Suppr超能文献

基于大数据技术的脑卒中高危人群颈动脉超声筛查分析。

Analysis of Carotid Ultrasound Screening of High-Risk Groups of Stroke Based on Big Data Technology.

机构信息

Department of Ultrasound Medicine, 3201 Hospital, Shanxi 723000, China.

Department of Oncology, 3201 Hospital, Shanxi 723000, China.

出版信息

J Healthc Eng. 2022 Jan 25;2022:6363691. doi: 10.1155/2022/6363691. eCollection 2022.

Abstract

In order to understand detection of carotid atherosclerosis in the screening of high-risk stroke populations in a certain area of China, we have analyzed related risk factors of CAS. In accordance with the requirements of the "2015 Technical Plan for the Screening and Intervention Projects for High-Risk Stroke Populations," a cluster sampling method was used to select 4532 (number of screened persons from 2015 to 2021) permanent residents over 41 years old () in Shaheying Town, Liulin Town, Chenggu County, Hanzhong City, Shaanxi Province, and Da'an Town, Ningqiang County, and nearby communities are selected as the screening targets. We screened out high-risk groups of stroke based on big data technology and understood the detection of CAS. According to the screening results of big data technology, it was divided into two groups: CAS group and non-CAS group. The basic information, medical history, personal lifestyle, physical examination, and laboratory examination results of the two groups were classified and counted. The measurement data such as age and waist circumference of the two groups were tested by two independent samples, and the count data of gender, stroke history, hypertension, and other data were tested by the test of the four-table data, and the logistic regression model was used to analyze the risk factors for CAS of population at high risk of stroke. The results proved the following: (1) Among the 4532 screeners, 865 cases were screened out of the high-risk population of stroke, with an average age of (58.5 ± 8.3) years, mainly 59 to 68 years old, accounting for 43.8%, and the male-to-female ratio was 1.6 : 1. (2) The detection rates of CAS, intimal thickening, plaque formation, and stenosis among high-risk groups of stroke were 55.5%, 10.2%, 52.2%, and 32.6%, respectively. (3) Among the high-risk groups of stroke, CAS patients have a history of stroke, the proportion of hypertension, age, total cholesterol, and low-density lipoprotein cholesterol levels that are higher than those in the non-CAS group, and the difference is statistically significant. (4) Logistic regression analysis shows that age, diabetes, and low-density lipoprotein cholesterol are independent risk factors for CAS in the high-risk population of stroke in this area.

摘要

为了了解我国某地区高危卒中人群筛查中颈动脉粥样硬化的检出情况,我们对 CAS 的相关危险因素进行了分析。按照《2015 年高危卒中人群筛查与干预项目技术方案》的要求,采用整群抽样的方法,选取陕西省汉中市城固县沙河营镇、柳林镇和大安吉镇,宁强县附近社区 41 岁以上常住居民 4532 人(2015 年至 2021 年筛查人数)作为筛查对象,运用大数据技术筛选出卒中高危人群,并了解 CAS 的检出情况。根据大数据技术筛查结果,将其分为 CAS 组和非 CAS 组,对两组的基本信息、病史、个人生活方式、体格检查和实验室检查结果进行分类计数。对两组的年龄、腰围等计量资料采用两独立样本 t 检验,性别、卒中史、高血压等计数资料采用四格表资料的 检验,采用 logistic 回归模型分析高危人群的 CAS 发病风险因素。结果表明:(1)4532 名筛查者中,共筛查出卒中高危人群 865 例,平均年龄(58.5±8.3)岁,主要为 59~68 岁,占 43.8%,男女比例为 1.6∶1。(2)卒中高危人群的 CAS、内膜增厚、斑块形成及狭窄检出率分别为 55.5%、10.2%、52.2%、32.6%。(3)在卒中高危人群中,CAS 患者有卒中史、高血压比例、年龄、总胆固醇、低密度脂蛋白胆固醇水平均高于非 CAS 组,差异有统计学意义。(4)logistic 回归分析显示,年龄、糖尿病、低密度脂蛋白胆固醇是该地区高危人群中 CAS 的独立危险因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3833/8808203/bcbc831801a8/JHE2022-6363691.001.jpg

相似文献

4
[Association between carotid artery plaques and all-cause mortality and cardiovascular events].颈动脉斑块与全因死亡率及心血管事件之间的关联
Zhonghua Xin Xue Guan Bing Za Zhi. 2017 Dec 24;45(12):1086-1090. doi: 10.3760/cma.j.issn.0253-3758.2017.12.014.

本文引用的文献

2
Weight loss and carotid intima-media thickness-a meta-analysis.体重减轻与颈动脉内膜中层厚度:荟萃分析。
Obesity (Silver Spring). 2017 Feb;25(2):357-362. doi: 10.1002/oby.21732. Epub 2016 Dec 27.
3
Carotid artery stenting versus carotid endarterectomy.颈动脉支架置入术与颈动脉内膜切除术比较。
Postgrad Med J. 2016 Sep;92(1091):532-9. doi: 10.1136/postgradmedj-2015-133689. Epub 2016 Jun 17.
4
Exercise is a double-edged sword for endothelial function.运动对内皮功能而言是把双刃剑。
Hypertens Res. 2016 Feb;39(2):61-3. doi: 10.1038/hr.2015.127. Epub 2015 Nov 12.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验