The Brief Memory and Executive Test (BMET) for detecting vascular cognitive impairment in small vessel disease: a validation study
Bibliographic record
Abstract
BACKGROUND: Cognitive impairment is common in patients with cerebral small vessel disease, but is not well detected using common cognitive screening tests which have been primarily devised for cortical dementias. We developed the Brief Memory and Executive Test (BMET); a rapid screening measure sensitive to the impaired executive function and processing speed characteristic of small vessel disease (SVD). To assess the BMET's validity for general use, we evaluated it when administered by non-psychologists in a multicentre study and collected control data to derive normative scores. METHODS: Two-hundred participants with SVD, defined as a clinical lacunar stroke and a corresponding lacunar infarct on MRI, and 303 healthy controls aged between 40-90 years old were recruited. The BMET, as well as the Montreal Cognitive Assessment (MoCA) and Mini Mental State Examination (MMSE), were performed. Overall, 55 SVD participants underwent repeat testing at 3 months to assess the BMET test-retest reliability. RESULTS: Administering the BMET took a mean (SD) of 12.9 (4.7) in cases and 9.5 (2.6) minutes in controls. Receiver Operator Curve analysis showed the BMET was a good predictor of cognitive impairment in SVD (AUC = 0.94) and performed significantly better than both the MoCA (AUC = 0.77) and the MMSE (AUC = 0.70). Using a cut-off score of 13, the BMET had a sensitivity of 93% and specificity of 76% for detecting cognitive impairment in SVD. CONCLUSIONS: The BMET is a brief and sensitive tool for the detection of cognitive impairment in patients with SVD.
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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 | 0.003 | 0.008 |
| 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".