P3–206: The prevalence of vascular cognitive impairment and its subtypes in Korean elders
Bibliographic record
Abstract
Vascular cognitive impairment (VCI) is defined as a cognitive impairment caused by or associated with vascular risk factors. It is a large heterogeneous group of disorders including vascular dementia (VD), mixed primary neurodegenerative dementia, and vascular mild cognitive impairment (vMCI). We investigated the prevalence of VCI and its subtypes in a Korean elderly population. This study was a part of the Korean Longitudinal Study on Health and Aging (KLoSHA) which had been conducted on the residents aged 65 years or older in Seongnam, Korea from September 2005 to August 2006. A simple random sample (N=1118) was drawn from the roster of 61,730 persons aged 65 years or older. Standardized clinical interviews, neurological and physical examinations and comprehensive neuropsychological assessments were administered. Diagnosis of vascular dementia was made according to NINDS-AIREN criteria. Diagnosis of mixed dementia was made according to DSM-IV-TR criteria. And, diagnosis of vMCI was made according to the MCI criteria proposed by the International Working Group with vascular risk factors (Modified Hachinski ischemic scale ≥ 4). Age- and sex-standardized prevalence rate of VCI was 4.4% (95% CI=2.9%-5.9%). Age- and sex-standardized prevalence of VD or mixed dementia was 1.4% (95% CI=0.6%-2.3%), and that of vMCI was 3.0% (95% CI=1.8%-4.3%). The prevalence of VCI increased with advancing age (2.3% in 65–69, 5.1% in 70–74, and 6.8% in 75 or older). Gender and educational level had no significant influence on the prevalence of VCI. The prevalence of VCI in Korean elders was comparable to other western countries (5% in Canada, 6.6% in UK) and older age was significantly associated with an increased risk of developing VCI. As operational criteria of VCI is still variable between studies, it is warranted to establish uniform operational criteria for VCI for ensuring validity and comparability in future researches.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".