Different Lipid Parameters in Predicting Clinical Outcomes in Chinese Statin-Naive Patients After Coronary Stent Implantation.
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ABSTRACT: Background: Low-density lipoprotein cholesterol (LDL-C) is a critical surrogate outcome for cardiovascular disease (CVD). Recent observational studies identified different predictive lipid parameters, but these have not been fully validated in the Chinese population. This study aimed to compare the predictive value of lipid parameters for cardiovascular outcomes in Chinese statin-naïve patients who underwent percutaneous coronary intervention (PCI). Methods: We retrospectively recruited statin-naïve patients who underwent PCI for stable angina and acute coronary syndrome at Sichuan Provincial People's Hospital between 1 January 2016 and 31 December 2017. A follow-up was conducted via outpatient visits or telephone. We divided patients into three groups based on lipid parameter tertiles. We calculated the hazard ratios (HRs) of the highest and lowest tertiles for major adverse cardiovascular events (MACEs) using multivariate Cox proportional hazards regression. We compared the association strength of lipid parameters with MACEs using the HR of non-LDL-C lipid parameters relative to LDL-C. Results: Among 445 included patients, the highest LDL-C, LDL-C/high-density lipoprotein cholesterol (HDL-C), atherosclerosis index, and non-HDL-C level tertiles were associated with an average increase of 165% (HR 2.65, confidence interval [CI] 1.26 to 5.61; P = 0.01), 324% (HR 4.24, CI 1.89 to 9.52; P < 0.001), 152% (HR 2.52, CI 1.22 to 5.22; P = 0.01), and 125% (HR 2.25, CI 1.09 to 4.64; P = 0.01) in the hazard of composite CVD, respectively. Lipoprotein (a) levels did not show a significant association with the endpoints. Except for LDL-C/HDL-C, different lipid parameter HR ratios were <1.0; none were statistically significant. Conclusion: Compared with non-LDL-C lipid parameters, LDL-C acts better predictive value for cardiovascular outcomes in general Chinese statin-naïve post-PCI patients.
SUBMITTER: Zeng L
PROVIDER: S-EPMC8007761 | biostudies-literature |
REPOSITORIES: biostudies-literature
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