Subthalamic stimulation and neuropsychiatric symptoms in Parkinson’s disease: results from a long-term follow-up cohort study
Bibliographic record
Abstract
BACKGROUND: Reports on behavioural outcomes after subthalamic nucleus deep brain stimulation in Parkinson's disease are controversial and limited to short-term data. Long-term observation in a large cohort allows a better counselling and management. METHODS: To determine whether a long-term treatment with subthalamic stimulation induces or reduces impulse control behaviours, neuropsychiatric fluctuations and apathy, 69 patients treated with subthalamic stimulation are prospectively and retrospectively assessed using Ardouin Scale of Behavior in Parkinson's Disease before and after 3-10 years of stimulation. RESULTS: At a mean follow-up of 6 years, all impulse control disorders and dopaminergic addiction were significantly decreased, apart from eating behaviour and hypersexuality. Neuropsychiatric fluctuations also significantly improved (ON euphoria: 38% of the patients before surgery and 1% after surgery, P<0.01; OFF dysphoria: 39% of the patients before surgery and 10% after surgery, P<0.01). However, apathy increased (25% of the patients after surgery and 3% before, P<0.01). With the retrospective analysis, several transient episodes of depression, apathy, anxiety and impulse control disorders occurred. CONCLUSIONS: Bilateral subthalamic nucleus stimulation was overall very effective in improving impulse control disorders and neuropsychiatric fluctuations in parkinsonian patients in the long term despite a counteracting frequent apathy. Transient episodes of impulse control disorders still occurred within the follow-up. These findings recommend a close follow-up in parkinsonian patients presenting with neuropsychiatric symptoms before deep brain stimulation surgery. CLINICAL TRIAL REGISTRATION: NCT01705418;Post-results.
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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 | 0.001 |
| 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) | 0.001 | 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".