Adductor Spasmodic Dysphonia Improves with Bilateral Thalamic Deep Brain Stimulation: Report of 3 Cases Done Asleep and Review of Literature
Bibliographic record
Abstract
Background: To date, there are only six published reports of adductor spasmodic dysphonia (SD) responding to awake thalamic deep brain stimulation (DBS). Methods: We retrospectively reviewed cases of Essential Tremor (ET) with SD that were seen in our center from 2012 to 2020. We further identified those that have undergone thalamic DBS, and had a blinded laryngologist rate first the audio voice recordings before and after DBS using the Unified Spasmodic Dysphonia Rating Scale (USDRS), and the video recordings last to rate the related movements and facial grimacing. Results: We identified three cases of adductor SD with ET that had undergone bilateral ventralis intermedius (VIM) DBS under general anesthesia. All patients noted improvement of their limb and voice tremor, as well as their SD post-DBS. Although improvement of tremor was observed even with initial programming in all three, improvement of SD was noted only upon reaching higher amplitudes or wider pulse widths. Blinded voice assessments showed improvement of USDRS scores post-DBS compared to pre-DBS, and with stimulator on compared to stimulator off. Discussion: We report the first three cases of SD responding favorably to bilateral VIM asleep DBS and summarize the nine cases so far of SD who have undergone thalamic DBS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".