Relationship between syntax score and leukoglycemic index in acute coronary syndrome patients

Introduction Inflammation plays a central role in the pathophysiology of atherosclerosis, and early diagnosis and risk stratification in acute coronary syndromes (ACS) directly influence clinical outcomes. The leuko-glycemic index (LGI), calculated from leukocyte count and blood glucose levels, is a simple and cost-effective parameter with potential prognostic value in CAD. This study aimed to evaluate the relationship between LGI and the SYNTAX score, an established measure of CAD complexity, to assess the feasibility of predicting CAD severity through a non-invasive approach. Methods The relationship between LGI and SYNTAX score was evaluated using Pearson correlation analysis. Logistic and linear regression analyses were performed to identify predictors of CAD prevalence, with p-values <0.05 considered statistically significant. Results Following exclusion criteria, a total of 552 patients diagnosed with ACS were included in the study. Patients were stratified into two groups based on SYNTAX score: Group I (SYNTAX=<22) and Group II (SYNTAX>22). The mean age was significantly higher in Group II (p<0.001). No statistically significant differences were observed between the groups in terms of gender, hypertension, hyperlipidemia, smoking status, or family history of CAD. LGI, HbA1c, and HDL levels were significantly higher in Group II compared to Group I (p:0.02, p:0.005, and p:0.037, respectively). SYNTAX score showed a significant positive correlation with LGI, glucose, and HbA1c levels (p:0.001 for all). Additionally, LGI was negatively correlated with ejection fraction (p<0.001). In the multiple linear regression analysis, age (B:0.134, p<0.001), LGI (B:0.214, p:0.002), HbA1c (B:0.0571, p:0.008), creatinine (B:2.879, p:0.046), and diastolic blood pressure (B:–0.072, p:0.008) were independently associated with SYNTAX score.In the final step, logistic regression analysis was performed to identify the predictors of moderate-to-high SYNTAX scores. Initially, in the univariate analysis, the extent of coronary artery disease (CAD) was assessed using the Leukocyte Glucose Index (LGI) (OR: 1.060; 95% CI: 1.023–1.098; p=0.001).In the multivariate regression analysis, LGI, age, HbA1c, and creatinine were included as variables. Age (OR: 1.020; 95% CI: 1.002–1.038; p=0.033), HbA1c (OR: 1.385; 95% CI: 1.121–1.710; p=0.002), and LGI (OR: 1.046; 95% CI: 1.004–1.088; p=0.030) were found to be independent risk factors significantly associated with moderate-to-high SYNTAX scores. Conclusion This is the first study in the literature to evaluate the relationship between the SYNTAX score and the leukoglycemic index (LGI). LGI, as a combined indicator of inflammation and metabolic stress, may serve as a potential parameter for predicting the extent of coronary artery disease (CAD). Due to its simplicity and low cost, LGI may provide clinically valuable insights into CAD burden prior to invasive procedures.