Brittle Dyskinesia Following STN but not GPi Deep Brain Stimulation
Bibliographic record
Abstract
BACKGROUND: The aim was to describe the prevalence and characteristics of difficult to manage dyskinesia associated with subthalamic nucleus (STN) deep brain stimulation (DBS). A small subset of STN DBS patients experience troublesome dyskinesia despite optimal programming and medication adjustments. This group of patients has been referred to by some practitioners as brittle STN DBS-induced dyskinesia, drawing on comparisons with brittle diabetics experiencing severe blood sugar regulation issues and on a single description by McLellan in 1982. We sought to describe, and also to investigate how often the "brittle" phenomenon occurs in a relatively large DBS practice. METHODS: An Institutional Review Board-approved patient database was reviewed, and all STN and globus pallidus internus (GPi) DBS patients who had surgery at the University of Florida from July 2002 to July 2012 were extracted for analysis. RESULTS: There were 179 total STN DBS patients and, of those, four STN DBS (2.2%) cases were identified as having dyskinesia that could not be managed without the induction of an "off state," or by the precipitation of a severe dyskinesia despite vigorous stimulation and medication adjustments. Of 75 GPi DBS cases reviewed, none (0%) was identified as having brittle dyskinesia. One STN DBS patient was successfully rescued by bilateral GPi DBS. DISCUSSION: Understanding the potential risk factors for postoperative troublesome and brittle dyskinesia may have an impact on the initial surgical target selection (STN vs. GPI) in DBS therapy. Rescue GPi DBS therapy may be a viable treatment option, though more cases will be required to verify this observation.
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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 | 0.000 | 0.003 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".