Subthalamic Nucleus Stimulation in Pediatric Isolated Dystonia: A 10-Year Follow-up
Bibliographic record
Abstract
OBJECTIVE: To evaluate the short-term and long-term clinical effectiveness and safety of subthalamic nucleus deep brain stimulation (STN-DBS) for medically intractable pediatric isolated dystonia. METHODS: Using a longitudinal retrospective design, we assessed the clinical outcomes of nine patients who underwent STN-DBS for treatment-refractory pediatric isolated dystonia one decade ago (mean age at surgery: 15.9 ± 4.5 years). The primary clinical outcome used was assessed by retrospective video analyses of patients' dystonia symptoms using the Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS). Clinical assessments were performed at baseline, 1-year follow-up (1-yr FU), and 10-year follow-up (10-yr FU). Adverse side effects, including surgery-related, device-related, and stimulation-related effects, were also documented. RESULTS: After STN-DBS surgery, the mean improvement in the BFMDRS motor score was 77.1 ± 26.6% at 1-yr FU and 90.4 ± 10.4% at 10-yr FU. Similarly, the mean BFMDRS disability score was improved by 69.5 ± 13.6% at 1-yr FU and by 86.5 ± 13.9% at 10-yr FU. The clinical improvements gained at 10-yr FU were significantly larger than those observed at 1-yr FU. Negative correlations were found between the duration of disease to age at surgery ratio (DD/AS) and the improvements in the BFMDRS motor score and total score at 1-yr FU and 10-yr FU. CONCLUSION: To our knowledge, this study provides the first clinical evidence for the short- and long-term effectiveness and safety of STN-DBS for pediatric isolated dystonia. Additionally, putative evidence is provided that earlier STN-DBS intervention in patients with refractory pediatric isolated dystonia may improve short- and long-term clinical outcomes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".