Thalamic deep brain stimulation for the treatment of tremor due to multiple sclerosis: a prospective study of tremor and quality of life
Bibliographic record
Abstract
OBJECT: In several studies a significant reduction in tremor after thalamic deep brain stimulation (DBS) has been reported among patients with multiple sclerosis (MS). It has not been determined if this results in an improved quality of life. In this study the authors prospectively evaluated the effects of thalamic DBS on tremor and quality of life. METHODS: Videotapes of the patients' tremor were made preoperatively and 2 and 12 months postoperatively, and tremor was scored by a neurologist blinded to the treatment. Patients were tested pre- and postoperatively to measure any changes in their reported ability to perform selected activities of daily living and in their health-related quality of life. Patients were asked to complete a questionnaire about their satisfaction with the surgery. Postoperative changes were examined using paired t-tests. There were significant reductions in postural, action, and overall tremor at 2 and 12 months postoperatively. The patients' reported ability to feed themselves was significantly improved 2 months after surgery (p = 0.01). There were short-term trends toward improvement in reported dressing ability, personal hygiene, and writing. There were no significant changes in the SF-36 subscales or total score. CONCLUSIONS: In this cohort of patients with MS who suffered from tremor, thalamic DBS significantly improved their tremor and ability to feed themselves. Patient satisfaction with the procedure, however, was variable. Preoperative patient education about what functions might (and might not) be improved is crucial to avoid unrealistic expectations. Our results indicate that younger patients with MS tremor who had a shorter disease duration and no superimposed ataxia benefited most from this surgery.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".