Epilepsy surgery in the elderly
Bibliographic record
Abstract
BACKGROUND: Epilepsy surgery is increasingly well-supported as an effective treatment for patients with intractable epilepsy. It is most often performed on younger patients and the safety and efficacy of epilepsy surgery in elderly patients are not frequently described. CASE REPORT: We report a case of a 75-year-old right-handed man who underwent a left fronto-temporal craniotomy for resection of a suprasellar meningioma in 2002. Immediately following hospital discharge, he began to experience complex partial seizures. He continued to have frequent seizures despite treatment with multiple combinations of antiepileptic medications. He presented with status epilepticus every two or three months, and required long periods of hospitalization on each occasion for post-ictal confusion and aphasia. Scalp EEG showed continuous spikes and polyspikes and persistent slowing in the left temporal area, as well as spikes in the left frontal area. EEG telemetry recorded multiple seizures, all with a clear focus in the left temporal area. MRI scan showed an area of encephalomalacia in the left temporal lobe, as well as post-surgical changes in the left frontal area. Neuropsychological testing showed bilateral memory impairment with no significant cognitive decline expected after unilateral temporal lobe resection. A left anteromesial temporal lobectomy was performed with intraoperative electrocorticography. Since surgery, the patient was not seizure-free (Engel class II-b), but had no further episodes of status epilepticus in one year and two months of follow-up. CONCLUSIONS: This is one of the oldest patients reported in the literature with epilepsy surgery and supports the possibility of epilepsy surgery in elderly patients for particular cases. In addition, few cases with such a malignant evolution of temporal lobe epilepsy have been described in this age group.
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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) | 0.003 | 0.001 |
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".