Cerebral Microbleeds as Predictors of Mortality
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Cerebral microbleeds (CMB) represent a common magnetic resonance imaging marker of cerebral small vessel disease, increasingly recognized as a subclinical marker of stroke and dementia risk. CMB detection may reflect the cumulative effect of vascular risk burden and be a marker of higher mortality. We investigated the relation of CMB to risk of death in community dwelling participants free of stroke and dementia. METHODS: We evaluated 1963 Framingham Original and Offspring Cohort participants (mean age 67 years; 54% women) with available brain magnetic resonance imaging and mortality data. Using Cox proportional hazards models, we related CMB to all-cause, cardiovascular, and stroke-related mortality. RESULTS: Participants with CMB (8.9%) had higher prevalence of cardiovascular risk factors and use of preventive medications. During a mean follow-up of 7.2±2.6 years, we observed 296 deaths. In age- and sex-adjusted analysis, CMB were associated with increased all-cause mortality (hazards ratio, 1.39; 95% confidence interval 1.03-1.88), a relation that was no longer significant after adjustment for cardiovascular risk and preventive medication use (hazards ratio, 1.15; 95% confidence interval, 0.82-1.63). CONCLUSIONS: CMBs may represent the deleterious effect of cardiovascular risk factors in the cerebral vasculature. Although their presence was associated with increased all-cause mortality, the effect was no longer present after accounting for vascular risk factors and preventive treatment use. Further studies are required to clarify the role of cardiovascular preventive therapies for prevention of mortality in persons with incidental detection of CMB.
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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 | 0.007 |
| 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 | 0.001 | 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".