Introducing Two Novel Indices for Evaluating Coronary Artery Stenosis: Athero-Inflammatory Index and Athero-Inflammatory Glucose Index.
Creators
- 1. Applied Biomedical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
- 2. International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, Iran.
- 3. Department of Cardiology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
- 4. Department of Health Education and Health Promotion, Faculty of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
- 5. Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
- 6. Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
- 7. Division of Medical Education, Brighton and Sussex Medical School, Brighton, UK.
Description
We investigated the association of two novel indices, the athero-inflammatory (AI) index and athero-inflammatory glucose (AIG) index, with coronary artery stenosis (CAS).
In this case-control study, the cases were grouped as angiography (+) and angiography (-) according to the angiographic results. The control group comprised subjects who attended clinics for routine check-ups or pre-employment medical assessments. The AI index and AIG index were compared between the groups using ANOVA. Binary logistic regression (LR) was performed to find the association of the indices with angiography (+). Receiver operating characteristic (ROC) curve analysis was used to establish the cut-off values in differentiating angiography (+) from angiography (-) and healthy subjects. p < 0.05 were considered statistically significant.
Among a total of 2326 participants (761 angiography (+), 406 angiography (-), and 1159 controls), the AI index and AIG index were significantly different between the groups (p < 0.001). In LR analysis, after adjustment for potential confounders, the AI index and AIG index were independently associated with angiography (+). ROC curve analysis showed that the AI index (AUC: 0.895; 95% CI: 0.880, 0.908; p < 0.0001) and AIG index (AUC: 0.918; 95% CI: 0.905, 0.930; p < 0.0001) performed better diagnostic performance in differentiating angiography (+) from healthy subjects.
AI index demonstrated higher AUC compared to other biomarkers in differentiating angiography (+) from angiography (-) and healthy subjects. If it combines with fasting glucose (AIG index), it is a promising indicator for the identification of the CAS particularly from a healthy population, with a promising AUC.
© 2025 The Author(s). Journal of Clinical Laboratory Analysis published by Wiley Periodicals LLC.
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References
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