Serum Folate Levels and Subsequent Adverse Cerebrovascular Outcomes in Elderly Persons
Bibliographic record
Abstract
Recent epidemiologic studies have shown an association between low serum folate levels and risk of vascular disease, including stroke and various types of vascular cognitive impairment. We examined data from the Canadian Study of Health and Aging (CSHA), a population-based, prospective 5-year investigation of the epidemiology of dementia among Canadians aged 65+ years. The risk of an adverse cerebrovascular event (including vascular dementia, vascular cognitive impairment, or fatal stroke) during follow-up, was assessed according to serum folate quartiles among subjects with no evidence of dementia at baseline (n = 369). After adjusting for certain covariates, including cardiovascular disease and nutritional indices, education, smoking and baseline cognitive status, the risk estimate for an adverse cerebrovascular event associated with the lowest folate quartile compared with the highest quartile was OR 2.42 (95% CI 1.04-5.61). Results from stratified analyses also showed that relatively low serum folate was associated with a significantly higher risk of an adverse cerebrovascular event among female (OR 4.02, 95% CI 1.37-11.81) but not male (OR 1.02, 95% CI 0.25-4.13) subjects. Among the total sample, there was a consistent trend toward poorer health and cognitive outcomes during follow-up (including mortality, cognitive decline and dementia) among those in the lowest folate quartile compared with the highest quartile. Low serum folate levels are independently associated with a significantly higher risk of an adverse cerebrovascular event, including vascular dementia and stroke death, among older, cognitively vulnerable persons.
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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 | 0.000 |
| 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 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".