Functional Movement Disorders and Deep Brain Stimulation: A Multi‐Center Study
Bibliographic record
Abstract
Background: Functional movement disorders (FMD) are a commonly under-recognized diagnosis in patients with underlying neurodegenerative diseases. FMD have been observed in patients undergoing deep brain stimulation (DBS) for Parkinson's disease (PD) and other movement disorders. The prevalence of coexisting FMD among movement disorder-related DBS patients is unknown, and it may occur more often than previously recognized. Methods: We retrospectively assessed the relative prevalence and clinical characteristics of FMD occurring post-DBS, in PD and dystonia patients (FMD+, n = 29). We compared this cohort with age at surgery-, sex-, and diagnosis-matched subjects without FMD post-DBS (FMD-, n = 29). Results: Both the FMD prevalence (0.2%-2.1%) and the number of cases/DBS procedures/year varied across centers (0.15-3.65). A total of nine of 29 FMD+ cases reported worse outcomes following DBS. Although FMD+ and FMD- manifested similar features, FMD+ showed higher psychiatric comorbidity. Conclusions: DBS may be complicated by the development of FMD in a subset of patients, particularly those with pre-morbid psychiatric conditions.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".