Ventral Intermediate Nucleus Versus Zona Incerta Region Deep Brain Stimulation in Essential Tremor
Bibliographic record
Abstract
Abstract Background The ventral intermediate nucleus (VIM) is the target of choice for Essential Tremor (ET) deep brain stimulation (DBS). Renewed interest in caudal zona incerta (cZI) stimulation for tremor control has recently emerged and some groups believe this approach may address long‐term reduction of benefit seen with VIM‐DBS. Objectives To compare clinical outcomes and DBS programming in the long‐term between VIM and cZI neurostimulation in ET‐DBS patients. Materials and Methods A retrospective review of 53 DBS leads from 47 patients was performed. Patients were classified into VIM or cZI groups according to the location of the activated DBS contact. Demographics, DBS settings, and Tremor Rating Scale scores were compared between groups at baseline and yearly follow‐up to 4 years after DBS. Student t‐tests and analysis of variance (ANOVA) were used to compare variables between groups. Results Relative to baseline, an improvement in ON‐DBS tremor scores was observed in both groups from 6 months to 4 years post‐DBS (p < 0.05). Although improvement was still significant at 4 years, scores from month 6 to 2 years were comparable between groups but at 3 and 4 years post‐DBS the outcome was better in the VIM group (p < 0.01). Stimulation settings were similar across groups, although we found a lower voltage in the VIM group at 3 years post‐DBS. Conclusions More ventral DBS contacts in the cZI region do improve tremor, however, VIM‐DBS provided better long‐term outcomes. Randomized controlled trials comparing cZI vs VIM targets should confirm these results.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".