Background: Low-Density Lipoprotein Cholesterol (LDL-C) is the primary lipid therapy target for coronary artery disease (CAD) patients after percutaneous coronary intervention (PCI). However, progression of coronary atherosclerosis occurs even LDL-C controlled well, some potentially important factors have been overlooked.
Objective: This study aims to elucidate the relationship between remnant lipoprotein particle cholesterol (RLP-C) and the progression of non-target lesions (NTLs) in patients with well-controlled lipid levels after PCI.
Methods: This retrospective study included 769 CAD patients who underwent PCI and followed up angiography within 6-24 months thereafter. Employing Multivariate Cox regression analysis, we assessed the correlation between RLP-C and NTLs progression. Based on the receiver operating characteristic curve analysis, we identified the optimal cutoff point for RLP-C, following which the patients were divided into two groups. Propensity score matching balanced confounding factors between groups, and Log-rank tests compared Kaplan-Meier curves for overall follow-up to assess NTLs progression.
Results: Multivariate Cox analysis revealed an independent association between RLP-C and NTLs progression when LDL-C was well-controlled. Additionally, the RLP-C level of 0.555 mmol/L was determined to be the best value for predicting NTLs progression. Following propensity score matching, Kaplan-Meier curves illustrated a significantly higher cumulative rate of NTLs progression in patients with RLP-C levels ≥0.555 mmol/L compared to the others (Log-rank P = 0.002). Elevated RLP-C levels were associated with high triglyceride concentrations, diabetes mellitus, and increased risk of revascularization.
Conclusions: This study illustrated the atherogenic impact of RLP-C in CAD patients. High RLP-C levels increased the risk of revascularization.
Keywords: atherosclerosis; non-target lesion; percutaneous coronary intervention; remnant lipoprotein particle cholesterol; triglyceride-rich lipoproteins.
© 2024 Liu, Teng, Li, Hu, Sha, Shen, Xia, Zhang and Liang.