Influence of Physical Activity on Mortality in Elderly with Coronary Artery Disease
Bibliographic record
Abstract
PURPOSE: The primary objectives were to 1) examine the dose-response relationship between physical activity and mortality in individuals with CAD, and 2) determine whether the aforementioned relationship is consistent within strata of other personal characteristics. METHODS: Subjects included 1045 elderly men and women with CAD from the Cardiovascular Health Study. In the first set of analyses, the dose-response relationship between baseline leisure-time physical activity level and all-cause mortality risk over 9 yr was determined using Cox proportional hazards regression models. Next, the subjects were stratified based on several different characteristics, and the consistency of the relationship between baseline leisure-time physical activity and mortality risk within the various strata was determined. RESULTS: Baseline leisure-time physical activity was related to all-cause mortality risk in a curvilinear dose-response manner such that greater differences in mortality risk were seen at the lower end of the energy expenditure scale, with a plateau occurring at approximately 4000 kcal x wk(-1). Within various strata of sex, age, smoking, adiposity, self-perceived health status, number of comorbid conditions, and type of CAD; the relative risks of mortality were lower in active participants (>/=1500 kcal x wk(-1)) in comparison with inactive participants (<1500 kcal x wk(-1)). CONCLUSION: This study highlights the inverse graded relationship between physical activity and all-cause mortality in men and women with CAD. Physical inactivity was a risk factor for mortality regardless of whether the subjects were men or women, old or very old, smokers or nonsmokers, lean or overweight, or otherwise healthy or unhealthy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".