Depression and 1-Year Prognosis in Unstable Angina
Bibliographic record
Abstract
BACKGROUND: Depression is common after acute myocardial infarction and is associated with an increased risk of mortality for at least 18 months. The prevalence and prognostic impact of depression in patients with unstable angina, who account for a substantial portion of acute coronary syndrome admissions, have not been examined. METHODS: Interviews were carried out in hospital with 430 patients with unstable angina who did not require coronary artery bypass surgery before hospital discharge. Depression was assessed using the 21-item self-report Beck Depression Inventory and was defined as a score of 10 or higher. The primary outcome was 1-year cardiac death or nonfatal myocardial infarction. RESULTS: The Beck Depression Inventory identified depression in 41.4% of patients. Depressed patients were more likely to experience cardiac death or nonfatal myocardial infarction than other patients (odds ratio, 4.68; 95% confidence interval, 1.94-11.27; P<.001). The impact of depression remained after controlling for other significant prognostic factors, including baseline electrocardiographic evidence of ischemia, left ventricular ejection fraction, and the number of diseased coronary vessels (adjusted odds ratio, 6.73; 95% confidence interval, 2.43-18.64; P<.001). CONCLUSIONS: Depression is common following an episode of unstable angina and is associated with an increased risk of major cardiac events during the following year.
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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 | 0.001 |
| 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".