The Mediating Effect of Carotid Plaque Vulnerability in the Association Between NMLR and Cognitive Impairment
Bibliographic record
Abstract
Objective: This study aims to explore the mediating role of carotid plaque vulnerability in the association between the neutrophil-plus-monocyte-to-lymphocyte ratio (NMLR) and cognitive impairment in patients with carotid artery stenosis (CAS). Methods: A total of 211 CAS patients who underwent carotid endarterectomy (CEA) were retrospectively enrolled and divided into stable plaque (n = 104) and vulnerable plaque (n = 107) groups based on postoperative pathological examination. Clinical data, laboratory indicators (including neutrophil, monocyte, and lymphocyte counts), and Montreal Cognitive Assessment (MoCA) scores were collected. Multivariate logistic regression and mediation analysis were used to evaluate the relationships among NMLR, plaque vulnerability, and cognitive function. Results: Patients with vulnerable plaques had significantly higher NMLR and lower MoCA scores compared to those with stable plaques (both P < 0.001). Multivariate analysis identified NMLR as an independent risk factor for both plaque vulnerability (OR = 4.51, P < 0.001) and cognitive impairment (OR = 4.22, P < 0.001). Mediation analysis revealed that plaque vulnerability partially mediated the association between NMLR and cognitive function, accounting for 10.58% of the total effect. The area under the ROC curve of NMLR for predicting plaque vulnerability was 0.80. Conclusion: NMLR is significantly associated with carotid plaque vulnerability and cognitive impairment. Plaque vulnerability mediates part of the effect of NMLR on cognitive function, suggesting that NMLR may serve as a novel inflammatory biomarker for assessing plaque stability and cognitive risk in CAS patients, providing a potential target for early intervention in vascular cognitive impairment.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".