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ORIGINAL RESEARCH article

Front. Cardiovasc. Med.
Sec. Atherosclerosis and Vascular Medicine
Volume 11 - 2024 | doi: 10.3389/fcvm.2024.1392752

Screening for Carotid Atherosclerosis: Development and Validation of a High-Precision Risk Scoring Tool

Provisionally accepted
Zhixin Huang Zhixin Huang 1*Lijuan Chen Lijuan Chen 2Ping Chen Ping Chen 3Yingyi Dai Yingyi Dai 1Haike Lu Haike Lu 1Yicheng Liang Yicheng Liang 1Qingguo Ding Qingguo Ding 4
  • 1 Guangdong Second Provincial General Hospital, Guangzhou, China
  • 2 Songyang County People's Hospital, Lishui, China
  • 3 The First Hospital of Putian City, Putian, Fujian Province, China
  • 4 Nanhai Economic Development Zone Peoples Hospital, Foshan, Guangdong Province, China

The final, formatted version of the article will be published soon.

    Objective-This study aimed to investigate the prevalence of carotid atherosclerosis (CAS), especially among seniors, and develop a precise risk assessment tool to facilitate screening and early intervention for high-risk individuals.Methods-A comprehensive approach was employed, integrating traditional epidemiological methods with advanced machine learning techniques, including support vector machines, XGBoost, decision trees, random forests, and logistic regression.Results-Among 1,515 participants, CAS prevalence reached 57.4%, concentrated within older individuals. Positive correlations were identified with age, systolic blood pressure, a history of hypertension, male gender, and total cholesterol. High-density lipoprotein (HDL) emerged as a protective factor against CAS, with total cholesterol and HDL levels proving significant predictors.Conclusions-This research illuminates the risk factors linked to CAS and introduces a validated risk scoring tool, highlighted by the logistic classifier's consistent performance during training and testing. This tool shows potential for pinpointing high-risk individuals in community health programs, streamlining screening and intervention by clinical physicians. By stressing the significance of managing cholesterol levels, especially HDL, our findings provide actionable insights for CAS prevention. Nonetheless, rigorous validation is paramount to guarantee its practicality and efficacy in real-world scenarios.

    Keywords: CAS Prevention: Ivy Action Study Keywords prevention, cerebrovascular disease, screening, ultrasound, machine learning, carotid atherosclerosis

    Received: 28 Feb 2024; Accepted: 15 Jul 2024.

    Copyright: © 2024 Huang, Chen, Chen, Dai, Lu, Liang and Ding. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Zhixin Huang, Guangdong Second Provincial General Hospital, Guangzhou, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.