Blood immune inflammatory indicators predict prognosis in patients with coronary artery disease

Abstract

Background

The relationship between the combined hematological parameters and echocardiography and long-term prognosis in patients with coronary artery disease (CAD) remains unclear.

Methods

We examined the ability of hematological parameters to predict all-cause death and major adverse cardiovascular events (MACE) based on Lasso Cox regression analysis. The significant predictors of hematological parameters from the Lasso Cox model were analyzed via multivariate Cox regression analysis and by adjusting for echocardiographic data. We calculated the continuous net reclassification improvement (cNRI) and integrated discrimination improvement (IDI) of the hematological parameters to assess the improvement in prediction.

Results

A low hemoglobin and lymphocyte ratio and high hematocrit, red blood cell distribution width-coefficient of variation, and monocyte ratio significantly increased the risk of MACE and death in CAD patients. Neutrophil-to-lymphocyte ratio was associated with MACE but not death in CAD patients. After adjustment for echocardiographic parameters, hemoglobin, hematocrit, and lymphocyte ratio remained independently related to death and MACE. The addition of hematological and echocardiographic parameters to the Framingham risk score model significantly improved the area under the curve of mortality (0.794 vs. 0.713, p = 0.0007) and reclassification with cNRI of 30.6% (p = 0.002) and IDI of 0.055 (p < 0.001). Mendelian randomization analyses identified that fibrinogen and neutrophil-to-lymphocyte ratio were associated with increased brain natriuretic peptide and decreased left ventricular ejection fraction.

Conclusions

These findings suggest that the blood immune inflammatory indicators fibrinogen and neutrophil-to-lymphocyte ratio were causally associated with the risk of heart failure after CAD. The combination of hematological biomarkers and echocardiography parameters as predictor variables is a useful predictive tool for all-cause mortality in patients with CAD.