Future Development of Arrhythmogenic Risk Scores in Patients with Heart Failure and Inherited Dilated Cardiomyopathy. A Scientific Statement of the Heart Failure Association of the ESC
Bibliographic record
Abstract
The risk of sudden cardiac death (SCD) in the general population of patients with dilated cardiomyopathy (DCM) has progressively declined with the implementation of novel medical strategies. However, still cases occur in young individuals and the challenge of risk stratification remains unsolved. Traditional criteria, including left ventricular ejection fraction, have demonstrated their profound weakness to identify subjects at high risk of SCD in this specific context. The increasing availability of genetic information has allowed identification of certain genotypes with a high arrhythmic risk that deserve a more individualized approach. Recent European guidelines recognized the contribution of genetic information in clinical decision-making. Gene-specific risk stratification tools have been developed, and in some cases externally validated, which can support clinicians in the decisions on SCD primary prevention interventions. However, they are generally based on basic variables, whereas the growing amount of knowledge on novel methods for risk prediction, and in particular the solid data on the predictive value of cardiac magnetic resonance tissue characterization (i.e. late gadolinium enhancement) are not incorporated in available scores, and more in general, are not systematically part of the clinical work-up. In this scientific statement, we summarized the current state of the art concerning the risk stratification of SCD in DCM, with particular emphasis on genetic forms, highlight the weaknesses of the available strategies and the potential actions needed for improving them. Available risk stratification tools are discussed, and methodologies that should be incorporated in future prognostication models are summarized. Lastly, a point-by-point summary of the key prerequisites for developing the future arrhythmogenic risk scores in patients with DCM is provided.
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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 | 0.009 | 0.016 |
| 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".