Cerebral Microbleeds Are Associated With Mild Cognitive Impairment in Patients With Hypertension
Bibliographic record
Abstract
Background Cerebral microbleeds (CMBs) are hypothesized downstream markers of brain damage caused by vascular and amyloid pathologic mechanisms. The aim of this study was to determine whether CMB count and location are associated with an increased risk for mild cognitive impairment (MCI) in patients with essential hypertension without a history of transient ischemic attack or stroke. Methods and Results In this cross‐sectional study, patients were prospectively enrolled from consecutive outpatients with essential hypertension 50 years and older at 3 centers in northern China. Generalized linear Poisson models were used to determine the association between the number and location of CMB s and MCI in patients with hypertension. The association of microbleeds with different cognitive domains was estimated using linear mixed models. The presence, number, and distribution of CMB s were greater in patients with hypertension who had MCI ( P <0.001). The presence of any CMB s, strictly lobar CMB s, and deep or infratentorial CMB s were all related to MCI after adjusting for age, sex, education, cardiovascular risk factors, body mass index, intima‐media thickness, the presence of silent lacunar infarctions, white matter lesion grade, and brain atrophy. Furthermore, the presence of multiple microbleeds (≥5) was associated with lower Montreal Cognitive Assessment total scores and worse performance on specific domains of cognitive tests, such as global cognitive function, information processing speed, and motor speed. Conclusions This study suggests that the presence of and a greater number of cerebral CMB s independently correlate with MCI in patients with essential hypertension without a history of transient ischemic attack or 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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".