The analysis of MoCA and MMSE assessment for cognitive impairment in elderly patients with Parkinson's disease
Bibliographic record
Abstract
Objective To investigate the characteristics of mild cognitive impairment and the evaluation value of Montreal cognitive assessment(MoCA) and the mini-mental state examination(MMSE) in Parkinson's disease cognitive function.Methods Data from 57 patients with PD and 30 controls were analysed.The patients were estimated by using MoCA and MMSE,meanwhile,the probable effecting factors,such as motor symptom indexes,age,sex,time of onset,educational level and so on were also examed to assess cognitive function.Results The detection range of cognitive impairment of MoCA was much wider than that of MMSE.MoCA total score of the PD group was lower than that of the control group(P 0.05),PD patients existed mainly as executive or visuospatial impairments,abstract thinking,delayed recall fluency damage compared to the control group(P 0.05).Conclusion Executive or visuospatial impairments,abstract thinking and delayed recall fluency dysfunction existed in PD patients,and MoCA,which can early recognize cognitive impairment in patients with Parkinson's disease,was an effective screening means for the old PD groups.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 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".