Stimulating Frontostriatal Circuitry to Treat Motor and Non-Motor Symptoms of Parkinson’s Disease (P6.073)
Bibliographic record
Abstract
OBJECTIVE: We sought to assess patients with a diagnosis of PD along with TRD/psychosis in the motoric (UPDRS-Unified Parkinson’s Disease Rating Scale), cognitive (MOCA-Montreal Cognitive Assessment), and neuropsychiatric (AS-Apathy Scale, GDS-Geriatric Depression Scale, HAMD-17-Hamilton Depression Scale, SAPS-Scale for the Assessment of Positive Symptoms) domains prior to and after an acute course of right unilateral ultrabrief pulse (RULUBP) electroconvulsive therapy (ECT). BACKGROUND: Parkinson’s disease (PD) is a movement disorder frequently associated with neuropsychiatric dysfunction. Despite ECT's efficacy in treating PD, clinicians have been reluctant to use traditional ECT due to its cognitive side-effects. Recent studies in treatment-resistant depression (TRD) have demonstrated that RULUBPECT has a favorable cognitive side-effect profile. DESIGN/METHODS: We assessed change from baseline (BL) to immediate post-treatment (IPT) and one month post-treatment. Due to sample size (n=5), we chose a nominal value of p=0.10 to denote a statistical significance, and used the Wilcoxon signed-rank test (WSRT) to compare matched values at different time-points for each participant. RESULTS: All measures (except MOCA) dropped dramatically acutely and long-term. Mean values from baseline to post-treatment decreased from 33.8 to 8.6(HAMD-17), 60.2 to 23.6(AS), 23.2 to 9.0(GDS), 4.2 to 0.2(SSI), 18.6 to 1.6(SAPS), and 31.4 to 11.75(UPDRS) while MOCA increased from 26.2 to 27.6. Based on WSRT, improvements were statistically significant for HAMD-17, AS, and GDS scales at IPT (p=0.06). UPDRS, SSI, and SAPS trended toward statistical significance. CONCLUSIONS: This open label study suggests that RULUBPECT is safe, and is likely efficacious in treating multiple domains of PD. Study Supported by: R25 DA020537-06 Back, SE & Brady, KT(PI)
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".