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Higher Heart Disease Risk Seen in People with HIV
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Current methods of predicting heart attack and stroke risk vastly underestimate the problem in patients with HIV, according to a new study published in the journal JAMA Cardiology.Based on a study of 20,000 people infected with HIV, investigators found their risk of heart events is nearly twice that of the general population.Researchers at Northwestern University School of Medicine found the elevated risk even in those in whom the virus was undetectable because of the use of antiretroviral drugs.
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Patients With HIV Have Nearly Double The Risk Of Heart Attack, Stroke
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AdvertisementResearchers from Northwestern University Feinberg School of Medicine have found that patients with HIV have nearly double the risk of heart attacks and strokes compared with the general population.In a study published in the journal JAMA Cardiology, the researchers showed that those infected with the HIV virus, even patients whose viral load are undetectable, have 1.5 to 2 times greater risks for heart attacks."The actual risk of heart attack for people with HIV was roughly 50 percent higher than predicted by the risk calculator many physicians use for the general population," said Matthew Feinstein, M.D., a cardiovascular disease fellow at Northwestern Medicine and the study's first author.
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CV Risk Calculator 'Adequate' For HIV Patients
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The standard atherosclerotic disease risk predictor worked as well as other models for HIV-positive individuals on antiretroviral therapy, researchers reported in a study.The American College of Cardiology and American Heart Association's 2013 Pooled Cohort Equations -- intended for use in the general population -- were an adequate predictor of combined MI and stroke risk over 10 years among HIV-positive patients (Harrell C-statistic 0.75, 95% CI 0.71-0.78), according to the study published online in JAMA Cardiology.Donald M. Lloyd-Jones, MD, ScM, of Northwestern University Feinberg School of Medicine in Chicago, and colleagues tried to incorporate HIV-specific factors to create two better models.
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