Recent Evidence Linking Coronary Heart Disease and Depression
Bibliographic record
Abstract
OBJECTIVES: To review the recent literature on the relation between depression and coronary heart disease (CHD), including both etiologic studies (that is, depression preceding development of CHD) and prognostic studies (that is, depression predicting prognosis in established CHD), and to assess the degree to which the literature supports a causal interpretation of the link between depression and CHD. METHOD: We searched the MEDLINE, Current Contents, and PsycINFO databases for articles published between December 15, 2003, and December 15, 2005, containing combinations of several key words related to CHD, prognosis, and depression. We reviewed papers for evidence of 6 rule-of-thumb criteria for making causal inferences: objective CHD outcome measures, prospective designs, results showing consistent and strong dose-response relations, adequate covariate adjustment, biological plausibility, and evidence from clinical trials that changing depression alters CHD risk. RESULTS: We found 8 recent etiologic studies, 16 prognostic studies, 2 publications with both types of data, and 23 review papers. Although there was much methodological variability concerning measurement of depression and assessment of cardiac outcomes, the recent etiologic studies increase the evidence of a role for depression. Recent prognostic data are less consistent. Small studies showing no link between depression and CHD prognosis continue to appear, despite lack of adequate statistical power. CONCLUSIONS: The recent literature continues to support both an etiologic and a prognostic role for depression in CHD. Despite this evidence, there have been few clinical trials of depression treatment in CHD patients and no clinical trials of depression prevention. Additional trials are needed.
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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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".