Report of the American Epilepsy Society and the Epilepsy Foundation Joint Task Force on Sudden Unexplained Death in Epilepsy
Bibliographic record
Abstract
The American Epilepsy Society and the Epilepsy Foundation jointly convened a task force to assess the state of knowledge about sudden unexplained death in epilepsy (SUDEP). The task force had five charges: (1) develop a position statement describing if, when, what, and how SUDEP should be discussed with patients and their families and caregivers; (2) design methods by which the medical and lay communities become aware of the risk of SUDEP; (3) recommend research directions in SUDEP; (4) explore steps that organizations can take to perform large-scale, prospective studies of SUDEP to identify risk factors; and (5) identify possible preventive strategies for SUDEP. Some of the major task force recommendations include convening a multidisciplinary workshop to refine current lines of investigation and to identify additional areas of research for mechanisms underlying SUDEP; performing a survey of patients and their families and caregivers to identify effective means of education that will enhance participation in SUDEP research; conducting a campaign aimed at patients, families, caregivers, coroners, and medical examiners that emphasizes the need for complete autopsy examinations for patients with suspected SUDEP; and securing infrastructure grants to fund a consortium of centers that will conduct prospective clinical and basic research studies to identify preventable risk factors and mechanisms underlying SUDEP. For now, the principal effort in preventing SUDEP should be prompt and optimal control of seizures, especially generalized convulsive seizures.
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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 | 0.042 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".