The Correlation of Epileptiform Discharges in Sleep with Ictal Onset in Schizencephaly (P2.093)
Bibliographic record
Abstract
OBJECTIVE: To determine the impact of different sleep stages on electrographic extent of epileptiform discharges in schizencephaly, and to correlate zone of ictal onset with extent of epileptiform discharges in sleep. BACKGROUND: Schizencephaly is a common developmental cause of epilepsy. The cortical structural abnormalities may be diffuse or multifocal. When medically refractory, delineating the zone of ictal onset for possible epilepsy surgery may be challenging. Sleep has shown promise in localizing the zone of ictal onset in other diffuse and multifocal developmental epileptogenic conditions, like tuberous sclerosis. DESIGN/METHODS: We retrospectively reviewed the EEGs of schizencephaly patients and analyzed electrical fields of epileptiform discharges in wakefulness, N1, N2, N3 and REM sleep. We analyzed the zones of ictal onset for all seizures. We characterized fields by enumerating the number of electrodes involved. We calculated the percent difference in the number of electrodes involved in epileptiform discharges from different sleep stages compared to wakefulness. We also calculated the ratio between electrodes involved in ictal onset and interictal epileptiform discharges from wakefulness and different sleep stages. RESULTS: We found 6 patients with schizencephaly. Compared to wakefulness, the field of interictal epileptiform discharges increased by 20.4[percnt] in N1 (n= 6), 62.2[percnt] in N2 (n=6), 153.7[percnt] in N3 (n=3), and decreased by 3.0[percnt] in REM (n=3) sleep. We also discovered that fields of epileptiform discharges overlapped with zones of ictal onset by 28.7[percnt] in wakefulness (n=4), 28.4[percnt] in N1 (n=4), 24.3[percnt] in N2 (n=4), 20.5[percnt] in N3 (n=2) and 44.1[percnt] in REM (n=2) sleep. CONCLUSIONS: Despite small sample sizes, this study suggests that non-REM sleep expands the field of interictal discharges in schizencephaly while the field in REM sleep is comparable to wakefulness. This study also suggests that the field of epileptiform discharges correlates best with the zone of ictal onset in REM sleep.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".