Nonmotor Symptoms and Impulse Control Disorders in Parkinson’s Disease Patients in India: A Cross-sectional Study
Bibliographic record
Abstract
INTRODUCTION: Parkinson's disease (PD) is a prevalent neurodegenerative disorder with significant nonmotor symptom (NMS) burden, including impulse control disorders. This study aimed to comprehensively evaluate NMS and impulse control disorders in PD patients under primary care. MATERIALS AND METHODS: A descriptive cross-sectional study was conducted on 32 PD patients and evaluated using standardized assessment tools. Demographics, comorbidities, and symptom burdens were recorded. Evaluation tools included the Hoehn and Yahr Scale, REM Sleep Behavior Disorder assessment, Geriatric Depression Scale, Montreal Cognitive Assessment scale for cognitive impairment, NMS scale, and identification of impulse control disorders. RESULTS: In PD, comorbidities were prevalent (84%), and most were at Hoehn and Yahr Stages 2 and 3. REM Sleep Behavior Disorder was present in 28.12%, with 5 receiving clonazepam treatment. Depression affected 28.12%, with 5 receiving pharmacological treatment. Cognitive impairment was notable in 9 patients. NMS burden was high, with varying severity. Impulse control disorders were limited, whereas one case of dopamine dysregulation syndrome was identified. DISCUSSION: This primary care-based study in India assessed NMS and impulse control disorders in PD patients, highlighting comorbidities and management opportunities. The study's strength lies in evaluating an unselected primary care population, whereas limitations include small sample size. CONCLUSION: This study emphasizes the importance of primary care physicians in monitoring and managing NMS in PD patients. Impulse control disorders and cognitive impairment are critical aspects that need attention. The findings support an integrated approach involving health-care professionals across various disciplines to provide holistic care for PD patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".