Bibliographic record
Abstract
Objective: Cognitive impairment is associated with compliance issues and worse outcomes in patients with chronic diseases. Most guidelines recommend using the Mini Mental State Examination (MMSE) to screen for cognitive impairment in older hypertensive patients. The aim of this study was to compare the yield of the MMSE and of the Montreal Cognitive Assessment (MoCA), a screening test known to be more sensitive for vascular dementia and mild cognitive impairment (TCL), in older outpatients at high cardiovascular risk. Design and method: Independently living patients over 65 who were prescribed a treatment for cardiovascular prevention and followed-up by their general practitioner were recruited in a health center. Each patient was randomly assigned to undergo either the MMSE or the MoCA. A MMSE score < 27 (or 24 if high school was not completed) or MoCA score < 26 (25 if high school was not completed) was considered as indicating cognitive impairment. The physician judgement regarding the cognitive ability of each patient was recorded, blind to test results. Results: Patients randomized to the MMSE (n = 55) were similar to those randomized to the MoCA (n = 56, Table). Assessment lasted a little more than 10 min with both tests (Table). There were 22 (40%) screen positive patients with the MMSE and 38 (68%) with the MoCA (p < 0.004 for the difference). Physicians’ judgements predicted a positive MMSE with 97% specificity but only 9% sensitivity, a positive MoCA with 94% specificity but only 16% sensitivity.Conclusions: Cognitive impairment is very frequent in patients over 65 years treated for cardiovascular prevention in primary care, and largely unrecognized by physicians despite its wide ranging consequences including therapeutic non-compliance. Screening guidelines should promote use of the MoCA rather than the MMSE in these patients, since it is able to better detect vascular dementia and mild cognitive impairment with a similar screening time.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.952 | 0.951 |
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".