The clinical risk factors of cerebral microbleeds and its relationship with cognitive dysfunction
Bibliographic record
Abstract
Abstract Background To explore the risk factors of cerebral microbleeds (CMBs) and the relationship between CMBs and cognitive impairment, and to provide more theoretical basis for the prevention and treatment of CMBs and vascular cognitive impairment. Method The CMBs group was classified according to the number and location. The basic clinical data were collected and the subjects all received the cognitive tests using Mini‐Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA) and the Neuropsychological Assessment Scales. Result A total of 138 subjects [71 participants in CMBs group and 67 as control] were enrolled, with an average age of 64.36±10.14 years. Ordered logistic regression analysis showed diastolic blood pressure (OR=1.05, 95% CI: 1.01‐1.09), history of ischemic stroke and transient ischemic attack (TIA) (OR=7.74, 95% CI: 2.74) ‐21.88), white matter hyperintensities (OR = 2.01, 95% CI: 1.46‐2.78) are independently associated with CMBs (P<0.05). Spearman correlation analysis showed that MMSE, MoCA, memory and executive function were correlated with CMBs (MMSE r=‐0.24, P=0.005; MoCA r=‐0.32, P<0.001; memory r=‐0.28, P=0.001; execution function r = ‐0.33, P<0.001). Multivariate linear regression analysis showed that MoCA score, memory and executive function were negatively correlated with CMBs number after adjusting for gender, age, years of education, other imaging biomarkers of cerebral small vessel disease and vascular risk factors (MoCA β=‐0.88, P=0.012; memory β = ‐0.22, P = 0.002; executive function β = ‐0.13, P = 0.001). As for the location, the results showed that the executive function of patients with strict lobe CMBs was lower than that of control group (P=0.046). In terms of speed and motion control, the differences between deep group and control group (P=0.037), deep group and infratentorial group (P=0.005) were statistically significant. Conclusion Diastolic blood pressure, history of ischemic stroke / TIA, white matter hyperintensities were independent risk factors for CMBs. CMBs are associated with cognitive dysfunction. CMBs in the strict lobe area are associated with the decline of executive function, and CMBs in the deep area are associated with the decline of speed and motor control ability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.003 | 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".