Early detection of the risk of cognitive disorders
Bibliographic record
Abstract
BACKGROUND: Cognitive disorders are a relevant problem in an aging population. Research shows a wide range of data on the prevalence of cognitive disorders in the general population. Thus, more studies on the prevalence of cognitive disorders and assessment of the risks of their development are necessary, which will determine the burden on the regional healthcare system. AIM: To examine the prevalence of cognitive impairment in an outpatient multidisciplinary clinic setting and determine the risk ratios for cognitive deficits in different age groups. MATERIALS AND METHODS: The Montreal Cognitive Assessment Scale was used in the screening of people aged 4590 years. RESULTS: Cognitive dysfunction was noted in 20.0% of patients in the group aged 4559 years, 33.1% in the group aged 6074 years, and 79.6% in the group aged 7590 years. The average results on the assessment of cognitive functions of persons aged 4559 (27.10.3) and 6074 (26.20.2) years corresponded to the norm, and the value in persons aged 7590 (23.60.3) years was below the norm. In groups aged 6074 and 7590 years, the prevalence of cognitive dysfunction was comparable between men and women. Cognitive impairments in men aged 4559 years were recorded 2.5 times more often than that in women. The risk of cognitive disorders in the second group (aged 6074 years) relative to that in the first group (aged 4559 years) is insignificant (relative risk [RR], 1.21). In the third group (aged 7590 years), the probability of cognitive disorders is significantly higher than that in the second group (RR=2.40) and nearly five times higher than that in the first group (RR=4.86). CONCLUSION: Sex- and age-stratified screening indicators for assessing cognitive functions and the RRs of developing cognitive disorders in older age groups make it possible to plan for diagnostic, therapeutic, and preventive measures in mental health.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".