Bilateral subthalamic nucleus deep brain stimulation for refractory isolated cervical dystonia
Bibliographic record
Abstract
Subthalamic nucleus (STN) deep brain stimulation (DBS) has been proven to be an alternative target choice for refractory isolated cervical dystonia (CD). However, assessments of its short and long-term safety, efficacy, and sustained effectiveness have been limited to few reports. Here, we evaluated nine consecutive refractory isolated CD patients who underwent bilateral STN DBS and accepted to short and long-term follow-up in this retrospective study. Seven time points were used to see the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS) scores (pre-operation [baseline], 1, 3, 6, 12, 24 months post-operation and last follow-up) to assess improvement of dystonic symptoms. The 36-item Short-Form General Health Survey (SF-36) scores obtained at pre-operation and last follow-up to assess the changes in quality of life. All patients tolerated surgery well and acquired observable clinical benefits from STN DBS therapy. All patients achieved a considerable improvement in quality of life at the last follow-up. The hardware-related adverse events can be tolerated and the stimulation-related adverse events can be ameliorated by programming. Our data support the idea that bilateral STN DBS is a safety and effective method for the treatment of refractory isolated CD, with persistent and remarkable improvement in both movement and quality of life.
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) | 0.001 | 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".