Clinical Relevance of Cortical Cerebral Microinfarcts on 1.5T Magnetic Resonance Imaging in the Late-Adult Population
Bibliographic record
Abstract
Background and Purpose: Cortical cerebral microinfarcts (CMIs) have been linked with dementia and impaired cognition in cross-sectional studies. However, the clinical relevance of CMIs in a large population-based setting is lacking. We examine the association of cortical CMIs detected on 1.5T magnetic resonance imaging with cardiovascular risk factors, cerebrovascular disease, and brain tissue volumes. We further explore the association between cortical CMIs with cognitive decline and risk of stroke, dementia, and mortality in the general population. Methods: Two thousand one hundred fifty-six participants (age: 75.7±5.9 years, women: 55.6%) with clinical history and baseline magnetic resonance imaging (January 2009–December 2013) were included from the Rotterdam Study. Cortical CMIs were graded based on a previously validated method. Markers of cerebrovascular disease and brain tissue volumes were assessed on magnetic resonance imaging. Cognition was assessed using a detailed neuropsychological test at baseline and at 5 years of follow-up. Data on incident stroke, dementia, and mortality were included until January 2016. Results: Two hundred twenty-seven individuals (10.5%) had ≥1 cortical CMIs. The major risk factors of cortical CMIs were male sex, current smoking, history of heart disease, and stroke. Furthermore, presence of cortical CMIs was associated with infarcts and smaller brain volume. Persons with cortical CMIs showed cognitive decline in Stroop tests (color-naming and interference subtasks; β for color-naming, 0.18 [95% CI, 0.04–0.33], P interaction ≤0.001 and β for interference subtask, 1.74, [95% CI, 0.66–2.82], P interaction ≤0.001). During a mean follow-up of 5.2 years, 73 (4.3%) individuals developed incident stroke, 95 (5.1%) incident dementia, and 399 (19.2%) died. People with cortical CMIs were at an increased risk of stroke (hazard ratio, 1.18 [95% CI, 1.09–1.28]) and mortality (hazard ratio, 1.09 [95% CI, 1.00–1.19]). Conclusions: Cortical CMIs are highly prevalent in a population-based setting and are associated with cardiovascular disease, cognitive decline, and increased risk of stroke and mortality. Future investigations will have to show whether cortical CMIs are a useful biomarker to intervene upon to reduce the burden of stroke.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".