Mild cognitive impairment in patients with Parkinson´s disease and the analysis of associated factors
Bibliographic record
Abstract
Objectives This research targeted to understand the impact of clinical findings, non-motor symptoms, white matter hyperintensities (WMHs), and metabolic features on cognition in Parkinson’s disease patients with mild cognitive impairment (PD-MCI).Methods Sixty-one PD patients sundered into two groups: PD-MCI and normal cognition (PD-NC). We assessed cognition using Montreal Cognitive Assessment-TR (MoCA-TR) and Frontal Assessment Battery (FAB). We used the modified Hoehn&Yahr staging scale (mH&Y), Unified Parkinson’s Disease Rating Scale (UPDRS), Freezing of Gait questionnaire, Beck Depression Inventory, Parkinson’s disease sleep scale-2, Pittsburgh sleep quality index, Epworth sleepiness scale, and Non-motor symptoms questionnaire to evaluate all patients. We used the Fazekas scale to evaluate the WMHs and also investigated all laboratory parameters affecting cognitive functions.Results Duration of disease, UPDRS-Motor part, age, disease stage, and daytime sleepiness were dramatically higher in the PD-MCI group than in PD-NC (p < 0.05). WMHs and homocysteine were higher in the PD-MCI group than in the controls (p = 0.016 and p < 0.001, respectively). There was a negative correlation between cognition and duration of disease, age, disease stage, UPDRS-Motor scale, daytime drowsiness, WMHs and homocysteine levels. Homocysteine was negatively related to visuospatial/executive functions (r=-0.303, p = 0.021). WMHs were correlated with global cognition (p =.000 r = .-542), language (p = .001, r = -.434), and delayed recall (p = .011, r = -.332).Discussion Mild cognitive impairment is a widespread clinical situation of PD patients and often presents before the motor symptoms. Revealing curable causes that affect cognition before the development of PD-related dementia is crucial in controlling motor findings and reducing the burden of the caretakers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".