Changes in sensor recorded activity patterns and neuropsychiatric symptoms after deep brain stimulation for Parkinson’s disease: 5 case reports
Bibliographic record
Abstract
BACKGROUND: Effects of subthalamic nucleus deep brain stimulation (STN-DBS) on neuropsychiatric symptoms of Parkinson's disease (PD) remain debated. Sensor technology might help to objectively assess behavioural changes after STN-DBS. CASE PRESENTATION: 5 PD patients were assessed 1 before and 5 months after STN-DBS with the Movement Disorders Society Unified Parkinson's Disease Rating Scale part III in the medication ON (plus postoperatively stimulation ON) condition, the Montreal Cognitive Assessment, the Questionnaire for Impulsive-Compulsive Behaviors in Parkinson's Disease Rating Scale present version, the Hospital Anxiety and Depression Scale and the Starkstein Apathy Scale. Steps taken per hour, nighttime spent in bed and time spent outside were monitored with a smartwatch and ambient sensors placed in patient homes for an average of 20 days pre- and postoperatively. Postoperative improvement in ICDs and concomitant anxious-depressive symptoms was observed in 3 patients and was accompanied by a decrease in steps taken per hour, as well as an increase in nighttime spent in bed. In the two patients without baseline ICDs, mild anxiety and apathy improved postoperatively, and no new neuropsychiatric symptoms occurred. Steps taken per hour did not decrease in these cases and nighttime spent in bed improved in one of the patients, but decreased in the other, who had experienced pain during OFF-phases at night before STN-DBS. CONCLUSION: Changes in neuropsychiatric symptoms are associated with distinct activity patterns after STN-DBS, and wearable and ambient sensors may aid to capture those gradual shifts in behavior.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".