A simultaneous test of the relationship between identified psychosocial risk factors and recurrent events in coronary artery disease patients
Bibliographic record
Abstract
Psychosocial factors are increasingly recognized as risk indicators for coronary artery disease (CAD) prognosis and they are likely interrelated. The objective of this study is to simultaneously test the relationship between key psychosocial constructs as independent factor scores and recurrent events in CAD patients. There were 1268 CAD outpatients of 97 cardiologists surveyed at two points. Recurrent events or hospitalization in the intervening nine months were reported. Factor analysis of items from the Hospital Anxiety and Depression Scale, Perceived Stress Scale, the ENRICHD Social Support Inventory, and Hostile Attitudes Scale was performed to generate orthogonal factor scores. With adjustment for prognostic variables, logistic regression analysis was performed to examine the relationship between these factor scores and recurrent events. Factor analysis resulted in a six-factor solution: hostility, stress, anxiety, depressive symptoms, support, and resilience. Logistic regression revealed that functional status and anxiety, with a trend for depressive symptoms, were related to experiencing a recurrent event. In this simultaneous test of psychosocial constructs hypothesized to relate to cardiac prognosis, anxiety may be a particularly hazardous psychosocial factor. While replication is warranted, efforts to investigate the potential benefits of screening and to investigate treatments are needed.
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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 | 0.001 |
| 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".