Evaluation of using Montreal Cognitive Assessment in patients with Parkinson' s disease with cognitive impairment
Bibliographic record
Abstract
Objective To examine the application of Montreal Cognitive Assessment (MoCA) in Parkinson' s disease (PD) patients with normal general cognitive function by Mini-Mental State Examination (MMSE) evaluation.Methods PD patients were examined with MMSE, and those having a normal ageand education-adjusted MMSE score were included in the further study of MoCA testing.The patients with MoCA score not less than 26 were selected into normal control PD-NC group, and the patients with less than 26 into cognitive impaired PD-CI group.Scores of MoCA subtests were used in PD-CI group and PD-NC group to characterize cognitive changes in PD patients with mild cognitive impairment (MCI).MoCA score in PD-CI group used as dependent variable, and sex, educational level, age, course of disease, Hamilton Depression Rating Scale (HAMD), Hamilton Anxiety Rating Scale (HAMA), Self-rating depression Scale (SDS), Self-rating Anxiety Scale (SAS) and Unified Parkinson' s Disease Rating Scale (UPDRS) were used as independent variable, the risk factors of CI in PD patients was analysed by Linear Regression Analysis.Results There are 52.6% (112/213) PD patients with MMSE ≥ 26 while their MoCA < 26.Significant differences were observed in subtests of MoCA in visuospatial, executive, naming, attention,language, abstract, delayed recall and orientation between PD-CI group and PD-NC group (all P <0.01).Univariate and multivariate regression analysis showed that educational level is the most significant factor in PD-CI (OR:0.72, 95% CI 0.64-0.81, P < 0.05).Conclusions There is a high proportion of PD patients whose MMSE test showed normal but MoCA test showed cognitive impairment.MoCA examination was used to detect cognitive function of PD patients.Furthermore we suggest consider the education level in PD patients when evaluate their cognitive function. Key words: Parkinson disease; Cognition disorders; Neuropsychological tests; Mental status schedule
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| 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".