Abstract 223: Elevated Mip-1b, Peripheral Arterial Disease, and Antiplatelet Medication Use Predict Cognitive Function Among Asymptomatic Patients Referred for Carotid Doppler Evaluation
Bibliographic record
Abstract
Background: Vascular cognitive impairment (VCI) includes the entire spectrum of cognitive disorders associated with cerebrovascular disease, ranging from mild cognitive impairment to vascular dementia. Our incomplete understanding of vascular and inflammatory mechanisms involved limits the ability to prevent cognitive impairment. We explored whether inflammation may be associated with cognitive function among subjects at risk for cerebrovascular disease. Methods: Sixty consecutive patients without dementia or stroke referred for carotid Doppler evaluation were screened for cognitive impairment using the Montreal Cognitive Assessment (MoCA). Serum was obtained for measurement of inflammatory markers using the Bio-Plex Pro Human Cytokine 27-plex Assay kit (Bio-Rad Laboratories). Hs-CRP was also measured. Inflammatory markers were analyzed according to quartiles of marker concentration for association with MoCA score. Backward stepwise regression was conducted to find the best combination of predictors. Markers having bivariate correlations at the 0.25 significance level were included as potential predictors. Relevant demographic and comorbid factors were also considered. Variables with p values <0.05 were retained in the final model. Results: Fifty-eight percent of patients (35/60) had cognitive impairment (MoCA<26, range 19-25). Stepwise multiple regression analysis revealed inverse correlations between three variables and MoCA scores: Macrophage Inflammatory Protein-1b - MIP-1b (b= -0.99, SE = 0.30, p=0.0016), use of antiplatelet medications (b= -1.96, SE = 0.93, p=0.039), and peripheral arterial disease - PAD (b= -1.53, SE = 0.73, p=0.041), overall model R2 = 0.26, F = 6.5, p=0.0007. Conclusions: Elevated MIP-1b, presence of PAD, and use of antiplatelet medications were associated with lower cognitive performance among patients at risk for cerebrovascular disease. The range of abnormal MoCA scores (19-25) and high prevalence of vascular risk factors among this group suggest that the cognitively impaired subjects have early VCI. These data suggest that MIP-1b should be further explored as a potential link to mechanisms for development of VCI.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".