Surgical treatment of independent bitemporal lobe epilepsy defined by invasive recordings
Bibliographic record
Abstract
OBJECTIVES: Bitemporal lobe epilepsy is commonly encountered in the evaluation of pharmacoresistant epilepsy. Yet the role of surgery in the management of these patients is unclear. This study evaluates the impact of surgery on seizure tendency and quality of life, as well as prognostic indicators in individuals with proven ictal onset bitemporal lobe epilepsy. METHODS: The study population comprised all patients who underwent temporal lobe surgery over a 10 year period and had ictal onset bitemporal lobe epilepsy identified with intracranial electrode monitoring. Patients with extratemporal seizure generators were excluded. Subjects were divided into a favourable or less favourable group based on the results of surgery on seizure tendency. RESULTS: 11 subjects were studied with a mean 5.9 years of post-surgical follow-up. Six subjects constituted the favourable outcome group. Four had a less favourable outcome and continued to have frequent seizures after surgery; however, three with less favourable seizure reduction subjectively reported improvement in quality of life after surgery as a result of reduced seizure frequency and severity, and reduced medications. No single preoperative factor was significantly different between the groups, including ictal EEG laterality, epilepsy duration, age at surgery, age at seizure onset and mesial temporal atrophy. CONCLUSIONS: Surgical resection is an important treatment option for medically intractable bitemporal epilepsy. The proportion of seizures arising from one temporal lobe is not reliable as a single indicator to prognosticate the results of surgery on seizure tendency. In addition, individuals who achieved only palliation by reducing seizure frequency experienced improvement in quality of life.
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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) | 0.002 | 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".