Experience and consensus on stimulation of the anterior nucleus of thalamus for epilepsy
Bibliographic record
Abstract
Deep brain stimulation of the anterior nuclei of thalamus (ANT-DBS) is effective for reduction of seizures, but little evidence is available to guide practitioners in the practical use of this therapy. In an attempt to fill this gap, a questionnaire with 37 questions was circulated to 578 clinicians who were either engaged in clinical trials of or known users of DBS for epilepsy, with responses from 141, of whom 58.2% were epileptologists and 28.4% neurosurgeons. Multiple regions of the world were represented. The survey found that the best candidates for DBS were considered those with temporal or frontal seizures, refractory to at least two medicines. Motivations for renewing therapy upon battery depletion were reduced convulsive, impaired awareness, and severe seizures and improved quality of life. Targeting of leads mainly was by magnetic resonance imaging, sometimes with intraoperative imaging or microelectrode recording. The majority used transventricular approaches. Stimulation parameters mostly imitated the SANTE study parameters, except for initial stimulation amplitudes in the 2-3-V or -mA range, versus 5 V in the SANTE study. Stimulation intensity was most often increased or reduced, respectively, for lack of efficacy or side effects, but changes in active contacts, cycle time, and pulse duration were also employed. Mood or memory problems or paresthesias were the side effects most responsible for adjustments. Off-label sites stimulated included centromedian thalamus, hippocampus, neocortex, and a few others. Several physicians used DBS in conjunction with vagus nerve stimulation or responsive neurostimulation, although our study did not track efficacy for combined use. Experienced users varied more from published parameters than did inexperienced users. In conclusion, surveys of experts can provide Class IV evidence for the most prevalent practical use of ANT-DBS. We present a flowchart for one protocol combining common practices. Controlled comparisons will be needed to choose the best approach.
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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 | 0.012 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".