The Characteristics and Influencing Factors of Parkinson's Disease with Mild Cognitive Impairment
Bibliographic record
Abstract
Objective:To investigate the frequency of mild cognitive impairment in patients with Parkinson's disease(PD) and healthy controls over 55 years of age without dementia and to analyze the characteristics and influencing factors of PD with mild cognitive impairment. Methods:One hundred and twelve PD patients having a normal age and education adjusted MMSE score were included in the further study of MoCA testing. Patients with MoCA score no less than 26 were selected into normal control PD-NC group,and patients with MoCA score less than 26 into mild cognitive impaired PD-MCI group. The frequency and influencing factors of PD-MCI were statistically analyzed. One hundred and fifteen healthy subjects over the age of 55 without dementia were selected as control group,which divided into normal control C-NC group and mild cognitive impaired C-MCI group by MoCA testing.Scores of MoCA subtests were used in PD-MCI group and C-MCI group to compare the difference and characterize of cognitive changes. Results:The incidence of MCI in PD-MCI group was 55.4%(62/112) and 27.8%(32/115) in C-MCI group,with a significant difference between these 2 groups(χ2=17.73,P0.05). PD-MCI patients had lower scores in subtests of MoCA in visuospatia1, executive,attention and orientation compared with C-MCI patients(P0.05). Univariate and logistic regression analysis revealed that a high frequency of PD-MCI occurred in patients with high UPDRS Ⅲscore,H-Y stage,and HAMD score. Conclusion:MCI is common in patients with PD,and the main cognitive deficits involve visuospatial,executive,attention, and orientation,which is associated with severity of motor disturbances and depression.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".