Association between fibrinogen and cognitive impairment in patients with ischemic cerebrovascular disease
Bibliographic record
Abstract
Fibrinogen has been reported as a potential risk factor for vascular dementia (VaD). However, the association between fibrinogen and cognition in patients with ischemic cerebrovascular disease (ICVD) has not been studied adequately. We aimed to examine the association of fibrinogen with cognitive impairment among patients with ICVD and to test whether white matter hyperintensities (WMH) and brain atrophy play a role under the association. In this case-control study, ICVD patients were recruited from the Neurology Department. Cognitive function was assessed using the Montreal Cognitive Assessment. WMH and brain atrophy were quantified by brain magnetic resonance imaging (MRI). The associations of fibrinogen with cognition and MRI markers were investigated by conditional logistic regression models and generalized additive models. The risk of cognitive impairment increased with each unit increase in fibrinogen ( AOR = 1.92, 95% CI = 1.06 - 3.48). Individuals with fibrinogen levels > 4 g/L presented a substantially higher risk of cognitive impairment than those with fibrinogen levels of 2-4 g/L ( AOR = 5.72, 95% CI = 1.22- 26.82). Fibrinogen was negatively correlated with global cognitive function ( r s = -0.235) and visuospatial/executive function ( r s = -0.251). A negative correlation between fibrinogen and normal-appearing white matter (NAWM) volume was observed ( r s = -0.282). Fibrinogen is associated with cognitive impairment among patients with ICVD, and significantly negatively impacts global cognitive function and visuospatial/executive function. Furthermore, the negative correlation between fibrinogen and NAWM volume supports further exploration of potential mechanistic paths.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".