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

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 (一) 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 ${\chi }^2$ 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.