The Montreal Cognitive Assessment is superior to the Mini–Mental State Examination in detecting patients at higher risk of dementia
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Bibliographic record
Abstract
BACKGROUND: To examine the discriminant validity of the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE) in detecting patients with cognitive impairment at higher risk for dementia at a memory clinic setting. METHODS: Memory clinic patients were administered the MoCA, MMSE, and a comprehensive formal neuropsychological battery. Mild cognitive impairment (MCI) subtypes were dichotomized into two groups: single domain-MCI (sd-MCI) and multiple domain-MCI (md-MCI). Area under the receiver operating characteristic curve (ROC) analysis was used to compare the discriminatory ability of the MoCA and the MMSE. RESULTS: Two hundred thirty patients were recruited, of which 136 (59.1%) were diagnosed with dementia, 61 (26.5%) with MCI, and 33 (14.3%) with no cognitive impairment (NCI). The majority of MCI patients had md-MCI (n = 36, 59%). The MoCA had significantly larger AUCs than the MMSE in discriminating md-MCI from the lower risk group for incident dementia (NCI and sd-MCI) [MoCA 0.92 (95% CI, 0.86-0.98) vs. MMSE 0.84 (95% CI, 0.75-0.92), p = 0.02). At their optimal cut-off points, the MoCA (19/20) remained superior to the MMSE (23/24) in detecting md-MCI [sensitivity: 0.83 vs. 0.72; specificity: 0.86 vs. 0.83; PPV: 0.79 vs. 0.72; NPV: 0.89 vs. 0.83; correctly classified: 85.1% vs. 78.7%]. CONCLUSION: The MoCA is superior to the MMSE in the detection of patients with cognitive impairment at higher risk for incident dementia at a memory clinic setting.
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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 | 0.001 | 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 it