Harnessing Metabolic Indices as a Predictive Tool for Cardiovascular Disease in a Korean Population without Known Major Cardiovascular Event.

IF 6.8 2区 医学 Q1 ENDOCRINOLOGY & METABOLISM
Diabetes & Metabolism Journal Pub Date : 2024-05-01 Epub Date: 2024-02-01 DOI:10.4093/dmj.2023.0197
Hyun-Jin Kim, Byung Sik Kim, Yonggu Lee, Sang Bong Ahn, Dong Wook Kim, Jeong-Hun Shin
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引用次数: 0

Abstract

Backgruound: This study evaluated the usefulness of indices for metabolic syndrome, non-alcoholic fatty liver disease (NAFLD), and insulin resistance (IR), as predictive tools for cardiovascular disease in middle-aged Korean adults.

Methods: The prospective data obtained from the Ansan-Ansung cohort database, excluding patients with major adverse cardiac and cerebrovascular events (MACCE). The primary outcome was the incidence of MACCE during the follow-up period.

Results: A total of 9,337 patients were included in the analysis, of whom 1,130 (12.1%) experienced MACCE during a median follow-up period of 15.5 years. The metabolic syndrome severity Z-score, metabolic syndrome severity score, hepatic steatosis index, and NAFLD liver fat score were found to significantly predict MACCE at values above the cut-off point and in the second and third tertiles. Among these indices, the hazard ratios of the metabolic syndrome severity score and metabolic syndrome severity Z-score were the highest after adjusting for confounding factors. The area under the receiver operating characteristic curve (AUC) of the 10-year atherosclerotic cardiovascular disease (ASCVD) score for predicting MACCE was 0.716, and the metabolic syndrome severity Z-score had an AUC of 0.619.

Conclusion: The metabolic syndrome severity score is a highly reliable indicator and was closely associated with the 10-year ASCVD risk score in predicting MACCE in the general population. Given the specific characteristics and limitations of metabolic syndrome severity scores as well as the indices of NAFLD and IR, a more practical scoring system that considers these factors is essential to achieve greater accuracy in forecasting cardiovascular outcomes.

利用代谢指标作为韩国未发生重大心血管事件人群的心血管疾病预测工具》(Harnessing Metabolic Indices as a Predictive Tool for Cardiovascular Disease in a Korean Population without Known Major Cardiovascular Event)。
背景:本研究评估了代谢综合征、非酒精性脂肪肝(NAFLD)和胰岛素抵抗(IR)指数作为韩国中年人心血管疾病预测工具的实用性:从安山-安城队列数据库中获取的前瞻性数据,排除了发生重大不良心脑血管事件(MACCE)的患者。主要结果是随访期间心脑血管不良事件的发生率:共有 9,337 名患者被纳入分析,其中 1,130 人(12.1%)在中位 15.5 年的随访期间发生了 MACCE。研究发现,代谢综合征严重程度Z-评分、代谢综合征严重程度评分、肝脏脂肪变性指数和非酒精性脂肪肝肝脏脂肪评分在高于临界点值时以及在第二和第三分位数时能显著预测MACCE。在这些指数中,代谢综合征严重程度评分和代谢综合征严重程度 Z 评分的危险比在调整混杂因素后最高。预测 MACCE 的 10 年动脉粥样硬化性心血管疾病(ASCVD)评分的接收者操作特征曲线下面积(AUC)为 0.716,代谢综合征严重程度 Z 评分的接收者操作特征曲线下面积(AUC)为 0.619:代谢综合征严重程度评分是一个高度可靠的指标,在预测普通人群的 MACCE 时与 10 年 ASCVD 风险评分密切相关。鉴于代谢综合征严重程度评分以及非酒精性脂肪肝和内脏脂肪肝指数的具体特点和局限性,要想更准确地预测心血管疾病的预后,必须建立一个考虑到这些因素的更实用的评分系统。
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来源期刊
Diabetes & Metabolism Journal
Diabetes & Metabolism Journal Medicine-Endocrinology, Diabetes and Metabolism
CiteScore
10.40
自引率
6.80%
发文量
92
审稿时长
52 weeks
期刊介绍: The aims of the Diabetes & Metabolism Journal are to contribute to the cure of and education about diabetes mellitus, and the advancement of diabetology through the sharing of scientific information on the latest developments in diabetology among members of the Korean Diabetes Association and other international societies. The Journal publishes articles on basic and clinical studies, focusing on areas such as metabolism, epidemiology, pathogenesis, complications, and treatments relevant to diabetes mellitus. It also publishes articles covering obesity and cardiovascular disease. Articles on translational research and timely issues including ubiquitous care or new technology in the management of diabetes and metabolic disorders are welcome. In addition, genome research, meta-analysis, and randomized controlled studies are welcome for publication. The editorial board invites articles from international research or clinical study groups. Publication is determined by the editors and peer reviewers, who are experts in their specific fields of diabetology.
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