Values of Montreal Cognitive Assessment Scale and Mini-Mental State Scale in detection of Parkinson's disease with mild cognitive dysfunction
Bibliographic record
Abstract
Objective To investigate the values of Montreal Cognitive Assessment Scale(MoCA) and Mini-Mental State Examination(MMSE) in detecting Parkinson's disease(PD) with mild cognitive impairment(PDMCI). Methods Random sampling was used to select 75 PDMCI patients,180 PD patients with normal cognitive function,and 145 healthy controls. These subjects were screened by MoCA and MMSE for PDMCI,and the two scales were compared in terms of sensitivity and specificity. Results In the illiterate group, MMSE had a sensitivity of 93. 10% and a specificity of 100%,versus 0% and 92. 72% for MoCA. In the primary school group, MMSE had a sensitivity of 87. 50% and a specificity of 100%,versus 41. 67% and 79. 17% for MoCA. In the junior high school and above group,MMSE had a sensitivity of 27. 27% and a specificity of 100%,versus 90. 91% and 85. 71% for MoCA. Conclusions MoCA is suitable for PDMCI detection in people with degrees of junior high school and above,while MMSE for people with degrees below junior high school.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".