Prevalence of dementia and mild cognitive impairment among older Albanian patients detected by different screening tools
Bibliographic record
Abstract
Rationale, aims and objectives: Recent studies have identified significant gaps in dementia´s epidemiology, especially regarding low- and middle-income countries. The aim of our study was to estimate the prevalence of mild cognitive impairment (MCI) and dementia by applying different tests among older Albanian patients and to find correlates with socio-demographic and medical factors. Method: Study population consisted of older people (60 years or more) who visited primary healthcare centers in two Albanian cities (Shkoder and Tirana). The MoCA (Montreal Cognitive Assessment), MoCA B (Basic) and the mini-cog were translated and applied by two trained pharmacists. A predictive multivariate logistic regression analysis was conducted. Degree of agreement between the MoCA and mini-cog tools was assessed using Kappa statistic. Results: A total of 206 participants with a mean age of 68,8 years old (SD 5.65), almost equally distributed among the two cities, were included in our study. A high prevalence of dementia and MCI was detected with MoCA, respectively 19,42 % and 93,20 %. The latter was 20,39 % with mini-cog. Multivariate regression analysis showed that men had an elevated risk for MCI (OR 5,31; 95% CI 1,40 – 20,15), as well as patients from Shkoder (OR 14,48; 95% CI 1,11 – 4,53), when MoCA detected MCI. According to mini-cog, more than 7 years of education acted as a protective factor for MCI (OR 0,12; 95% CI, 0,05 – 0,33), whereas having 1 to 6 years of education was a risk factor. For each year increase of age the risk of MCI was 1,16 times higher. The degree of agreement between the two tools was poor with Kappa 2.38 (SD 1,87). Conclusion: The results of these tests may help in selecting individuals for more specialised examination, in order to facilitate early diagnosis of dementia and MCI among Albanian older patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 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".