Elevated Plasma Level of D-dimer Predicts the High Risk of Early Cognitive Impairment in Type 2 Diabetic Patients as Carotid Artery Plaques become Vulnerable or Get Aggravated
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: D-dimer prompts fibrinolysis system, which is involved in Alzheimer's disease and the complications of type 2 diabetic patients, especially among those with carotid artery plaques. Hence, this study aims to investigate the role of D-dimer in early cognitive impairment among type 2 diabetic patients with carotid artery plaques. METHODS: A total of 175 Chinese patients with type 2 diabetes were recruited and divided into two groups according to the Montreal Cognitive Assessment score. Demographic data were collected, plasma D-dimer was tested through VIDAS D-dimer New, neuropsychological tests were examined, and carotid artery plaques were detected by ultrasound and further stratified by vulnerability and level. RESULTS: A total of 67 types 2 diabetic patients with Mild Cognitive Impairment (MCI) displayed significantly increased plasma D-dimer levels compared with their health-cognition controls (p = 0.011). Plasma D-dimer concentration was negatively related with Digit Span Test scores in diabetic patients with vulnerable plaques (r=-0.471, p=0.023) and Stroop Color Word Test C (number) in diabetic patients with stable plaques (r=-0.482, p<0.001). Multivariable regression analysis further showed that D-dimer concentration was an independent factor of diabetic MCI with carotid artery plaque (p=0.005), and D-dimer concentration especially contributed to the high risk of MCI with vulnerable plaques (p=0.028) or high levels of carotid plaque (p=0.023). CONCLUSION: Elevated D-dimer level predicts the high risk of early cognitive impairment in type 2 diabetic patients with carotid artery plaques, especially vulnerable plaques or high levels of carotid plaques.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 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".