RESEARCH ARTICLE · International journal of gerontology · 2012

Relationship Between Metabolic Scores, Systemic Inflammation, Renal Function, and High-risk Peripheral Arterial Disease

Chih‐Hsuan Yen, Chung‐Lieh Hung, Yih‐Jer Wu, Jui‐Peng Tsai, Ta‐Chuan Hung, Cheng‐Huang Su, Jen‐Yuan Kuo, Hung‐I Yeh, Cheng‐Ho Tsai

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Abstract

Metabolic syndrome (MS) associated with systemic inflammation identifies high-risk cardiovascular diseases (CVDs). Deteriorated renal function leads to poor cardiovascular outcomes. However, the relationship between such metabolic anomaly, systemic inflammation and renal function in patients diagnosed with peripheral arterial disease (PAD) remains largely unknown. A total of 249 consecutive individuals meeting the study criteria from our outpatient clinics were enrolled in the study. Baseline demographic data and information regarding metabolic abnormalities [presented as Adult Treatment Panel (ATP) III scores], high-sensitivity C-reactive protein (Hs-CRP) level, and estimated renal function [calculated by the Modification of Diet in Renal Disease (MDRD) method] were obtained. High-risk PAD was defined by utilizing the ankle–brachial index (ABI) method. Of all 249 subjects, 60 had diagnostic high-risk PAD. The prevalence of PAD increased in a significant trend with worsening ATP III scores. By utilizing a multivariate adjustment model, body mass index and worse renal function were independently associated with PAD (both p < 0.05). A receiver operating characteristic (ROC) curve showed that estimated glomerular filtration rate (eGFR) and Hs-CRP superimposed on metabolic scores (Mets) well expanded the area under the curve from 0.646 to 0.743 (c-statistics: 0.015) in identifying PAD and that the addition of eGFR on Mets and Hs-CRP further increased the model significantly by likelihood ratio test (p < 0.001). The combination of metabolic scores and systemic inflammation in terms of Hs-CRP superimposed on estimated renal function yielded better identification of patients at high risk for PAD. Our data suggested that early recognition of PAD may be enhanced in a population by screening for established higher cardiovascular risks combined with abnormal renal function.

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