Prognostic impact of estimated remnant-like particle cholesterol in patients with differing glycometabolic status: an observational cohort study from China
Qi Zhao, Tingyu Zhang, Yujing Cheng, Yue Ma, Ying-Kai Xu, Jiaqi Yang, Yu-Jie Zhou
Abstract
BACKGROUND: It is uncertain whether estimated remnant-like particle cholesterol (RLP-C) could predict residual risk in patients with different glycometabolic status. This study aimed to evaluate the relationship between estimated RLP-C and adverse prognosis in patients with non-ST-segment elevation acute coronary syndrome (NSTE-ACS) treated with percutaneous coronary intervention (PCI) and to identify the potential impact of glycometabolism on the predictive value of estimated RLP-C. METHODS: The study assessed 2419 participants with NSTE-ACS undergoing PCI at Beijing Anzhen Hospital from January to December 2015. Estimated RLP-C was calculated as follows: total cholesterol (TC) minus low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C). The adverse events included all-cause death, non-fatal myocardial infarction (MI), and ischemia-driven revascularization. RESULTS: Estimated RLP-C was prominently associated with adverse prognosis in the total population [hazard ratio (HR) 1.291 per 1-SD increase, 95% confidence interval (CI) 1.119-1.490, P < 0.001], independent of confounding risk factors. However, subgroup analysis showed that increasing estimated RLP-C was related to a higher risk of adverse events in the diabetic population only [HR 1.385 per 1-SD increase, 95% CI 1.183-1.620, P < 0.001]. Estimated RLP-C failed to be a significant determinant of adverse prognosis in non-diabetic and pre-diabetic subgroups. The addition of estimated RLP-C to a baseline model including traditional risk factors enhanced the predictive performance both in total and diabetic populations. CONCLUSIONS: High estimated RLP-C level is a significant predictor for recurrent adverse events in patients with diabetes and NSTE-ACS treated with PCI.