Incidence, Risk Assessment and Prevention of Sudden Cardiac Death in Cardiomyopathies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Cardiomyopathies are a significant contributor to cardiovascular morbidity and mortality, mainly due to the development of heart failure and increased risk of sudden cardiac death (SCD). Despite improvement in survival with contemporary treatment, SCD remains an important cause of mortality in cardiomyopathies. It occurs at a rate ranging between 0.15% and 0.7% per year (depending on the cardiomyopathy), which significantly surpasses SCD incidence in the age- and sex-matched general population. The risk of SCD is affected by multiple factors including the aetiology, genetic basis, age, sex, physical exertion, the extent of myocardial disease severity, conduction system abnormalities, and electrical instability, as measured by various metrics. Over the past decades, the knowledge on the mechanisms and risk factors for SCD has substantially improved, allowing for a better-informed risk stratification. However, unresolved issues still challenge the guidance of SCD prevention in patients with cardiomyopathies. In this review, we aim to provide an in-depth discussion of the contemporary concepts pertinent to understanding the burden, risk assessment and prevention of SCD in cardiomyopathies (dilated, non-dilated left ventricular, hypertrophic, arrhythmogenic right ventricular, and restrictive). The review first focuses on SCD incidence in cardiomyopathies and then summarizes established and emerging risk factors for life-threatening arrhythmias/SCD. Finally, it discusses validated approaches to the risk assessment and evidence-based measures for SCD prevention in cardiomyopathies, pointing to the gaps in evidence and areas of uncertainties that merit future clarification.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it