Antidepressant Use by Class: Association with Major Adverse Cardiac Events in Patients with Coronary Artery Disease
Bibliographic record
Abstract
BACKGROUND: To assess use of antidepressants by class in relation to cardiology practice recommendations, and the association of antidepressant use with the occurrence of major adverse cardiovascular events (MACE) including death. METHODS: This is a historical cohort study of all patients who completed cardiac rehabilitation (CR) between 2002 and 2012 in a major CR center. Participants completed the Patient Health Questionnaire (PHQ-9) at the start and end of the program. A linkage system enabled ascertainment of antidepressant use and MACE through 2014. RESULTS: There were 1,694 CR participants, 1,266 (74.7%) of whom completed the PHQ-9 after the program. Depressive symptoms decreased significantly from pre- (4.98 ± 5.20) to postprogram (3.57 ± 4.43) (p < 0.001). Overall, 433 (34.2%) participants were on antidepressants, most often selective serotonin reuptake inhibitors (SSRI; n = 299; 23.6%). The proportion of days covered was approximately 70% for all 4 major antidepressant classes; discontinuation rates ranged from 37.3% for tricyclics to 53.2% for serotonin-norepinephrine reuptake inhibitors (SNRI). Antidepressant use was significantly associated with lower depressive symptoms after CR (before, 7.33 ± 5.94 vs. after, 4.69 ± 4.87; p < 0.001). After a median follow-up of 4.7 years, 264 (20.9%) participants had a MACE. After propensity matching based on pre-CR depressive symptoms among other variables, participants taking tricyclics had significantly more MACE than those not taking tricyclics (HR = 2.46; 95% CI 1.37-4.42), as well as those taking atypicals versus not (HR = 1.59; 95% CI 1.05-2.41) and those on SSRI (HR = 1.45; 95% CI 1.07-1.97). There was no increased risk with use of SNRI (HR = 0.89; 95% CI 0.43-1.82). CONCLUSION: The use of antidepressants was associated with lower depression, but the use of all antidepressants except SNRI was associated with more adverse events.
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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 | 0.000 | 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 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".