Abstract
This research aims to investigate correlations between the neutrophil-to-lymphocyte*platelet (NLPR) ratio combined with lipid parameters and coronary artery disease (CAD), and to assess the value of these indicators in predicting the severity of coronary atherosclerosis in the Chinese population. This study included 474 Chinese patients aged 28 to 88 years who underwent coronary angiography (CAG). Patients were grouped by NLPR, residual cholesterol (RC), and low-density lipoprotein/high-density lipoprotein (LDL/HDL) levels. CAD was determined via CAG and defined as stenosis of ≥50% in at least one major coronary artery. The Gensini score was calculated to assess the severity of coronary atherosclerosis. Patients with different NLPR levels showed differences in age (P<0.001), gender (P=0.002), hypertension (P<0.001), hyperlipidemia (P=0.003), Gensini scores (P=0.002), and severe stenosis (P<0.001). Multivariate logistic regression analysis revealed that NLPR was independently correlated with severe stenosis (OR, 1.275; 95% CI, 1.066 to 1.525; P=0.008). After adjusting for variables, individuals with elevated LDL/HDL alone, elevated NLPR alone, and both elevated LDL/HDL and NLPR demonstrated progressively increased risks of severe stenosis relative to those with low levels of LDL/HDL and NLPR. Furthermore, only individuals with both elevated RC and NLPR had a significantly higher risk of severe stenosis compared to those with lower RC and NLPR. NLPR-RC and NLPR-LDL/HDL, as complex indexes combining NLPR and lipid parameters, were independently associated with severe stenosis. The areas under the receiver operating characteristic (ROC) curve for NLPR, NLPR-RC, and NLPR-LDL/HDL were 0.630, 0.643, and 0.658, respectively. NLPR, NLPR-RC, and NLPR-LDL/HDL are independently associated with an increased risk of severe coronary artery stenosis. Compared with NLPR, the composite indicators, due to their higher sensitivity, might be applicable for screening severe coronary artery stenosis. However, these composite indicators still require prospective and multi-center validation before they can be widely applied.