Mini Mental Status Examination vs. Montreal Cognitive Assessment For Early Diagnosis Of Vascular Dementia
Bibliographic record
Abstract
Background: The Mini Mental Status Examination (MMSE) and Montreal Cognitive Assessment (MoCA) are the most commonly used scales to detect mild cognitive impairment in population-based epidemiologic studies.The aim of this study was to define which test is more reliable for early diagnosis of vascular dementia -MoCA or MMSE.Material and methodes: This prospective study included 274 patients with acute stroke, both sexes and all age groups.Patients were divided into groups: demented (DP) and non-demented (NDP).Each patient was underwent to a clinical examination and scoring with appropriate scales (MMSE and MoCA).Patients were tested on two times after discharge.Results: Out of the total number of patients, 171 (62.5%) of them were male, and 103 (37.5%) were female (p=0.339).First testing with the MMSE showed that 143 (52%) had mild or moderate dementia.Sixth months after stroke, the number of demented patients increased to 165 (60%).First testing with the MoCA scale showed that 183 (66%) had some degree of dementia, and after the sixth month 191 (69%).The MoCA recorded a greater number of patients with dementia in both, the first and second testing.MoCA is more sensitive than MMSE for detecting patient with vascular dementia 3 and 6 months after stroke (p=0.0004;p=0.01). Conclusion:The MoCA is more sensitive scale than the MMSE for detecting early stages of vascular dementia.It should be used in daily practice more often than the MMSE in order to make a timely diagnosis of the early stage of dementia.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".