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Data_Sheet_1_Prediction of subclinical atherosclerosis in low Framingham risk score individuals by using the metabolic syndrome criteria and insulin s.docx (24.07 kB)

Data_Sheet_1_Prediction of subclinical atherosclerosis in low Framingham risk score individuals by using the metabolic syndrome criteria and insulin sensitivity index.docx

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posted on 2022-10-24, 04:53 authored by Benjamin Huang, Weiting Huang, John Carson Allen, Lijuan Sun, Hui Jen Goh, Siew Ching Kong, Dewaine Lee, Cherlyn Ding, Nabil Bosco, Leonie Egli, Lucas Actis-Goretta, Faidon Magkos, Fabrizio Arigoni, Melvin Khee-Shing Leow, Swee Yaw Tan, Khung Keong Yeo
Background

Subclinical atherosclerosis can be present in individuals with an optimal cardiovascular risk factor profile. Traditional risk scores such as the Framingham risk score do not adequately capture risk stratification in low-risk individuals. The aim of this study was to determine if markers of metabolic syndrome and insulin resistance can better stratify low-risk individuals.

Methods

A cross-sectional study of 101 healthy participants with a low Framingham risk score and no prior morbidities was performed to assess prevalence of subclinical atherosclerosis using computed tomography (CT) and ultrasound. Participants were compared between groups based on Metabolic Syndrome (MetS) and Insulin-Sensitivity Index (ISI-cal) scores.

Results

Twenty three individuals (23%) had subclinical atherosclerosis with elevated CT Agatston score ≥1. Presence of both insulin resistance (ISI-cal <9.23) and fulfillment of at least one metabolic syndrome criterion denoted high risk, resulting in significantly improved AUC (0.706 95%CI 0.588–0.822) over the Framingham risk score in predicting elevated CT Agatston score ≥1, with net reclassification index of 50.9 ± 23.7%. High-risk patients by the new classification also exhibited significantly increased carotid intima thickness.

Conclusions

The overlap of insulin resistance and presence of ≥1 criterion for metabolic syndrome may play an instrumental role in identifying traditionally low-risk individuals predisposed to future risk of atherosclerosis and its sequelae.

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