Self‐Reported Health and Outcomes in Patients With Stable Coronary Heart Disease
Bibliographic record
Abstract
Background The major determinants and prognostic importance of self‐reported health in patients with stable coronary heart disease are uncertain. Methods and Results The STABILITY (Stabilization of Atherosclerotic Plaque by Initiation of Darapladib Therapy) trial randomized 15 828 patients with stable coronary heart disease to treatment with darapladib or placebo. At baseline, 98% of participants completed a questionnaire that included the question, “Overall, how do you feel your general health is now?” Possible responses were excellent, very good, good, average , and poor . Adjudicated major adverse cardiac events, which included cardiovascular death, myocardial infarction, and stroke, were evaluated by Cox regression during 3.7 years of follow‐up for participants who reported excellent or very good health (n=2304), good health (n=6863), and average or poor health (n=6361), before and after adjusting for 38 covariates. Self‐reported health was most strongly associated with geographic region, depressive symptoms, and low physical activity ( P <0.0001 for all). Poor/average compared with very good/excellent self‐reported health was independently associated with major adverse cardiac events (hazard ratio [ HR ]: 2.30 [95% confidence interval ( CI ), 1.92–2.76]; adjusted HR : 1.83 [95% CI , 1.51–2.22]), cardiovascular mortality ( HR : 4.36 [95% CI , 3.09–6.16]; adjusted HR : 2.15 [95% CI , 1.45–3.19]), and myocardial infarction ( HR : 1.87 [95% CI , 1.46–2.39]; adjusted HR : 1.68 [95% CI , 1.25–2.27]; P <0.0002 for all). Conclusions Self‐reported health is strongly associated with geographical region, mood, and physical activity. In a global coronary heart disease population, self‐reported health was independently associated with major cardiovascular events and mortality beyond what is measurable by established risk indicators. Clinical Trial Registration URL : http://www.ClinicalTrials.gov . Unique identifier: NCT 00799903.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".