POSTICTAL WANDERING IS COMMON AFTER TEMPORAL LOBE SEIZURES
Bibliographic record
Abstract
Some epilepsy patients in their postictal state may leave the setting of their complex partial seizures and wander either aimlessly or semipurposely. This postictal wandering (PIW) may result not only in social embarrassment but also in potentially tragic consequences if a patient wanders into a dangerous situation before regaining full consciousness. Although PIW is recognized by various names1 and has been described in patients with temporal lobe epilepsy, frontal lobe epilepsy, somnambulism, and other sleep disorders,1–4 its prevalence and localizing value have not been systematically studied. We sought to determine the frequency of PIW and whether it is preferentially associated with seizures arising from certain areas of the brain. ### Methods. Presence or absence of PIW and seizure onset localization were prospectively analyzed in 42 of 54 consecutive patients admitted to an epilepsy monitoring unit between October 2007 and May 2008 for video-EEG investigation of presumed medically refractory localization-related epilepsy. Excluded patients had nonepileptic seizures (n = 6) or no seizures (n = 4) during admission, or were found to have primary generalized epilepsy (n = 2). Simple partial seizures and secondarily generalized tonic-clonic seizures were excluded. Seizure videos were reviewed by the attending epileptologists and PIW was deemed present when in the postictal phase, after disappearance of ictal EEG patterns, patients stood up from their chairs or beds and wandered away (often …
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".