Sudden unexpected death in epilepsy is prevented by blocking postictal hypoxia
Bibliographic record
Abstract
Abstract Epilepsy is at times a fatal disease. Sudden unexpected death in epilepsy (SUDEP) is the leading cause of mortality in people with intractable epilepsy and is defined by exclusion; non-accidental, non-toxicologic, and non-anatomic causes of death. While SUDEP often follows a bilateral tonic-clonic seizure, the mechanisms that ultimately lead to terminal apnea and then asystole remain elusive and there is a lack preventative treatments. Based on the observation that discrete seizures lead to local vasoconstriction, resulting in hypoperfusion, hypoxia and behavioural disturbances in the forebrain (Farrell et al., 2016), we reasoned that similar mechanisms may play a role in SUDEP when seizures invade the brainstem. Here we tested this neurovascular-based hypothesis of SUDEP in awake non-anesthetized mice by pharmacologically preventing seizure-induced vasoconstriction, with cyclooxygenase-2 or L-type calcium channel antagonists. In both acute and chronic mouse models of SUDEP, ibuprofen and nicardipine extended life. We also examined the potential role of spreading depolarization in the acute model of SUDEP. These data provide a proof of principle for the neurovascular hypothesis of SUDEP and the use of currently available treatments to prevent it.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".