Improvement of non-motor symptoms and quality of life after DBS stimulation for dystonia: one-year follow-up
Bibliographic record
Abstract
Background: DBS is an established treatment option in refractory dystonia, and motor outcomes have been extensively evaluated instead of the usually neglected NMS (e.g., pain). Objective: To describe the non-motor symptoms (NMS) after Deep Brain Stimulation (DBS) surgery for refractory generalized inherited/idiopathic dystonia in a prospective study. Design and setting: A prospective study that evaluated patients in the Hospital das Clinicas da Faculdade de Medicina da Universidade de Sao Paulo. Methods: This study evaluated patients before and one year after DBS surgery. We applied the following scales: Burke-Fahn-Marsden Rating Scale (BFMRS), Hospital Anxiety and Depression Scale (HADS), Non-Motor Symptoms Scale for Parkinson’s Disease (NMSS-PD), Parkinson’s Disease Questionnaire-8 (PDQ8) Brief Pain Inventory (BPI), Neuropathic Pain Symptom Inventory (NPSI) and McGill pain questionnaire. Results: 11 patients (38.35 ± 11.30 years) underwent surgery (36.3% women). Motor BFMRS subscore was 64.36 ± 22.94 at baseline and 33.55 ± 17.44 after surgery (p=0.003, 47.9% improvement on motor symptoms). HADS scores remained unchanged. NMSS-PD had a significant change after DBS, from 70.91 ± 59.07 to 37.18 ± 55.05 (p=0.013, 47,5% improvement). Seven patients reported pain before DBS surgery, and after one year, four patients reported chronic pain (i.e., pain improved by 42.28%). BPI’s severity and interference scores were 4.61 ± 2.84 and 4.12 ± 2.67, respectively before surgery, and 2.79 ± 2.31 (0.00–6.25) and 1.12 ± 1.32 (0.00–3.00) after DBS (p=0.043 and p=0.028). NPSI total score was 15.29 ± 13.94 before DBS, and reduced to 2.29 ± 2.98 afterward (p=0.028). McGill’s total score was 9.00 ± 3.32 before DBS, achieving 2.71 ± 2.93 after surgery (p=0.028), mostly driven by the sensory sub-score. Conclusions: We found that DBS improves NMS in dystonia, including chronic pain, anxiety, gastrointestinal symptoms, besides the already established improvement in QoL and motor symptoms.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".