Psychological Distress and the Risk of Adverse Cardiovascular Outcomes in Patients With Coronary Heart Disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Psychological distress is a recognized risk factor in patients with coronary heart disease (CHD), but its clinical significance is unclear. OBJECTIVES: The purpose of this study was to determine if an index of psychological distress is independently associated with adverse outcomes and significantly contributes to risk prediction. METHODS: Pooled analysis of 2 prospective cohort studies of patients with stable CHD (N = 891). A psychological distress score was constructed using measures of depression, anxiety, anger, perceived stress, and post-traumatic stress disorder, measured at baseline. The study endpoint included cardiovascular death or first or recurrent nonfatal myocardial infarction or hospitalization for heart failure at 5.9 years. RESULTS: In both cohorts, first and recurrent events occurred more often among those in the highest tertile of distress score than those in the lowest tertile. After combining the 2 cohorts, compared with the lowest tertile, the hazards ratio for having a distress score in the highest tertile was 2.27 (95% CI: 1.69-3.06), and for the middle tertile, it was 1.52 (95% CI: 1.10-2.08). Adjustment for demographics and clinical risk factors only slightly weakened the associations. When the distress score was added to a traditional clinical risk model, C-statistic, net reclassification index, and integrative discrimination index all significantly improved. CONCLUSIONS: Among patients with CHD, a composite measure of psychological distress was significantly associated with an increased risk of adverse events and significantly improved risk prediction.
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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) | 0.000 | 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) | 0.000 | 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 it