European recommendations integrating genetic testing into multidisciplinary management of sudden cardiac death
Bibliographic record
Abstract
Sudden cardiac death (SCD) accounts for 10-20% of total mortality, i.e., one in five individuals will eventually die suddenly. Given the substantial genetic component of SCD in younger cases, postmortem genetic testing may be particularly useful in elucidating etiological factors in the cause of death in this subset. The identification of genes responsible for inherited cardiac diseases have led to the organization of cardiogenetic consultations in many countries worldwide. Expert recommendations are available, emphasizing the importance of genetic testing and appropriate information provision of affected individuals, as well as their relatives. However, the context of postmortem genetic testing raises some particular ethical, legal, and practical (including economic or financial) challenges. The Public and Professional Policy Committee of the European Society of Human Genetics (ESHG), together with international experts, developed recommendations on management of SCD after a workshop sponsored by the Brocher Foundation and ESHG in November 2016. These recommendations have been endorsed by the ESHG Board, the European Council of Legal Medicine, the European Society of Cardiology working group on myocardial and pericardial diseases, the ERN GUARD-HEART, and the Association for European Cardiovascular Pathology. They emphasize the importance of increasing the proportion of both medical and medicolegal autopsies and educating the professionals. Multidisciplinary collaboration is of utmost importance. Public funding should be allocated to reach these goals and allow public health evaluation.
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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 | 0.024 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.023 | 0.010 |
| Insufficient payload (model declined to judge) | 0.016 | 0.009 |
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".