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Association of lipoprotein(a) levels with recurrent events in patients with coronary artery disease

医学 内科学 脂蛋白(a) 心肌梗塞 冠状动脉疾病 比例危险模型 冲程(发动机) 前瞻性队列研究 心脏病学 脂蛋白 胆固醇 机械工程 工程类
作者
Huihui Liu,Ye‐Xuan Cao,Jing‐Lu Jin,Huiwen Zhang,Qi Hua,Yanfang Li,Yuan‐Lin Guo,Cheng‐Gang Zhu,Na‐Qiong Wu,Ying Gao,Rui‐Xia Xu,Li-Feng Hong,Jian‐Jun Li
出处
期刊:Heart [BMJ]
卷期号:106 (16): 1228-1235 被引量:37
标识
DOI:10.1136/heartjnl-2020-316586
摘要

Whether lipoprotein(a) (Lp(a)) is a predictor for recurrent cardiovascular events (RCVEs) in patients with coronary artery disease (CAD) has not been established. This study, hence, aimed to examine the potential impact of Lp(a) on RCVEs in a real-world, large cohort of patients with the first cardiovascular event (CVE).In this multicentre, prospective study, 7562 patients with angiography-diagnosed CAD who had experienced a first CVE were consecutively enrolled. Lp(a) concentrations of all subjects were measured at admission and the participants were categorised according to Lp(a) tertiles. All patients were followed-up for the occurrence of RCVEs including cardiovascular death, non-fatal myocardial infarction and stroke.During a mean follow-up of 61.45±19.57 months, 680 (9.0%) RCVEs occurred. The results showed that events group had significantly higher Lp(a) levels than non-events group (20.58 vs 14.95 mg/dL, p<0.001). Kaplan-Meier analysis indicated that Lp(a) tertile 2 (p=0.001) and tertile 3 (p<0.001) groups had significantly lower cumulative event-free survival rates compared with tertile 1 group. Moreover, multivariate Cox regression analysis further revealed that Lp(a) was independently associated with RCVEs risk (HR: 2.01, 95% CI: 1.44 to 2.80, p<0.001). Moreover, adding Lp(a) to the SMART risk score model led to a slight but significant improvement in C-statistic (∆C-statistic: 0.018 (95% CI: 0.011 to 0.034), p=0.002), net reclassification (6.8%, 95% CI: 0.5% to 10.9%, p=0.040) and integrated discrimination (0.3%, 95% CI: 0.1% to 0.7%, p<0.001).Circulating Lp(a) concentration was indeed a useful predictor for the risk of RCVEs in real-world treated patients with CAD, providing additional information concerning the future clinical application of Lp(a).
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