The risk and prevention of sudden death in patients with heart failure with reduced ejection fraction
Bibliographic record
Abstract
PURPOSE OF REVIEW: Patients with heart failure are at increased risk of sudden cardiac death. The methods to predict patients at high risk of sudden cardiac death in heart failure are neither sensitive nor specific; both overestimating risk in those with ejection fractions less than 35% and not identifying those at risk with ejection fractions greater than 35%. RECENT FINDINGS: The absolute risk of sudden cardiac death in patients with heart failure have decreased over the past 20 years. New novel tools are being developed and tested to identify those at higher risk of sudden cardiac death. Reduction in the risk of sudden cardiac death has been achieved with the use of beta-blockers, spironolactone, sacubitril-valsartan, cardiac resynchronization and implantable cardioverter defibrillators. SUMMARY: The use of contemporary treatments for patients with heart failure can reduce the risk of sudden cardiac death, but research is required to identify those at highest risk.
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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 | 0.000 |
| 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".