Parameters of complete blood count, lipid profile and their ratios in predicting obstructive coronary artery disease in patients with non-ST elevation acute coronary syndrome

Abstract

Aim. To evaluate the predictive potential of the parameters of complete blood count (CBC), lipid profile and their ratios for predicting obstructive coronary artery disease (oCAD) in patients with non-ST elevation acute coronary syndrome (NSTEACS).Material and methods. The study included 600 patients with NSTE-ACS with a median age of 62 years who underwent invasive coronary angiography (CA). Two groups were formed, the first of which consisted of 360 (60%) patients with oCAD (stenosis ≥50%), and the second — 240 (40%) with coronary stenosis <50%. The clinical and functional status of patients before CAG was assessed by 33 parameters, including parameters of CBC, lipid profile and their ratio. For statistical processing and data analysis, the Mann-Whitney, Fisher, chi-squared tests, univariate logistic regression (LR) were used, while for the creation of predictive models, multivariate LR (MLR) was used. The quality was assessed by 4 metrics: area under the ROC curve (AUC), sensitivity (Se), specificity (Sp), and accuracy (Ac).Results. CBC and lipid profile analysis made it possible to identify factors that are linearly and non-linearly associated with oCAD. Univariate LR revealed their threshold values with the highest predictive potential. The quality metrics of the best prognostic model developed using MLR were as follows: AUC — 0,80, Sp — 0,79, Ac — 0,76, Se — 0,78. Its predictors were 8 following categorical parameters: age >55 years in men and >65 years in women, lymphocyte count (LYM) <19%, hematocrit >49%, immune-inflammation index >1000, high density lipoprotein cholesterol (HDL-C) to low density lipoprotein cholesterol (LDL-C) ratio <0,3, monocyte (MON)-to-HDL-C ratio >0,8, neutrophil (NEUT)-to-HDL-C ratio >5,7 and NEUT/LYM >3. The relative contribution of individual predictors to the development of end point was determined.Conclusion. The predictive algorithm (model 9), developed on the basis of MLR, showed a better quality metrics ratio than other models. The following 3 factors had the dominant influence on the oCAD risk: HDL-C/LDL-C (38%), age of patients (31%), and MON/HDL-C (14%). The influence of other factors on the oCAD risk was less noticeable.