Purpose of the studyTo assess statistical agreement of metabolic syndrome (MS) ATPIII, IDF, EGIR and AACE classification in HIV-infected patients and association with body fat redistribution.MethodsCross-sectional observational study that included all consecutive HIV-infected patients seen at a metabolic clinic who were screened for MS and had a clinical and radiological lipodystrophy (LD) evaluation. Cohen's Kappa statistic was calculated to assess statistical agreement between different MS classifications. Logistic regression models were performed to identify factors associated with different MS classifications. (Tables 1 and 2.)Table 1. K of Cohen shows a low level of agreement between MS classifications.Summary of results1,348 pts were included in the analysis.Figure 1 depicts prevalence of metabolic syndrome according to different definition.ConclusionConcordance between MS classification is less than ideal. After adjusting for BMI strata, lipodystrophy phenotypes and central fat accumulation are associated with for MS diagnosis.
Statistical agreement between ATPIII, IDF, EGIR, AACE metabolic syndrome classifications in HIV-infected patients and association with lipodystrophy / Guaraldi, Giovanni; S., Zona; D'Amico, Roberto; N., Squillace; G., Orlando; C., Stentarelli; Esposito, Roberto. - STAMPA. - 11(Suppl 1):(2008), pp. P125-P125. (Intervento presentato al convegno Ninth International Congress on Drug Therapy in HIV Infection tenutosi a Glasgow nel 9-13/11/2008).
Statistical agreement between ATPIII, IDF, EGIR, AACE metabolic syndrome classifications in HIV-infected patients and association with lipodystrophy
GUARALDI, Giovanni;D'AMICO, Roberto;ESPOSITO, Roberto
2008
Abstract
Purpose of the studyTo assess statistical agreement of metabolic syndrome (MS) ATPIII, IDF, EGIR and AACE classification in HIV-infected patients and association with body fat redistribution.MethodsCross-sectional observational study that included all consecutive HIV-infected patients seen at a metabolic clinic who were screened for MS and had a clinical and radiological lipodystrophy (LD) evaluation. Cohen's Kappa statistic was calculated to assess statistical agreement between different MS classifications. Logistic regression models were performed to identify factors associated with different MS classifications. (Tables 1 and 2.)Table 1. K of Cohen shows a low level of agreement between MS classifications.Summary of results1,348 pts were included in the analysis.Figure 1 depicts prevalence of metabolic syndrome according to different definition.ConclusionConcordance between MS classification is less than ideal. After adjusting for BMI strata, lipodystrophy phenotypes and central fat accumulation are associated with for MS diagnosis.Pubblicazioni consigliate
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