Prognostic Tests and Antiepileptic Drug Withdrawal After Epilepsy Surgery
Bibliographic record
Abstract
Approximately one in three patients with a successful epilepsy surgery will have seizure recurrence following antiepileptic drugs (AED) withdrawal. The value of postoperative testing for predicting seizure relapse after AED tapering is not clear. The purpose of this study was to review the literature for evidence on the use of postoperative investigations before AED discontinuation after successful epilepsy surgery. We were unable to identify studies on the prognostic value of postoperative magnetic resonance imaging and AED blood levels. The literature review yielded seven studies on the predictive value of electroencephalography. Four studies found no association between interictal discharges (IED) and seizure relapse. These studies suffered from various limitations due to their retrospective design and generally small cohorts. Two of the three studies reporting a positive association were prospective and provided strong evidence of an increased risk of seizure recurrence with presence of postoperative IED in successfully operated patients undergoing AED withdrawal.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".