Exploring the relationship between dystonia and STN-DBS in Parkinson’s disease: insights from a single-centre cohort
Bibliographic record
Abstract
INTRODUCTION: Motor side effects may emerge after deep brain stimulation (DBS) of the subthalamic nucleus (STN) in Parkinson's disease (PD) patients. Out of 60 PD patients, we observed 16 patients displaying de novo dystonic symptoms after the implantation and 11 dystonic PD patients without benefit from the stimulation. We hypothesized that a common neural pathway may cause dystonia in both conditions. Our study aims to investigate the clinical and connectivity substrates of dystonia after STN-DBS. METHODS: We divided our cohort into four groups: 16 patients displaying dystonia after STN-DBS, 11 patients with previously known dystonia not improving after surgery, 14 patients with dystonic symptoms relieved by the stimulation and 19 controls who never experienced dystonia. MANOVA was used to compare clinical data and the distance of the active contact center from the STN border among the four groups. Finally, we reconstructed the "sour" spots for dystonic symptoms and the associated structural and functional connectivity using a Parkinsonian normative connectome. RESULTS: De novo dystonic and not-improved dystonic patients had a statistically significant longer PD duration before surgery (p = 0.001) and a greater active contact-STN distance (p < 0.001). Moreover, the "sour" spots were similar in both groups and structural and functional connectivity profiles were associated with brain areas correlated with dystonia pathophysiology (cerebellum, midbrain, parietal and temporal cortices). CONCLUSIONS: We formulated a two-hit model for dystonia after STN-DBS: a clinical feature of Parkinsonian patients causes predisposing altered plasticity contributing to dystonic symptoms development when coupled with the stimulation of dystonia-related subcortical and cortical structures.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".