Anesthesia for deep brain stimulation: an update
Bibliographic record
Abstract
PURPOSE OF REVIEW: Deep brain stimulation (DBS) is a rapidly expanding surgical modality for the treatment of patients with movement disorders. Its ability to be adjusted, titrated, and optimized over time has given it a significant advantage over traditional more invasive surgical procedures. Therefore, the success and popularity of this procedure have led to the discovery of new indications and therapeutic targets as well as advances in surgical techniques. The aim of this review is to highlight the important updates in DBS surgery and to exam the anesthesiologist's role in providing optimal clinical management. RECENT FINDINGS: New therapeutic indications have a significant implication on perioperative anesthesia management. In addition, new technologies like frameless stereotaxy and intraoperative magnetic resonance imaging to guide electrode placement have altered the need for intraoperative neurophysiological monitoring and hence increased the use of general anesthesia. With an expanding number of patients undergoing DBS implantation, patients with preexisting DBS increasingly require anesthesia for unrelated surgery and the anesthesiologist must be aware of the considerations for perioperative management of these devices and potential complications. SUMMARY: DBS will continue to grow and evolve requiring adaptation and modification to the anesthetic management of these patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 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 teacher head, 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".