Clinical Characters and Correlated Factors of Mild Cognitive Impairment in Parkinson's Disease
Bibliographic record
Abstract
Objective:To investigate the correlated factors and predictors of mild cognitive impairment in patients with Parkinson's disease and its clinical characters.Methods:According to the diagnostic criteria of Movement Disorder Society Task Force for Mild Cognitive Impairment in Parkinson's Disease,81 PD patients were evaluated by Montreal Cognitive Assessment(Mo CA),and Unified Parkinson's Disease Rating Scale( Ⅰ-Ⅲ).Results:In 81 PD patients,47 cases(58 %) were with mild cognitive impairment PD-MCI and 23 cases(28 %) were with no cognitive impairment(PD-NCI).Patients(14 %) with mild impaired cognition had a disease duration of less than 5 years.There was significant difference between PD-MCI and PD-NCI group in education(P0.05),HY stage(P0.05),the L-dopa equivalent daily dose(LEDD)(P0.05);the score in PD-MCI group was significantly lower in visuospatial and executive functioning(P 0.05),delayed recall(P 0.05),attention(P 0.05),language(P 0.05) and abstract(P 0.05) subdomains compared with that of PD-NCI group.The difference of UPDRSⅢ and postural instability and gait difficulty(PIGD) were statistically significant in two groups(P0.05).Mo CA score of PD-MCI group was negatively correlated with age(r =-0.31,P0.05),HY stage(r=-0.44,P0.05),UPDRS-Ⅲ(r=-0.32,P0.05),UPDRS-Ⅱ(r=-0.35,P0.05),UPDRS-Ⅰ(r =-0.40,P0.05),bradykinesia(r=-0.38,P0.05) and PIGD(r=-0.31,P0.05),and Mo CA score of PD-MCI group was positively correlated with education(r=0.30,P0.05).Including Mo CA score as the dependent variable,and age,HY stage,education,UPDRS-Ⅲ,UPDRS-Ⅱ,UPDRS-Ⅰas the independent variables,PD-MCI was predicted by age(β coefficients-0.06,P0.05) and HY stage(β coefficients-0.80,P0.05).Furthermore,multiple regressions with UPDRS subscale scores were conducted to examine their unique contributions to cognitive function.When including bradykinesia and PIGD subscale scores,only bradykinesia predicted PD-MCI(β coefficients-0.12,P0.05).Conclusions:Mild cognition impairment is one of the common non-motor symptom with highly prevalence in PD,which is mainly characterized by the dramatic impairments in the cognitive domains of visuospatial and executive functioning,delayed recall,attention,language.Poorer cognitive performance is associated with increasing disease severity,age,movement disorder and education,especially in bradykinesia and PIGD.Mild cognitive impairment may be predicted by age,HY and bradykinesia.
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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 | 0.003 |
| 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 | 0.001 |
| 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".