Stimulation of the Anterior Nucleus of the Thalamus for Epilepsy: A Canadian Experience
Bibliographic record
Abstract
OBJECTIVE: To describe the experience with Anterior Nucleus of the Thalamus-Deep Brain Stimulation (ANT-DBS) for the treatment of epilepsy at a Canadian Center. METHODS: All patients who underwent ANT-DBS implantation between 2013 (first patient implanted at our center) and 2020 were included. These patients had therapy-resistant epilepsy (TRE), were not candidates for resective surgery, and failed vagus nerve stimulation (VNS) treatment. Baseline of monthly seizure frequency was calculated within 3 months prior to VNS placement. Monthly seizure frequency was assessed at different points along the timeline: 3 months before ANT-DBS implantation as well as 3, 6, 12, 24, 36, 48, 60, and 72 months after ANT-DBS device placement. At each time point, seizure frequency was compared to baseline. RESULTS: Six patients were implanted with ANT-DBS. Three (50%) patients had multifocal epilepsy, one (16.6%) had focal epilepsy, and two (33.4%) had combined generalized and focal epilepsy. Two patients with multifocal epilepsy experienced a seizure reduction >50% in the long-term follow-up. Three (50%) patients did not showed improvement: two with combined generalized and focal epilepsy and one with focal epilepsy. There were not surgical or device-related side effects. Two (33.3%) patients presented mild and transient headaches as a stimulation-related side effect. CONCLUSION: ANT-DBS is an effective and safe treatment for focal TRE. Our experience suggests that patients with multifocal epilepsy due to regional lesion may benefit from ANT-DBS the most. Further investigations are required to determine optimal parameters of stimulation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".