Diagnostic significance of the difference values between Mini-Mental State Examination and Montreal Cognitive Assessment in elderly patients with dementia
Bibliographic record
Abstract
Objective To investigate the diagnostic significance of the difference values between Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA)in elderly patients with dementia. Methods 331 elderly patients with dementia were collected from out-patients in our hospital. There were 148 people with Alzheimer′s disease (AD), 87 cases with vascular dementia (VaD), 44 cases with mixed dementia (MD), 41 cases with frontotemporal dementia (FTD) and 11 cases with dementia with Lewy bodies (DLB). MMSE and MoCA were applied to test the cognitive impairment separately. Results The difference values between MMSE and MoCA was (3.3±1.7) points, (6.6±2.1) points, (6.6±2.1) points, (5.4±2.3) points, (6.1±1.9) points in AD, VaD, MD, FTD and DLB group respectively, and there were statistical differences among the five groups (F=46.420, P=0.000). Statistical differences were found in the difference values between MMSE and MoCA between dementia patients with AD and non-AD (t=-13.429, P=0.000). According to receiver operating characteristic curve (ROC curve), the optimal cut off point of the difference values between MMSE and MoCA for differential diagnosis between AD and non-AD dementia was 5 points, with 79.8% sensitivity and 78.4% specificity, and area under the curve was 0.848 (95%CI: 0.807-0.890). Conclusions The difference values between MMSE and MoCA may be one of parameters for differential diagnosis between AD and non-AD dementia. Key words: Dementia; Psychiatric status rating scales; Cognition
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".