CONCORDANCE BETWEEN MINI-MENTAL STATE EXAMINATION, MONTREAL COGNITIVE ASSESSMENT AND MEMORY AND EXECUTIVE SCREENING FOR THE ASSESSMENT OF COGNITIVE DECLINE IN HYPERTENSIVE PATIENTS
Bibliographic record
Abstract
Objective: To study the correlation and concordance between MMSE, MoCA and MES in the evaluation of cognitive impairement in hypertensive patientsDesign and method: We conducted a prospective, multicenter, cross-sectional study including patients over 40 years of age with confirmed essential hypertension for more than 3 years, without prior diagnosis of cognitive decline. All participants underwent neuropsychological assessment using three tests. The cut-offs used to define CI for MMSE, MOCA and MES were scores <24, <26 and<75 respectively. The correlation was analyzed using Pearson correlation coefficient(r). For the concordance study, we calculated Cohen’s Kappa coefficient. Results: We included 256 patients with a mean age of 65±9 years and a gender ratio of 0.77. Assessment of cognitive performance revealed cognitive decline in 40.6% of patients(n=104) by MMSE, 75% of cases(n=192) by MoCA and 80.8% of cases(n=207) by MES. Among the 104 patients who had a cognitivi deficit diagnosed by the MMSE test, no patient had a normal MoCA or MES score. 84.4% of patients(n=76) with mild cognitive impairment diagnosed by MoCA had normal MMSE scores. 88.6% of patients(n=52) with mild cognitive impairment diagnosed by MES had normal MMSE scores. We found a statistically significant positive correlation between MMSE and MoCA (r=0.86, p< 0.001), MMSE and MES (r=0.82, p<0.001) and MoCA and MES (r=0.84, p<0.001)(Figure1). Our study also showed fair agreement between MMSE and MoCA(kappa=0.367), MMSE and MES (kappa=0.275) and substantial agreement between MoCA and MES (kappa=0.627). Conclusions: Cognitive disorders were frequent in hypertensive patients. Our study showed a good correlation between the three tests, a fair agreement between MMSE and MES and a substantial agreement between MoCA and MES. Further studies are needed to validate and include MES in screening for cognitive decline in hypertensive patients in order to define the best tools for early prevention.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".