
Abstract
BACKGROUND: Accurate assessment of physical activity among coronary artery disease patients is important for assessing adherence to interventions. The study compared moderate-to-vigorous physical intensity activity and relationships with cardiometabolic health/fitness indicators using accelerometer cut-points developed for coronary artery disease patients versus those developed in younger and middle-aged adults. METHODS: A total of 231 adults with coronary artery disease wore an Actigraph GT3X accelerometer for ≥4 days (≥10 hours/day). Moderate-to-vigorous intensity physical activity between cut-points was compared using Bland-Altman analyses. Partial spearman correlations assessed relationships between moderate-to-vigorous intensity physical activity from each cut-point with markers of cardiometabolic health and fitness while controlling for age and sex. RESULTS: Average time spent in bouts of moderate-to-vigorous intensity physical activity using coronary artery disease cut-points was significantly higher than the young (mean difference: 13.0±12.8 minutes/day) or middle-aged (17.0±15.2 minutes/day) cut-points. Young and middle-aged cut-points were more strongly correlated with body mass index, waist circumference and systolic blood pressure, while coronary artery disease cut-points had stronger relationships with triglycerides, high-density and low-density lipoproteins. All were similarly correlated with measures of fitness. CONCLUSION: Researchers need to exert caution when deciding on which cut-points to apply to their population. Further work is needed to validate which cut-points provide a true reflection of moderate-to-vigorous intensity physical activity and to examine relationships among patients with varying fitness.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".