The Value of Inflammation indexes in Predicting Patency of Saphenous Vein Grafts in Patients With Coronary Artery Bypass Graft Surgery

Aim:Our study aimed to investigate the predictive values of inflammation markers in predicting postoperative saphenous vein graft patency in patients who underwent coronary artery bypass grafting (CABG). Method: We retrospectively analyzed 89 patients who undergone CABG, and 49 patients diagnosed with non-critical coronary artery disease (less than <= 50% stenosis) on coronary angiography were included in the study as a control group. Eighty-nine patients who underwent CABG were divided into two groups according to the presence of 50% or more stenosis in saphenous vein grafts. In these three groups of patients, neutrophil to lymphocyte ratio (NLR), derived NLR (dNLR; neutrophils/white blood cells-neutrophils), platelet to lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR), systemic inflammation response index (SIRI; neutrophils x monocytes/lymphocytes), systemic inflammation index (SII; platelet x neutrophil/lymphocyte), and the aggregate index of systemic inflammation (AISI; neutrophil x platelet x monocyte/lymphocyte ratio) were calculated from blood LesLs. The primary endpoint was more than 50% of saphenous vein stenosis or occlusion, and the aim is to predict this saphenous vein graft disease by inflammation indexes. Results: The groups were similar in terms of the frequency of stroke, diabetes mellitus, and chronic obstructive pulmonary disease. The frequency of heart failure and hypertension was higher in group 2 (p=0.045, p=0.005), respectively. Multivariate logistic regression analysis showed that LMR and NLR levels were independent predictors of saphenous vein graft disease (SVGD; OR: 0.896; 95%CI: 0.465-0.957; P<0.001) , (OR: 0.592; 95%CI: 0.450-0.875; P=0.034, respectively).The cut-off value of the LMR <2.625 was associated with 78.4% sensitivity and 78% specificity to predict saphenous vein graft disease in patients with CABG. Conclusion: LMR and NLR may be useful predictors for SVGD.