Underestimation of Cognitive Impairment by Mini-Mental State Examination Versus the Montreal Cognitive Assessment in Patients With Transient Ischemic Attack and Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The Mini-Mental State Examination (MMSE) is insensitive to mild cognitive impairment and executive function. The more recently developed Montreal Cognitive Assessment (MoCA), an alternative, brief 30-point global cognitive screen, might pick up more cognitive abnormalities in patients with cerebrovascular disease. METHODS: In a population-based study (Oxford Vascular Study) of transient ischemic attack and stroke, the MMSE and MoCA were administered to consecutive patients at 6-month or 5-year follow-up. Accepted cutoffs of MMSE <27 and MoCA <26 were taken to indicate cognitive impairment. RESULTS: Of 493 patients, 413 (84%) were testable. Untestable patients were older (75.5 versus 69.9 years, P<0.001) and often had dysphasia (24%) or dementia (15%). Although MMSE and MoCA scores were highly correlated (r(2)=0.80, P<0.001), MMSE scores were skewed toward higher values, whereas MoCA scores were normally distributed: median and interquartile range 28 (26 to 29) and 23 (20 to 26), respectively. Two hundred ninety-one of 413 (70%) patients had MoCA <26 of whom 162 had MMSE > or =27, whereas only 5 patients had MoCA > or =26 and MMSE <27 (P<0.0001). In patients with MMSE > or =27, MoCA <26 was associated with higher Rankin scores (P=0.0003) and deficits in delayed recall, abstraction, visuospatial/executive function, and sustained attention. CONCLUSIONS: The MoCA picked up substantially more cognitive abnormalities after transient ischemic attack and stroke than the MMSE, demonstrating deficits in executive function, attention, and delayed recall.
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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 | 0.003 | 0.021 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".