Hypothesis 4. Depression is associated with other physical precipitants of heart disease.
Bibliographic record
Abstract
Lesperance F, Frasure-Smith N, Theroux P, Irwin M: The association between major depression and levels of soluble intercellular adhesion molecule 1, interleukin-6, and C-reactive protein in patients with recent acute coronary syndromes. Am J Psychiatry 161:271–277, 2004 Investigators are avidly seeking pathophysiological (or biological) links between depression and coronary heart disease (CHD). Such data would further the status of depression as a modifiable CHD risk factor. In this study, Lesperance et al. determined whether depressed patients with established CHD have higher levels of inflammatory markers following an acute coronary event when judged against comparable nondepressed patients. The development of thrombi from an atherosclerotic plaque leads to a release of cytokines (including interleukin-6 [IL-6]), elevation of serum proteins known as acute-phase reactants (such as C-reactive protein), and the expression and endothelial shedding of soluble intercellular adhesion molecules (such as sICAM-1). These markers tend to be elevated following an acute coronary event, and higher levels predict a worse prognosis.36 The authors wondered whether depression further elevates these markers in patients with recent acute coronary syndromes, thereby increasing the risk for subsequent cardiac events and cardiac-related mortality. Four hundred eighty-one patients from the Montreal Heart Institute referred for a coronary angiogram following a myocardial infarction (MI) or because of unstable angina were assessed for depression. The patients then provided blood samples for measurement of IL-6, sICAM-1, and C-reactive protein. sICAM-1, but not IL-6 or C-reactive protein, was found to differ between depressed and nondepressed patients. The results suggested to the authors that, in patients with a recent acute coronary syndrome, depression is associated with higher degrees of endothelial dysfunction. This relationship remained …
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.002 |
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".