Anne-Lise Paisible1, Chung-Chou H Chang, Kaku A So-Armah, Adeel A Butt, David A Leaf, Matthew Budoff, David Rimland, Roger Bedimo, Matthew B Goetz, Maria C Rodriguez-Barradas, Heidi M Crane, Cynthia L Gibert, Sheldon T Brown, Hilary A Tindle, Alberta L Warner, Charles Alcorn, Melissa Skanderson, Amy C Justice, Matthew S Freiberg. 1. *Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA; Departments of †Biostatistics; ‡Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA; §Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA; Department of Internal Medicine, Yale University School of Medicine, New Haven, CT; ‖Department of Medicine, VA Greater Los Angeles Healthcare System, Los Angeles, CA David Geffen School of Medicine at UCLA, Los Angeles, CA; ¶Harbor-UCLA Medical Center and Los Angeles Biomedical Research Institute, Los Angeles, CA; #VA Medical Center; Department of Medicine, Emory University School of Medicine, Atlanta, GA; **Infectious Disease Section, Department of Medicine, VA North Texas Health Care System, UT Southwestern Medical Center, Dallas, TX; ††Infectious Diseases Section, Michael E. DeBakey VA Medical Center; Baylor College of Medicine, Houston, TX; ‡‡Department of Medicine, University of Washington, Seattle, WA; §§VA Medical Center and George Washington University Medical Center, Washington, DC; ‖‖Department of Internal Medicine, The Mount Sinai Medical Center; Bronx Veterans Affairs Medical Center, NY; ¶¶Division of Cardiology, Department of Medicine, University of California, Los Angeles, CA. ##Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA; ***VA Connecticut Healthcare System, West Haven, CT; †††VA Connecticut Healthcare System, West Haven, CT, and Section of General Medicine, Yale University School of Medicine, New Haven, CT; and ‡‡‡Vanderbilt University School of Medicine and Nashville Veterans Affairs Medical Center, Nashville TN.
Abstract
BACKGROUND: Traditional cardiovascular disease risk factors (CVDRFs) increase the risk of acute myocardial infarction (AMI) among HIV-infected (HIV+) participants. We assessed the association between HIV and incident AMI within CVDRF strata. METHODS: Cohort-81,322 participants (33% HIV+) without prevalent CVD from the Veterans Aging Cohort Study Virtual Cohort (prospective study of HIV+ and matched HIV- veterans) participated in this study. Veterans were followed from first clinical encounter on/after April 1, 2003, until AMI/death/last follow-up date (December 31, 2009). Predictors-HIV, CVDRFs (total cholesterol, cholesterol-lowering agents, blood pressure, blood pressure medication, smoking, diabetes) used to create 6 mutually exclusive profiles: all CVDRFs optimal, 1+ nonoptimal CVDRFs, 1+ elevated CVDRFs, and 1, 2, 3+ major CVDRFs. Outcome-Incident AMI [defined using enzyme, electrocardiogram (EKG) clinical data, 410 inpatient ICD-9 (Medicare), and/or death certificates]. Statistics-Cox models adjusted for demographics, comorbidity, and substance use. RESULTS: Of note, 858 AMIs (42% HIV+) occurred over 5.9 years (median). Prevalence of optimal cardiac health was <2%. Optimal CVDRF profile was associated with the lowest adjusted AMI rates. Compared with HIV- veterans, AMI rates among HIV+ veterans with similar CVDRF profiles were higher. Compared with HIV- veterans without major CVDRFs, HIV+ veterans without major CVDRFs had a 2-fold increased risk of AMI (HR: 2.0; 95% confidence interval: 1.0 to 3.9; P = 0.044). CONCLUSIONS: The prevalence of optimal cardiac health is low in this cohort. Among those without major CVDRFs, HIV+ veterans have twice the AMI risk. Compared with HIV- veterans with high CVDRF burden, AMI rates were still higher in HIV+ veterans. Preventing/reducing CVDRF burden may reduce excess AMI risk among HIV+ people.
BACKGROUND: Traditional cardiovascular disease risk factors (CVDRFs) increase the risk of acute myocardial infarction (AMI) among HIV-infected (HIV+) participants. We assessed the association between HIV and incident AMI within CVDRF strata. METHODS: Cohort-81,322 participants (33% HIV+) without prevalent CVD from the Veterans Aging Cohort Study Virtual Cohort (prospective study of HIV+ and matched HIV- veterans) participated in this study. Veterans were followed from first clinical encounter on/after April 1, 2003, until AMI/death/last follow-up date (December 31, 2009). Predictors-HIV, CVDRFs (total cholesterol, cholesterol-lowering agents, blood pressure, blood pressure medication, smoking, diabetes) used to create 6 mutually exclusive profiles: all CVDRFs optimal, 1+ nonoptimal CVDRFs, 1+ elevated CVDRFs, and 1, 2, 3+ major CVDRFs. Outcome-Incident AMI [defined using enzyme, electrocardiogram (EKG) clinical data, 410 inpatient ICD-9 (Medicare), and/or death certificates]. Statistics-Cox models adjusted for demographics, comorbidity, and substance use. RESULTS: Of note, 858 AMIs (42% HIV+) occurred over 5.9 years (median). Prevalence of optimal cardiac health was <2%. Optimal CVDRF profile was associated with the lowest adjusted AMI rates. Compared with HIV- veterans, AMI rates among HIV+ veterans with similar CVDRF profiles were higher. Compared with HIV- veterans without major CVDRFs, HIV+ veterans without major CVDRFs had a 2-fold increased risk of AMI (HR: 2.0; 95% confidence interval: 1.0 to 3.9; P = 0.044). CONCLUSIONS: The prevalence of optimal cardiac health is low in this cohort. Among those without major CVDRFs, HIV+ veterans have twice the AMI risk. Compared with HIV- veterans with high CVDRF burden, AMI rates were still higher in HIV+ veterans. Preventing/reducing CVDRF burden may reduce excess AMI risk among HIV+ people.
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