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


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 < 0.001).


CONCLUSIONS
The D:A:D equation overperforms Framingham and SCORE in HIV patients. However, all three equations underestimate the presence of subclinical atherosclerosis in this population. The accuracy of the D:A:D equation improves when CD4 counts and low-grade albuminuria are incorporated into the equation.
Department of Internal Medicine, Hospital Clínico San Carlos, Madrid, Spain serranovillar@gmail.com.
Sergio
S
Serrano-Villar
Department of Internal Medicine, Hospital Clínico San Carlos, Madrid, Spain Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain.
Vicente
V
Estrada
Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain Vascular Biology Research Laboratory, Hospital Clínico San Carlos, Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain.
Dulcenombre
D
Gómez-Garre
Department of Internal Medicine, Hospital Clínico San Carlos, Madrid, Spain.
Mario
M
Ávila
Department of Preventive Medicine, Hospital Clínico San Carlos, Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain.
Manuel
M
Fuentes-Ferrer
Department of Infectious Diseases, Hospital Carlos III, Madrid, Spain.
Román Jesús
RJ
San
Department of Infectious Diseases, Hospital Carlos III, Madrid, Spain.
Vicente
V
Soriano
Department of Internal Medicine, Hospital Clínico San Carlos, Madrid, Spain.
Clara
C
Sánchez-Parra
Laboratory of Immunomolecular Biology, Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Madrid, Spain.
Talía
T
Sainz
Department of Internal Medicine, Hospital Clínico San Carlos, Madrid, Spain Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain.
Arturo
A
Fernández-Cruz
D000328:Adult; D000368:Aged; D000419:Albuminuria / Q000175:diagnosis; D000465:Algorithms; D050197:Atherosclerosis / Q000175:diagnosis* / Q000209:etiology; D018791:CD4 Lymphocyte Count; D059168:Carotid Intima-Media Thickness; D003430:Cross-Sectional Studies; D005260:Female; D015658:HIV Infections / Q000150:complications*; D006801:Humans; D008297:Male; D008875:Middle Aged; D018570:Risk Assessment / Q000379:methods*