Literature DB >> 22718798

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

Sergio Serrano-Villar1, Vicente Estrada2, Dulcenombre Gómez-Garre3, Mario Ávila4, Manuel Fuentes-Ferrer5, Román Jesús San6, Vicente Soriano6, Clara Sánchez-Parra4, Talía Sainz7, Arturo Fernández-Cruz2.   

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 < 0.001).
CONCLUSION: 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. © The European Society of Cardiology 2012 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Entities:  

Keywords:  D:A:D risk equation; Framingham risk equation; HIV; SCORE; atherosclerosis; carotid intima-media thickness

Mesh:

Year:  2012        PMID: 22718798     DOI: 10.1177/2047487312452964

Source DB:  PubMed          Journal:  Eur J Prev Cardiol        ISSN: 2047-4873            Impact factor:   7.804


  11 in total

1.  Regarding: cardiovascular risk-factor knowledge and risk perception among HIV-infected adults.

Authors:  Natalie E Kelso
Journal:  J Assoc Nurses AIDS Care       Date:  2014-01-07       Impact factor: 1.354

2.  International Congress of Drug Therapy in HIV Infection 23-26 October 2016, Glasgow, UK.

Authors: 
Journal:  J Int AIDS Soc       Date:  2016-10-23       Impact factor: 5.396

3.  Cardiovascular disease risk scores' relationship to subclinical cardiovascular disease among HIV-infected and HIV-uninfected men.

Authors:  Anne K Monroe; Sabina A Haberlen; Wendy S Post; Frank J Palella; Lawrence A Kinsgley; Mallory D Witt; Matthew Budoff; Lisa P Jacobson; Todd T Brown
Journal:  AIDS       Date:  2016-08-24       Impact factor: 4.177

4.  Taming HIV-related inflammation with physical activity: a matter of timing.

Authors:  Gabriella d'Ettorre; Giancarlo Ceccarelli; Noemi Giustini; Claudio M Mastroianni; Guido Silvestri; Vincenzo Vullo
Journal:  AIDS Res Hum Retroviruses       Date:  2014-09-17       Impact factor: 2.205

5.  Cardiovascular Risk in HIV-Infected and Uninfected Postmenopausal Minority Women: Use of the Framingham Risk Score.

Authors:  Yamnia I Cortés; Nancy Reame; Cosmina Zeana; Haomiao Jia; David C Ferris; Elizabeth Shane; Michael T Yin
Journal:  J Womens Health (Larchmt)       Date:  2016-09-09       Impact factor: 2.681

6.  Cardiovascular Disease Prevention Policy in Human Immunodeficiency Virus: Recommendations From a Modeling Study.

Authors:  Mikaela Smit; Rosan A van Zoest; Brooke E Nichols; Ilonca Vaartjes; Colette Smit; Marc van der Valk; Ard van Sighem; Ferdinand W Wit; Timothy B Hallett; Peter Reiss
Journal:  Clin Infect Dis       Date:  2018-02-10       Impact factor: 9.079

7.  Coronary artery plaque progression and cardiovascular risk scores in men with and without HIV-infection.

Authors:  Kashif Shaikh; Fiona Bhondoekhan; Sabina Haberlen; Rine Nakanishi; Sion K Roy; Venkata M Alla; Todd T Brown; Juhwan Lee; Kazuhiro Osawa; Shone Almeida; Sina Rahmani; Negin Nezarat; Nasim Sheidaee; Michael Kim; Eranthi Jayawardena; Nicolas Kim; Nicolai Hathiramani; Frank J Palella; Mallory Witt; Khadije Ahmad; Lawrence Kingsley; Wendy S Post; Matthew J Budoff
Journal:  AIDS       Date:  2022-02-01       Impact factor: 4.632

Review 8.  Human Immunodeficiency Virus as a Chronic Disease: Evaluation and Management of Nonacquired Immune Deficiency Syndrome-Defining Conditions.

Authors:  Sergio Serrano-Villar; Félix Gutiérrez; Celia Miralles; Juan Berenguer; Antonio Rivero; Esteban Martínez; Santiago Moreno
Journal:  Open Forum Infect Dis       Date:  2016-05-12       Impact factor: 3.835

Review 9.  Cardiovascular Disease in the Setting of Human Immunodeficiency Virus Infection.

Authors:  Daniela Sofia Martins Pinto; Manuel Joaquim Lopes Vaz da Silva
Journal:  Curr Cardiol Rev       Date:  2018-03-14

10.  Assessment of the agreement between the Framingham and DAD risk equations for estimating cardiovascular risk in adult Africans living with HIV infection: a cross-sectional study.

Authors:  Steve Raoul Noumegni; Vicky Jocelyne Moor Ama; Felix K Assah; Jean Joel Bigna; Jobert Richie Nansseu; Jenny Arielle M Kameni; Jean-Claude Katte; Mesmin Y Dehayem; Andre Pascal Kengne; Eugene Sobngwi
Journal:  Trop Dis Travel Med Vaccines       Date:  2017-07-05
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