Seizure Freedom in Temporal Plus Epilepsy Surgery Following Stereo-Electroencephalography
Bibliographic record
Abstract
BACKGROUND: "Temporal plus" epilepsy (TPE) is a term that is used when the epileptogenic zone (EZ) extends beyond the boundaries of the temporal lobe. Stereotactic electroencephalography (SEEG) has been essential to identify additional EZs in adjacent structures that might be part of the temporal lobe/limbic network. OBJECTIVE: We present a small case series of temporal plus cases successfully identified by SEEG who were seizure-free after resective surgery. METHODS: We conducted a retrospective analysis of 156 patients who underwent SEEG in 5 years. Six cases had TPE and underwent anterior temporal lobectomy (ATL) with additional extra-temporal resections. RESULTS: Five cases had a focus on the right hemisphere and one on the left. Three cases were non-lesional and three were lesional. Mean follow-up time since surgery was 2.9 years (SD ± 1.8). Three patients had subdural electrodes investigation prior or in addition to SEEG. All patients underwent standard ATL and additional extra-temporal resections during the same procedure or at a later date. All patients were seizure-free at their last follow-up appointment (Engel Ia = 3; Engel Ib = 2; Engel Ic = 1). Pathology was nonspecific/gliosis for all six cases. CONCLUSION: TPE might explain some of the failures in temporal lobe epilepsy surgery. We present a small case series of six patients in whom SEEG successfully identified this phenomenon and surgery proved effective.
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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 | 0.000 | 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) | 0.001 | 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".