Highly active antiretroviral therapy (HAART) can cause side effects in HIV patients, as the metabolic syndrome. Early identification of risk for development of cardiovascular diseases using available reliable and practical methods is fundamental. On this basis, the aim of this study was to compare the effectiveness of anthropometric indicators to identify metabolic syndrome in HIV patients on HAART.
It is a cross-sectional study. A number of 280 stable HIV patients were studied. It measured weight, height, waist circumference (WC), hip circumference (HP), thigh circumference (TC) and calculated body mass index (BMI), body adiposity index (BAI), waist to hip ratio (WHR) and waist to thigh ratio (WTR). There was also a performance of biochemical tests of lipid profile and fasting glucose. Systemic blood pressure was measured. The criteria proposed by the National Cholesterol Education Program III (NCEP-ATP III) to metabolic syndrome classification was used. Individuals were divided in groups with or without metabolic alterations and their anthropometric indicators were compared. Receiver operating characteristic (ROC) curves were designed for each anthropometric indicator using the metabolic syndrome classification to identify sensitivity and specificity.
WC was a good tool to identify each metabolic disorder separately: total cholesterol (only females, p<0.05), triglycerides (only males, p<0.001), HDL cholesterol (p<0.05), LDL cholesterol (p<005) and fasting glycemic (p<005). WC also showed the best performance to identify metabolic syndrome in both genders (areas under the curve (AUCs): 0.79 and 0.76 for male and female, respectively), while BAI proved to be an inadequate indicator (AUCs: 0.63 and 0.67 for males and females), respectively, in this population.
The central adiposity measure (WC) had the best performance to identify metabolic syndrome, and it is a convenient, cheap and reliable tool that can be used in clinical practice routinely to prevent cardiovascular complications in HIV patients.
Below: Receiver operating characteristic curves for the performance evaluations of anthropometric indicators in identifying metabolic syndrome
Full article at: http://goo.gl/pUIfQT
Department of Internal Medicine, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil
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