Montreal Cognitive Assessment Arabic version: Reliability and validity prevalence of mild cognitive impairment among elderly attending geriatric clubs in Cairo
Bibliographic record
Abstract
AIM: Mild cognitive impairment (MCI) is a clinical label which includes elderly subjects with memory impairment and with no significant daily functional disability. MCI is an important target for Alzheimer's dementia prevention studies. Data on the prevalence and incidence of MCI varies greatly according to cultural difference. The first aim of this study was to assess the reliability and validity of Montreal Cognitive Assessment (MoCA) Arabic version in MCI detection. The second was to determine the prevalence of MCI among apparently healthy elderly people attending geriatric clubs in Cairo. METHODS: In stage I reliability & validity of MoCA Arabic version were assessed in reference to Cambridge Cognitive Examination (CAMCOG). In stage II prevalence of MCI was estimated using Arabic MoCA among apparently healthy elderly attending geriatric clubs. These geriatric clubs were randomly selected from different regions in Cairo governorate. RESULTS: Test-retest reliability data of the Arabic MoCA were collected approximately 35.0 +/- 17.6 days apart. The mean change in Arabic MoCA scores from the first to second evaluation was 0.9 +/- 2.5 points, and correlation between the two evaluations was high (correlation coefficient = 0.92, P < 0.001). The internal consistency of the Arabic MoCA was good, yielding a Cronbach's alpha on the standardized items of 0.83. In diagnosing mild cognitive impairment, the Arabic MoCA showed 92.3% sensitivity and 85.7% specificity. The prevalence of MCI among elderly subjects attending geriatric clubs in Cairo is 34.2% and 44.3% of healthy men and women, respectively. CONCLUSION: Older age, female sex and less education are the independent risk factors for MCI among apparently healthy elderly subjects attending geriatric clubs in Cairo.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".