Longitudinal Course of Depressive Symptomatology After a Cardiac Event: Effects of Gender and Cardiac Rehabilitation
Bibliographic record
Abstract
OBJECTIVE: Recent research has linked depression to cardiac mortality, and shown a high burden of persistent depressive symptomatology among cardiac patients. The objective of this study was to longitudinally examine the prevalence and course of depressive symptomatology among women and men for 1 year after a cardiac event, and the effect of cardiac rehabilitation (CR) on this trajectory. METHODS: Nine hundred thirteen unstable angina (UA) and myocardial infarction patients from 12 coronary care units were recruited, and follow-up data were collected at 6 and 12 months. Measures included CR participation, medication usage, and the Beck Depression Inventory (BDI). The longitudinal analysis was conducted using SAS PROC MIXED. RESULTS: At baseline there were 277 (31.3%) participants with elevated depressive symptomatology (BDI > or = 10), 131 (25.2%) at 6 months, and 107 (21.7%) at 1 year. Overall, approximately 5% were taking an antidepressant medication, and 20% attended CR over their year of recovery. Participants with greater depressive symptomatology participated in significantly fewer CR exercise sessions (r = -0.19, p = .02), and minimal psychosocial interventions were offered. The longitudinal analysis revealed that all participants experienced reduced depressive symptomatology over their year of recovery (p = .04), and younger, UA participants with lower family income fared worst (ps < 0.001). CR did not have an effect on depressive symptomatology over time, but women who attended CR were significantly more depressed than men (p = .01). CONCLUSION: Depressed cardiac patients are undertreated and their symptomatology persists for up to 6 months. CR programs require greater resources to ensure that depressed participants adhere to exercise regimens, and are screened and treated for their elevated symptomatology.
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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 | 0.002 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".