COGNITIVE IMPAIRMENT AND DEMENTIA IN PARKINSON'S DISEASE
Bibliographic record
Abstract
Cognitive impairment is one of the most frequent and disabling non-motor manifestations of Parkinson's disease. It significantly reduces patients' quality of life, increases caregiver burden, and contributes to loss of independence. Early identification of cognitive decline is crucial for timely intervention and prevention of dementia progression. The purpose of the study. To determine the prevalence of cognitive impairment and identify predictors of progression to dementia among patients with Parkinson's disease. Material and Methods. A total of 106 patients with PD were examined and followed in outpatient clinics in Almaty. The diagnosis of Parkinson's disease was confirmed according to international criteria. Cognitive status was assessed using the Mini-Mental State Examination and Montreal Cognitive Assessment. Disease severity was evaluated using the Hoehn and Yahr scale and the Schwab and England Activities of Daily Living Scale. Demographic and clinical parameters, including age, education level, disease duration, and motor subtype, were analyzed. Results. Mild cognitive impairment was identified in 26.4% of patients, dementia in 34.9%, and no cognitive impairment in 38.7%. More pronounced cognitive decline was more common among older patients, those with lower educational attainment, disease duration over 10 years, and the akinetic-rigid subtype of Parkinson's disease. Regression analysis revealed the key predictors of dementia: disease onset after age 60, duration exceeding 19 years, low education level, and severe motor deficit. Conclusion. Cognitive impairment is common among Parkinson's disease patients and tends to progress with disease duration and severity. Early detection and systematic monitoring of cognitive functions are essential for implementing preventive measures, slowing dementia progression, and improving the quality of life of individuals with Parkinson's disease.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".