A meta analysis of key risk factors for sudden unexpected death in epilepsy
Bibliographic record
Abstract
Purpose: To examine the risk factors (RFs), associated with Sudden Unexpected Death in Epilepsy (SUDEP), and the quantitative standards required to measure them Methods: The literature on RFs associated with SUDEP was systematically reviewed up to August 2020 in databases, including PubMed, the Cochrane Database and Embase. Revised Newcastle-Ottawa Scale (NOS) was performed to determine the quality of each study in this meta-analysis (MA), with a score of ≥ 3, indicating good quality. Any controversies in data extraction and quality assessment were resolved through counsel or adjudication with a third researcher. Results: An initial screening of the literature following the search strategy and manual inclusion yielded a total of 767 studies. After excluding duplicates as well as articles that did not match the topic, 112 studies remained. Twenty-nine studies were finally selected based on the inclusion and exclusion criteria. After a careful review of the full text, nine studies were included in the MA. Conclusion: The five RFs for SUDEP included age at the onset of epilepsy ≤15 years, generalized-tonic-clonic seizure, seizure frequency ≥50 seizures/year, treatment with a combination of multiple antiepileptic drugs, and history of alcohol abuse.
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.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| 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) | 0.001 | 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".