The Changing Nature of Epilepsy Surgery: A Retrospective Review of Practice Profiles
Bibliographic record
Abstract
OBJECTIVES: Recent literature documents a trend of gradual decline in temporal lobe (resective) epilepsy surgery over the past decade. Amongst these, a large scale, comprehensive survey done in selected European, Australian and American centres documents trends of resective temporal epilepsy surgery across two decades. Montreal Neurological Institute has been the leading epilepsy surgery centre for more than 50 years now. It has been at the forefront of investigating and managing epilepsy in Canada. We have looked into the trends of epilepsy surgery in our institute in the past 44 years. METHODS: The records of all adult epilepsy surgery procedures (excluding reoperations) performed by the senior authors were analysed from 1971 to 2015. Data retrieved for analysis included type of surgery (intracranial recording, resective, and neuromodulatory) and the specific surgical target for resection. Procedures were grouped into temporal resective, extratemporal (ET) resective and placement of intracranial electrodes (stereotactic electroencephalogram (SEEG)). RESULTS: A total of 2,078 new procedures were performed from 1971 to 2015 at the Montreal Neurological Institute. Temporal procedures constituted the bulk of the proportion of all procedures each year and the entire study period. SEEG group shows linear increase in the number of cases over the years catching up with the total number of temporal procedures. CONCLUSIONS: Our study involving a homogenous dataset spanning nearly 50 years shows a decline in temporal lobe surgeries and an increase in intracranial investigations despite the class I evidence of its effectiveness. This corroborates the trends in epilepsy surgery practice profiles in tertiary centres of developed countries.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".