Qianxiao Bao,1 Tao Liu,2 Hui Song,3 Weiguo Bao,4 Weiguo Fan5 

1Queen Mary College, Nanchang University, Nanchang, Jiangxi, 330031, People’s Republic of China; 2Medical Experimental Diagnostic Center; Administrative Office, Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250013, People’s Republic of China; 3Department of Cardiology, Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250013, People’s Republic of China; 4Department of Cardiovascular Surgery, The Second Hospital of Shandong University, Jinan, Shandong, 250013, People’s Republic of China; 5Department of Cardiology, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, 330000, People’s Republic of China

Correspondence: Weiguo Fan, Department of Cardiology, The Second Affiliated Hospital of Nanchang University, No. 1, Mingde Road, Nanchang, Jiangxi, 330000, People’s Republic of China, Email fwg18166045656@126.com Weiguo Bao, Department of Cardiovascular Surgery, The Second Hospital of Shandong University, No. 247 Beiyuan Street, Jinan, Shandong, 250013, People’s Republic of China, Email weiguo202020@163.com

Background: Coronary artery disease (CAD) remains a leading cause of morbidity and mortality, with inflammation playing a central role in the transition from Chronic Coronary Syndrome (CCS) to acute coronary syndrome (ACS). This study investigates the predictive value of multiple inflammatory indices in assessing the risk of ACS.
Methods: This retrospective case-control study included 1, 116 patients aged 60 and older diagnosed with CCS or ACS between June 2018 and June 2023. Patients were grouped into CCS and ACS categories, with inflammatory indices derived from hematological parameters. Key indices included the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic inflammatory response index (SIRI; calculated as monocyte count × neutrophil count / lymphocyte count), systemic immune-inflammation index (SII; platelet count × neutrophil count / lymphocyte count), and C-reactive protein-albumin-lymphocyte (CALLY) index (albumin × lymphocyte count / [C-reactive protein × 10]). Multivariate logistic regression and receiver operator characteristic (ROC) curve analyses assessed the indices’ predictive capacity for ACS.
Results: The ACS group demonstrated significantly elevated levels of inflammatory markers such as White Blood Cell Count (WBC), neutrophils, and monocytes. Among inflammatory indices, PLR, SIRI, and the SII were significant predictors of ACS. PLR had the highest area under the curve (AUC=0.841), with strong sensitivity (0.828) and specificity (0.747). SIRI followed with notable predictive efficacy (AUC=0.802). Increased BMI, diabetes, and adverse lipid profiles also correlated with heightened ACS risk.
Conclusion: PLR, SIRI, and SII emerge as valuable prognostic markers for ACS, reflecting the underlying inflammatory processes central to CAD progression. Their integration into clinical assessments could improve risk stratification and guide interventions. Future research should aim to elucidate mechanisms linking systemic inflammation to coronary events and explore therapeutic strategies targeting these pathways.

Keywords: coronary artery disease, inflammatory biomarkers, acute coronary syndrome, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, systemic inflammatory response index