Deep Brain Stimulation for Dystonia
Bibliographic record
Abstract
Stimulation electrodes are implanted under general anesthesia, without intra-operative electrophysiology or clinical testing, based only on stereotactic MRI and direct anatomical localization of the postero-ventro-basal GPi. We retrospectively analyzed the surgical procedure that has been designed and implemented in our center, using the Leksell G frame, for initiating deep brain stimulation in 65 dystonic patients. We report the surgical technique and the hardware and software complications. We recommend immediate postoperative stereotactic MRI under general anesthesia as a prerequisite to check the reliability of MR acquisition (magnet stability) and the exact localization of each electrode. This technique allowed us to reduce the duration of the operation to 4 h, including general anesthesia, frame fixation, MRI acquisition, implantation of two electrodes under radioscopic control, immediate postoperative stereotactic MRI and frame removal. Surgery-related morbidity was very low with a 0% hemorrhage rate and three delayed unilateral infections re-operated 6 months later. Hardware and software complications were rare. The advances in 3D-MR imaging permit the electrode implantation for deep brain stimulation without resorting to intraoperative localization techniques, which is especially helpful in children and for treating dystonia. The maximum follow-up period is 58 months (first case: November 1996). GPi stimulation has proven to be an effective treatment for most dystonic syndromes with particular efficacy in the disease due to the DYT1 mutation.
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 | 0.000 |
| 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".