Nocturnal seizures are associated with more severe hypoxemia and increased risk of postictal generalized <scp>EEG</scp> suppression
Bibliographic record
Abstract
Patients with epilepsy have 20-fold risk of sudden death when compared to the general population. Uncontrolled seizures is the most consistent risk factor, and death often occurs at night or in relation to sleep. We examined seizure-related respiratory disturbances in sleep versus wakefulness, focusing on periictal oxygen saturation. Respiratory measures were examined in 48 recorded seizures (sleep, n = 23, wake, n = 25) from 20 adult patients with epilepsy. Seizures from sleep were associated with lower saturation, as compared to seizures from wakefulness, both during ictal (sleep median = 90.8, wake median = 95.5; p < 0.01) and postictal periods (sleep median = 94.3, wake median = 96.9; p = 0.05). Compared to wake-related seizures, seizures from sleep were also associated with a larger desaturation drop (sleep median = -4.2, wake median = -1.2; p = 0.01). Postictal generalized electroencephalography (EEG) suppression (PGES) occurred more frequently after seizures from sleep (39%), as compared to wake-related seizures (8%, p = 0.01). Our findings suggest that nocturnal seizures may entail a higher sudden unexpected death in epilepsy (SUDEP) severity burden, as they are associated with more severe and longer hypoxemia events, and more frequently followed by PGES, both factors implicated in sudden death.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".