Machine learning based on systemic inflammation response index and risk of cardiovascular disease in gout: a retrospective study and clinical validation - Takeaways - MDSpire
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Utilizing Machine Learning to Assess the Impact of Systemic Inflammation Response Index on Cardiovascular Disease Risk in Gout: A Retrospective Analysis and Clinical Validation

  • By

  • Qiang Zhang

  • Xuan-hua Yu

  • Wei-zhen Zhang

  • Xue-bing Lyu

  • Hu-han Lin

  • Shan-ting Zeng

  • Chang-quan Liu

  • Hui-juan Huang

  • Wei-zhe Deng

  • November 18, 2025

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  • 1

    Gout affects over 41 million people globally, characterized by high uric acid levels and chronic inflammation, with a significant male predominance.

  • 2

    Cardiovascular disease (CVD) is prevalent in gout patients, with higher incidences of myocardial infarction, heart failure, and hypertension compared to the general population.

  • 3

    The systemic inflammation response index (SIRI) is a scoring system that reflects inflammation and organ function, potentially influencing CVD risk in gout patients.

  • 4

    This study utilized NHANES data from 2007 to 2018 to explore the association between SIRI levels and cardiovascular disease risk in individuals with gout.

  • 5

    Machine learning algorithms were applied to enhance the assessment of CVD risk in gout patients, aiming to identify high-risk individuals for better management.

Original Source(s)

Machine learning based on systemic inflammation response index and risk of cardiovascular disease in gout: a retrospective study and clinical validation

  • by Qiang Zhang, Xuan-hua Yu, Wei-zhen Zhang, Xue-bing Lyu, Hu-han Lin, Shan-ting Zeng, Chang-quan Liu, Hui-juan Huang, Wei-zhe Deng

  • November 18, 2025

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