Association of Serum Uric Acid and Lipid Parameters in Patients at Lamphun Hospital, Thailand
2022 17th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)(2022)
Abstract
Dyslipidemia leads to cardiovascular disease with several complications which include sudden cardiac death, acute myocardial infarction, and strokes. The primary evaluation tool for dyslipidemia is a fasting lipid panel which consists of total cholesterol (TC), (LDL-C), (HDL-C), and triglycerides (TG). However, the relationship between a fasting lipid panel and elevated uric acid has not been comprehensively investigated. This work investigates the relationship between serum uric acid (SUA) and a fasting lipid panel in the elderly patients in Thailand. A rule-based machine learning technique called association rule mining was used to define patterns in the rules discovered. The results showed a significant positive relationship for SUA with TG, TC and LDL levels, and an inverse relationship for SUA with HDL. Early prevention of hyperuricemia and dyslipidemia may be helpful to reduce the incidence of associated cardiovascular diseases.
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Key words
association rule mining,clinical chemistry,dys-lipidemia,interestingness measure,lipid profile,serum uric acid
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