Weight Change after Globus Pallidus Internus or Subthalamic Nucleus Deep Brain Stimulation in Parkinson’s Disease and Dystonia
Bibliographic record
Abstract
BACKGROUND: Weight gain has been described in Parkinson's disease (PD) patients after subthalamic nucleus (STN) deep brain stimulation (DBS). OBJECTIVES: We examined change in weight following DBS in both PD and dystonia patients to further investigate the role of disease and brain target (STN or globus pallidus internus, GPi) specificity. METHODS: Data was retrospectively collected on 61 PD DBS patients (STN n = 31 or GPi n = 30) and on 36 dystonia DBS patients (STN n = 9 and GPi n = 27) before and after surgery. Annual change in body mass index (BMI) was evaluated with nonparametric tests between groups and multiple quantile regression. RESULTS: PD patients treated with STN DBS had a small increase in median BMI while those with GPi had a small decrease in BMI. Dystonia patients treated with STN DBS had a greater increase in BMI per year compared to those treated with GPi DBS. Multivariable regression analyses for each disease showed little difference between targets in weight gain in those with PD, but STN target was strongly associated with weight gain in dystonia patients (STN vs. GPi, +7.99 kg, p = 0.012). CONCLUSIONS: Our results support previous reports of weight gain after DBS in PD. This is the first report to suggest a target-specific increase in weight following STN DBS in dystonia patients.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".