中文|English

Current issue
2024-5-25
Vol 32, issue 5

ISSUE

2022 年11 期 第30 卷

新进展 HTML下载 PDF下载

代谢综合征及其组分聚集性与卒中相关性的研究进展

Review of the Correlation between Metabolic Syndrome and Its Components Clustering and Stroke

作者:李捷,赵岩岩,周强,王妍妍,陈海英

单位:
1.050000 河北省石家庄市,河北医科大学护理学院 2.050000 河北省石家庄市,河北医科大学第三医院脊柱科 3.050000 河北省石家庄市,河北医科大学口腔医院护理部 通信作者:陈海英,E-mail:hychen1964@163.com
Units:
1.School of Nursing, Hebei Medical University, Shijiazhuang 050000, China 2.Department of Spine, the Third Hospital of Hebei Medical University, Shijiazhuang 050000, China 3.Nursing Department, Hospital of Stomatology Hebei Medical University, Shijiazhuang 050000, China Corresponding author: CHEN Haiying, E-mail: hychen1964@163.com
关键词:
卒中; 代谢综合征; 诊断标准; 聚集性; 综述;
Keywords:
Stroke; Metabolic syndrome; Diagnostic criteria; Clustering; Review
CLC:
DOI:
10.12114/j.issn.1008-5971.2022.00.294
Funds:
河北省省级科技计划资助(21377776D);河北省 2021年度医学科学研究课题(20211430)

摘要:

代谢综合征(MS)是多种心脑血管疾病代谢性危险因素(肥胖、高血糖、高血压和血脂异常)异常聚集的病理状态,研究表明,MS及其组分均与卒中的发病机制和病理生理过程密切相关。但目前现有的MS诊断标准筛查卒中高危人群及预测卒中发病风险的能力存在差异。此外,MS及其组分聚集性预测卒中相关风险的价值尚存争议:MS作为一个整体预测卒中发病和死亡风险的能力是否高于单个MS组分尚未明确;MS表型复杂多样,不同MS组分聚集数量和组合形式预测卒中的风险存在差异。本文主要综述了MS及其组分聚集性与卒中的相关性,以期为脑卒中防治策略的制定提供新思路。

Abstract:

【Abstract】 Metabolic syndrome (MS) is a pathological state characterized by abnormal aggregation of multiple metabolic risk factors for cerebrovascular disease (obesity, hyperglycemia, hypertension and dyslipidemia) , and studies have shown that both MS and its components are closely related to the pathogenesis and pathophysiological processes of stroke. However, the currently available diagnostic criteria for MS vary in their ability to screen for people at high risk of stroke and predict the risk of stroke onset. In addition, the value of MS and its components clustering for predicting stroke-related risk is controversial: whether the ability of MS as a whole in predicting the risk of stroke morbidity and mortality is higher than its individual components; the MS phenotypes are complex and diverse, and there are differences in the number and combination of MS components in predicting stroke risk. This paper mainly reviews the correlation between MS and its components clustering, in order to provide new ideas for stroke prevention and treatment.

ReferenceList: