Pathophysiology and prevention of sudden cardiac death
Bibliographic record
Abstract
Sudden cardiac death (SCD) is known to occur in individuals with diverse diseases. Each disease state has a specific etiology and pathophysiology, and is diagnosed and treated differently. Etiologies for SCD include cardiac arrhythmias, coronary artery disease, congenital coronary artery anomalies, hypertrophic cardiomyopathy, arrhythmogenic right ventricular dysplasia, dilated cardiomyopathy, and aortic valve stenosis. A potential unifying mechanism of SCD in these diseases involves a massive stimulation of the sympathetic nervous system's stress response and the subsequent elevation of circulating catecholamines. The diagnosis of cardiac diseases that contribute to an increased risk for SCD is accomplished by a combination of different techniques including electrocardiography, echocardiography, magnetic resonance imaging, and invasive cardiac catheterization. Several therapies including anti-arrhythmic drugs, β-blockers, and antiplatelet agents may be used as medical treatment in patients for the prevention of SCD. Invasive therapies including percutaneous angioplasty, coronary artery bypass surgery, and implantable cardioverter-defibrillators are also used in the clinical management of SCD.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".