Absence of Coronary Artery Disease is a Strong Negative Predictor of Major Adverse Cardiovascular Events in Patients with Chronic Kidney Disease.

IF 3.4 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Clinical Epidemiology Pub Date : 2023-11-29 eCollection Date: 2023-01-01 DOI:10.2147/CLEP.S433983
Pernille Tilma Tonnesen, Kevin Kris Warnakula Olesen, Pernille Gro Thrane, Christine Gyldenkerne, Christian Daugaard Peters, Niels Henrik Buus, Michael Maeng
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引用次数: 0

Abstract

Purpose: To investigate the interplay between chronic kidney disease (CKD) and coronary artery disease (CAD) on the incidence of cardiovascular events in patients with suspected chronic coronary syndrome (CCS).

Patients and methods: Patients with suspected CCS who underwent first-time coronary angiography in Western Denmark between 2003 and 2016 were included in this cohort study. Moreover, an age- and sex-matched general population cohort was established. Patients were stratified according to estimated glomerular filtration rate (eGFR). Presence of CAD was defined as ≥1 obstructive stenosis or non-obstructive diffuse disease. Major adverse cardiovascular events (MACE) were defined as a composite of myocardial infarction, ischemic stroke, and cardiac death.

Results: A total of 42,611 patients were included with a median follow-up of 7.3 years. Patients without and with CAD had MACE rates per 100 person-years that were 0.52 and 1.67 for eGFR ≥90 mL/min/1.73 m2, 0.68 and 2.09 for eGFR 60-89 mL/min/1.73 m2, 1.27 and 3.85 for eGFR 30-59 mL/min/1.73 m2, and 2.27 and 6.92 for eGFR <30 mL/min/1.73 m2. Comparing to eGFR ≥90 mL/min/1.73 m2, the adjusted incidence rate ratios for MACE were 1.29 (1.10-1.51) for eGFR 60-89 mL/min/1.73 m2, 1.86 (1.49-2.33) for eGFR 30-59 mL/min/1.73 m2, and 3.57 (1.92-6.67) for eGFR <30 mL/min/1.73 m2 in patients without CAD, and 1.11 (1.03-1.20), 1.71 (1.55-1.90), and 2.46 (1.96-3.09) in patients with CAD. The inverse relationship between kidney function and risk of MACE was confirmed when comparing patients with and without CAD to matched individuals in the general population.

Conclusion: Absence of CAD is a strong negative predictor of major adverse cardiovascular events in patients with CKD.

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无冠状动脉疾病是慢性肾病患者主要不良心血管事件的一个强有力的阴性预测因子。
目的:探讨慢性肾脏疾病(CKD)和冠状动脉疾病(CAD)在疑似慢性冠状动脉综合征(CCS)患者心血管事件发生率中的相互作用。患者和方法:2003年至2016年在丹麦西部首次接受冠状动脉造影的疑似CCS患者纳入本队列研究。此外,还建立了年龄和性别匹配的普通人群队列。根据估计的肾小球滤过率(eGFR)对患者进行分层。冠心病定义为≥1例梗阻性狭窄或非梗阻性弥漫性疾病。主要不良心血管事件(MACE)定义为心肌梗死、缺血性卒中和心源性死亡的复合事件。结果:共纳入42611例患者,中位随访时间为7.3年。无CAD和有CAD的患者每100人年的MACE率分别为:eGFR≥90 mL/min/1.73 m2的MACE率分别为0.52和1.67,eGFR 60-89 mL/min/1.73 m2的MACE率分别为0.68和2.09,eGFR 30-59 mL/min/1.73 m2的MACE率分别为1.27和3.85,eGFR 2的MACE率分别为2.27和6.92。与eGFR≥90 mL/min/1.73 m2相比,非CAD患者eGFR 60-89 mL/min/1.73 m2的MACE校正发病率比为1.29 (1.10-1.51),eGFR 30-59 mL/min/1.73 m2的MACE校正发病率比为1.86 (1.49-2.33),eGFR 2校正发病率比为3.57 (1.92-6.67),CAD患者为1.11(1.03-1.20)、1.71(1.55-1.90)、2.46(1.96-3.09)。当将患有和不患有CAD的患者与普通人群中的匹配个体进行比较时,证实了肾功能与MACE风险之间的负相关关系。结论:无CAD是CKD患者主要不良心血管事件的强烈阴性预测因子。
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来源期刊
Clinical Epidemiology
Clinical Epidemiology Medicine-Epidemiology
CiteScore
6.30
自引率
5.10%
发文量
169
审稿时长
16 weeks
期刊介绍: Clinical Epidemiology is an international, peer reviewed, open access journal. Clinical Epidemiology focuses on the application of epidemiological principles and questions relating to patients and clinical care in terms of prevention, diagnosis, prognosis, and treatment. Clinical Epidemiology welcomes papers covering these topics in form of original research and systematic reviews. Clinical Epidemiology has a special interest in international electronic medical patient records and other routine health care data, especially as applied to safety of medical interventions, clinical utility of diagnostic procedures, understanding short- and long-term clinical course of diseases, clinical epidemiological and biostatistical methods, and systematic reviews. When considering submission of a paper utilizing publicly-available data, authors should ensure that such studies add significantly to the body of knowledge and that they use appropriate validated methods for identifying health outcomes. The journal has launched special series describing existing data sources for clinical epidemiology, international health care systems and validation studies of algorithms based on databases and registries.
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