Reduced Cognitive Assessment Scores Among Individuals With Magnetic Resonance Imaging–Detected Vascular Brain Injury
Bibliographic record
Abstract
Background and Purpose— Little is known about the association between covert vascular brain injury and cognitive impairment in middle-aged populations. We investigated if scores on a cognitive screen were lower in individuals with higher cardiovascular risk, and those with covert vascular brain injury. Methods— Seven thousand five hundred forty-seven adults, aged 35 to 69 years, free of cardiovascular disease underwent a cognitive assessment using the Digital Symbol Substitution test and Montreal Cognitive Assessment, and magnetic resonance imaging (MRI) to detect covert vascular brain injury (high white matter hyperintensities, lacunar, and nonlacunar brain infarctions). Cardiovascular risk factors were quantified using the INTERHEART (A Global Study of Risk Factors for Acute Myocardial Infarction) risk score. Multivariable mixed models tested for independent determinants of reduced cognitive scores. The population attributable risk of risk factors and MRI vascular brain injury on low cognitive scores was calculated. Results— The mean age of participants was 58 (SD, 9) years; 55% were women. Montreal Cognitive Assessment and Digital Symbol Substitution test scores decreased significantly with increasing age ( P <0.0001), INTERHEART risk score ( P <0.0001), and among individuals with high white matter hyperintensities, nonlacunar brain infarction, and individuals with 3+ silent brain infarctions. Adjusted for age, sex, education, ethnicity covariates, Digital Symbol Substitution test was significantly lowered by 1.0 (95% CI, −1.3 to −0.7) point per 5-point cardiovascular risk score increase, 1.9 (95% CI, −3.2 to −0.6) per high white matter hyperintensities, 3.5 (95% CI, −6.4 to −0.7) per nonlacunar stroke, and 6.8 (95% CI, −11.5 to −2.2) when 3+ silent brain infarctions were present. No postsecondary education accounted for 15% (95% CI, 12–17), moderate and high levels of cardiovascular risk factors accounted for 19% (95% CI, 8–30), and MRI vascular brain injury accounted for 10% (95% CI, −3 to 22) of low test scores. Conclusions— Among a middle-aged community-dwelling population, scores on a cognitive screen were lower in individuals with higher cardiovascular risk factors or MRI vascular brain injury. Much of the population attributable risk of low cognitive scores can be attributed to lower educational attainment, higher cardiovascular risk factors, and MRI vascular brain injury.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".