The Correlation and Agreement of Montreal Cognitive Assessment, Mini-Mental State Examination and Abbreviated Mental Test in Assessing the Cognitive Status of Elderly People Undergoing Hemodialysis
Bibliographic record
Abstract
Background: Cognitive disorders are one of the most common disorders in elderly people with chronic renal failure. This study aimed to investigate the correlation and agreement of Montreal Cognitive Assessment (MoCA), Abbreviated Mental Test Score (AMTS), and Mini-Mental State Examination (MMSE) tests in assessing the cognitive status of elderly patients undergoing hemodialysis at Guilan University of Medical Sciences in north of Iran. Materials and Methods: This cross-sectional study was conducted on 84 elderly people undergoing hemodialysis. Inclusion criteria was having an age of 60 years old and older, hemodialysis treatment for at least 6 months, and having reading and writing skills. The Pearson correlation test, Intraclass Correlation Coefficient (ICC) test, and Bland–Altman plot were used for data analysis. Results: The majority of samples were in the age group of 60–65 years (28.57%) and the majority of them were male (66.66%). The results showed a significant positive correlation between MoCA and MMSE ( r = 0.69, p = 0.001), between MMSE and AMTS ( r = 0.64, p = 0.001), and between MoCA and AMTS tests ( r = 0.62, p = 0.001). The results also showed a weak agreement between MoCA and MMSE tests (ICC = −0.11, p = 0.633), between MMSE and AMTS tests (ICC = −0.007, p = 0.369), and between MoCA and AMTS tests (ICC = −0.001, p = 0.780). Conclusions: Based on the results, these tools seem to complement each other. The inconsistency between cognitive tests indicates a serious need to develop appropriate instruments for detecting cognitive disorders in elderly.
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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 | 0.000 |
| 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".