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胱抑素C与左心室射血分数比值作为冠心病患者不良结局的新型预测指标:一项前瞻性队列研究

Cystatin C to Left Ventricular Ejection Fraction Ratio as a Novel Predictor of Adverse Outcomes in Patients with Coronary Artery Disease: A Prospective Cohort Study.

作者信息

Ning Yi, Wang Kai-Yang, Min Xuan, Hou Xian-Geng, Wu Ting-Ting, Ma Yi-Tong, Xie Xiang

机构信息

Department of Cardiology, First Affiliated Hospital of Xinjiang Medical University, 830011 Urumqi, Xinjiang, China.

出版信息

Rev Cardiovasc Med. 2023 Sep 18;24(9):260. doi: 10.31083/j.rcm2409260. eCollection 2023 Sep.

Abstract

BACKGROUND

While both cystatin C and left ventricular ejection fraction (LVEF) revealed established prognostic efficacy in coronary artery disease (CAD), the relationship between cystatin C/left ventricular ejection fraction ratio (CLR) and adverse clinical outcomes among patients with CAD following percutaneous coronary intervention (PCI) remains obscure, to date. Therefore, we sought to assess the predictive efficacy of CLR among CAD patients who underwent PCI in current study.

METHODS

A total of 14,733 participants, including 8622 patients with acute coronary syndrome (ACS) and 6111 patients with stable coronary artery disease (SCAD), were enrolled from a prospective cohort of 15,250 CAD patients who underwent PCI and were admitted to the First Affiliated Hospital of Xinjiang Medical University from 2016 to 2021. The primary outcome of this study was mortality, including all-cause mortality (ACM) and cardiac mortality (CM). The secondary outcomes were major adverse cardiovascular events (MACEs), major adverse cardiac and cerebrovascular events (MACCEs) and nonfatal myocardial infarction (NFMI). For CLR, the optimal cut-off value was determined by utilizing receiver operating characteristic curve analysis (ROC). Subsequently, patients were assigned into two groups: a high-CLR group (CLR 0.019, n = 3877) and a low-CLR group (CLR 0.019, n = 10,856), based on optimal cut-off value of 0.019. Lastly, the incidence of outcomes between the two groups was compared.

RESULTS

The high-CLR group had a higher incidence of ACM (8.8% vs. 0.9%), CM (6.7% vs. 0.6%), MACEs (12.7% vs. 5.9%), MACCEs (13.3% vs. 6.7%), and NFMIs (3.3% vs. 0.9%). After adjusting for confounders, multivariate Cox regression analyses revealed that patients with high-CLR had an 8.163-fold increased risk of ACM (HR = 10.643, 95% CI: 5.52520.501, 0.001), a 10.643-fold increased risk of CM (HR = 10.643, 95% CI: 5.52520.501, 0.001), a 2.352-fold increased risk of MACE (HR = 2.352, 95% CI: 1.7543.154, 0.001), a 2.137-fold increased risk of MACCEs (HR = 2.137, 95% CI: 1.6112.834, 0.001), and a 1.580-fold increased risk of NFMI (HR = 1.580, 95% CI: 1.273~1.960, 0.001) compared to patients with low-CLR.

CONCLUSIONS

The current study indicated that a high CLR is a novel and powerful predictor of adverse long-term outcomes in CAD patients who underwent PCI, and that, it is a better predictor for patients wtih SCAD and ACS.

CLINICAL TRIAL REGISTRATION

NCT05174143, http://Clinicaltrials.gov.

摘要

背景

虽然胱抑素C和左心室射血分数(LVEF)在冠状动脉疾病(CAD)中均显示出既定的预后疗效,但迄今为止,CAD患者经皮冠状动脉介入治疗(PCI)后,胱抑素C/左心室射血分数比值(CLR)与不良临床结局之间的关系仍不清楚。因此,在本研究中,我们试图评估CLR对接受PCI的CAD患者的预测疗效。

方法

从2016年至2021年在新疆医科大学第一附属医院接受PCI并入院的15250例CAD患者的前瞻性队列中,共纳入14733名参与者,包括8622例急性冠状动脉综合征(ACS)患者和6111例稳定冠状动脉疾病(SCAD)患者。本研究的主要结局是死亡率,包括全因死亡率(ACM)和心脏死亡率(CM)。次要结局是主要不良心血管事件(MACE)、主要不良心脑血管事件(MACCE)和非致命性心肌梗死(NFMI)。对于CLR,通过利用受试者工作特征曲线分析(ROC)确定最佳临界值。随后,根据最佳临界值0.019,将患者分为两组:高CLR组(CLR≥0.019,n = 3877)和低CLR组(CLR<0.019,n = 10856)。最后,比较两组之间结局的发生率。

结果

高CLR组的ACM发生率(8.8%对0.9%)、CM发生率(6.7%对0.6%)、MACE发生率(12.7%对5.9%)、MACCE发生率(13.3%对6.7%)和NFMI发生率(3.3%对0.9%)更高。在调整混杂因素后,多因素Cox回归分析显示,与低CLR患者相比,高CLR患者发生ACM的风险增加8.163倍(HR = 10.643,95%CI:5.52520.501,P<0.001),发生CM的风险增加10.643倍(HR = 10.643,95%CI:5.52520.501,P<0.001),发生MACE的风险增加2.352倍(HR = 2.352,95%CI:1.7543.154,P<0.001),发生MACCE的风险增加2.137倍(HR = 2.137,95%CI:1.6112.834,P<0.001),发生NFMI的风险增加1.580倍(HR = 1.580,95%CI:1.273~1.960,P<0.001)。

结论

当前研究表明,高CLR是接受PCI的CAD患者不良长期结局的一种新的强大预测指标,并且,对于SCAD和ACS患者而言,它是一个更好的预测指标。

临床试验注册

NCT05174143,http://Clinicaltrials.gov。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0c3/11270069/4e33c0ff6139/2153-8174-24-9-260-g1.jpg

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