Diagnosis of subclinical atherosclerosis in HIV-infected patients: higher accuracy of the D:A:D risk equation over Framingham and SCORE algorithms

• Published in: European journal of preventive cardiology 2014-06, Vol.21 (6), p.739-748
• Main Authors: Serrano-Villar, Sergio, Estrada, Vicente, Gómez-Garre, Dulcenombre, Ávila, Mario, Fuentes-Ferrer, Manuel, San, Román Jesús, Soriano, Vicente, Sánchez-Parra, Clara, Sainz, Talía, Fernández-Cruz, Arturo
• Format: Article
• Language: English
• Subjects: Adult; Aged; Albuminuria - diagnosis; Algorithms; Atherosclerosis (general aspects, experimental research); Atherosclerosis - diagnosis; Atherosclerosis - etiology; Biological and medical sciences; Blood and lymphatic vessels; Cardiology. Vascular system; Carotid Intima-Media Thickness; CD4 Lymphocyte Count; Cross-Sectional Studies; Female; Heart; HIV Infections - complications; Human viral diseases; Humans; Immunodeficiencies; Immunodeficiencies. Immunoglobulinopathies; Immunopathology; Infectious diseases; Male; Medical sciences; Middle Aged; Risk Assessment - methods; Viral diseases; Viral diseases of the lymphoid tissue and the blood. Aids
• ISSN: 2047-4873; 2047-4881
• DOI: 10.1177/2047487312452964

Abstract Aims While the detection of subclinical atherosclerosis may provide an opportunity for the prevention of cardiovascular disease (CVD), which currently is a leading cause of death in HIV-infected subjects, its diagnosis is a clinical challenge. We aimed to compare the agreement and diagnostic performance of Framingham, SCORE and D:A:D equations for the recognition of subclinical atherosclerosis in HIV patients and to adjust the D:A:D equation using HIV and CVD variables. Methods and results Atherosclerosis was evaluated in 203 HIV-infected individuals by measuring the carotid intima-media thickness (IMT). The CVD risk was calculated using the Framingham, SCORE and D:A:D risk equations. Framingham, SCORE and D:A:D equations showed a low agreement with the IMT (Kappa: 0.219, 0.298, 0.244, respectively; p = 0.743) and a moderate predictive performance, (area under the curve [AUC] = 0.686, 0.665 and 0.716, respectively; p = 0.048), with the D:A:D equation being the most accurate. Atherosclerosis was demonstrated in a significant proportion of subjects with low predicted CVD risk by all three algorithms (16.3%, 17.2%, 17.2%, respectively; p = 0.743). In patients with an estimated low CVD risk atherosclerosis was associated with older age (p = 0.012) and low CD4 counts (p = 0.021). A model was developed to adjust the D:A:D equation; a significant increase in accuracy was obtained when CD4 counts and low-grade albuminuria were included (AUC = 0.772; p