The prevalence of mild cognitive impairment and its etiological subtypes in elderly Chinese
Bibliographic record
Abstract
BACKGROUND: Epidemiologic studies on mild cognitive impairment (MCI) are limited in China. METHODS: Using a multistage cluster sampling design, a total of 10,276 community residents (6096 urban, 4180 rural) aged 65 years or older were evaluated and diagnosed with normal cognition, MCI, or dementia. MCI was further categorized by imaging into MCI caused by prodromal Alzheimer's disease (MCI-A), MCI resulting from cerebrovascular disease (MCI-CVD), MCI with vascular risk factors (MCI-VRF), and MCI caused by other diseases (MCI-O). RESULTS: The prevalences of overall MCI, MCI-A, MCI-CVD, MCI-VRF, and MCI-O were 20.8% (95% confidence interval [CI] = 20.0-21.6%), 6.1% (95% CI = 5.7-6.6%), 3.8% (95% CI = 3.4-4.2%), 4.9% (95% CI = 4.5-5.4%), and 5.9% (95% CI = 5.5-6.4%) respectively. The rural population had a higher prevalence of overall MCI (23.4% vs 16.8%, P < .001). CONCLUSIONS: The prevalence of MCI in elderly Chinese is higher in rural than in urban areas. Vascular-related MCI (MCI-CVD and MCI-VRF) was most common.
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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 | 0.001 | 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".