Relation between Parkinson's Disease Severity and Cognitive Function with Monstreal Cognitive Assessment Indonesia
Bibliographic record
Abstract
Introduction: Parkinson disease is a wide-spectrum disease that can be accompanied by motor and non-motor symptoms. Non-motor symtoms can occurred before the existance of motoric symptoms until the terimal stage of the disease, where cognitive disturbance is one of the non-motor symptoms that can decrease patient’s quality of life and increase patient’s disability. Therefore, early detection of the cognitive function is important for patients with parkinson disease. The aim of this study was to find the association between the severity of Parkinson’s disease and cognitive disturbance using the Montreal Cognitive Assesment Indonesian version (MoCA-Ina) Method: This study used cross-sectional design. The research subject was a parkinson disease patients’ who went to Neurology Clinic at Haji Adam Malik General Hospital Medan and network hospital who met the inclusion and exclusion criteria of the study. The number of sample was 39 subjects. To determine the relationship between the severity of parkinson disease and cognitive function, the Gamma test was used. Results: There was a significant correlation between the severity of Parkinson's disease and cognitive function (p = 0.001, r = -0.858). There was a very strong correlation between the severity of Parkinson's disease and cognitive function, and the negative correlation means the higher the severity of disease, the lower the cognitive function. From this study, the most correlated domains were delayed memory, naming (r = 0.962), orientation (r = -0.944), visuospatial (r = -0.929), abstraction (r = -0.874), language (r = -0.674), attention (r = -0.592). Delayed memory could not be statistically analyzed because delayed memory were all impaired in all subjects. Conclusion: There was a correlation between the severity of Parkinson's disease and cognitive function with a very strong correlation strength. The cognitive function domains that correlate strongly with Parkinson's severity were delayed memory, naming, orientation, visuospatial and abstraction.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".