Clinical Impact of Subsequent Depression in Patients With a New Diagnosis of Stable Angina
Bibliographic record
Abstract
BACKGROUND: Depression is prevalent among patients with myocardial infarction and is associated with a worse prognosis. However, little is known about its importance in patients with chronic stable angina. We conducted a retrospective population-based cohort study to determine the occurrence and predictors of developing depression in patients with a new diagnosis of chronic stable angina. In addition, we sought to understand its impact on subsequent clinical outcomes. METHODS AND RESULTS: Our cohort included patients in Ontario, Canada, with stable angina based on obstructive coronary artery disease found on angiogram. Depression was ascertained by physician billing codes and hospital admissions diagnostic codes. We first developed multivariable Cox proportional hazards models to determine predictors of developing depression. Clinical outcomes of interest included all-cause mortality, admission for myocardial infarction, and subsequent revascularization. Using hierarchical multivariable Cox proportional hazards models with occurrence of depression as a time-varying variable to control for potential immortal time bias, we evaluated the impact of depression on clinical outcomes. Our cohort consisted of 22 917 patients. The occurrence of depression after diagnosis of stable chronic angina was 18.8% over a mean follow-up of 1084 days. Predictors of depression included remote history of depression, female sex, and more symptomatic angina based on Canadian Cardiovascular Society class. Patients who developed depression had a higher risk of death (hazard ratio 1.83, 95% confidence interval 1.62-2.07) and admission for myocardial infarction (hazard ratio 1.36, 95% confidence interval 1.10-1.67) compared with nondepressed patients. CONCLUSIONS: Depression is common in patients with chronic stable angina and is associated with increased morbidity and mortality.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".