Psychological Theories of Depression: Potential Application for the Prevention of Acute Coronary Syndrome Recurrence
Bibliographic record
Abstract
OBJECTIVE: The natural course of elevated depressive symptoms or subthreshold depression in patients with an acute coronary syndrome (ACS) is presented, as is the prognostic impact. Safe and effective psychological treatment options are desirable for subthreshold depression in patients with ACS, should they prove tolerable, efficacious, and cost-effective to cardiologists and their patients. To achieve this long-term goal, we propose focusing on 3 intermediate goals. First, we need to understand which symptoms or patterns of symptoms (eg, fatigue, anhedonia, guilt feelings) are specifically predictive of ACS recurrence. Second, the prevalence of known psychosocial vulnerabilities (proximal causes) of depressive disorders should be assessed in patients with ACS, to understand better the etiology of these symptoms in these patients. Third, randomized controlled trials of vulnerability-related, evidence-based psychological depression interventions in cardiac patients are needed. The ways in which psychological proximal cause theories are relevant--or irrelevant--for both the treatment of depressive symptoms in post-ACS patients and the prevention of ACS recurrence are discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".