Psychological Distress and the Risk of Adverse Cardiovascular Outcomes in Patients With Coronary Heart Disease
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.000 | 0.001 |
| 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 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".