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THE BOTTOM LINE:
This report explores the usefulness of the Veterans Aging Cohort Study (VACS) index in identifying those at risk for low bone mineral density (BMD). In 195 HIV-infected individuals 109 (56%) had low BMD. As the VACS index increased in these individuals, the odds of low BMD became higher. This was true even after correcting for race, weight, and the presence of Hepatitis C coinfection. The VACS index is a useful resource for predicting low BMD and can be used to justify more extensive testing.
People living with human immunodeficiency virus (HIV) infection have higher risk of low bone mineral density (BMD) and fragility fracture than general population. The aim of our retrospective study was to explore if HIV-specific Veterans Aging Cohort Study (VACS) Index and its specific components could help identify patients at risk for low BMD. A total of 195 HIV-infected patients with dual-energy X-ray absorptiometry (DXA) scan between 2007 and 2014 were included and DXA scan results were used to classify patients with osteopenia. VACS Index was calculated for all patients using laboratory values closest to the date of DXA scan. Logistic regression was used to assess the association between VACS Index score or individual components of VACS Index with the presence of low BMD after adjusting for confounding variables. A total of 109 (56%) patients were diagnosed with low BMD. VACS Index score was significantly associated with low BMD, with the odds of low BMD increasing 1.21 times for each 10 unit increase in VACS Index score [confidence interval (95% CI) 1.03-1.42; p = .02]. The two groups differed significantly on patient weights, proportion of white patients, and hepatitis C-coinfected patients. After adjusting for white race and weight, hepatitis C coinfection was significantly associated with increased risk of low BMD (odds ratio 24.4; 95% CI 7.45-80.16). VACS Index score, previously demonstrated to be a marker of frailty in HIV-infected patients, is significantly associated with risk of low BMD and could be used to develop a prediction tool to screen for low BMD in resource-limited setting where DXA scans are not easily available.