Background: It remains debated whether to include resting electrocardiogram (ECG) in the routine care of human immunodeficiency virus (HIV)-infected patients.
Methods: This analysis included 4518 HIV-infected patients (28% women and 29% blacks) from the Strategies for Management of Antiretroviral Therapy study, a clinical trial aimed to compare 2 HIV treatment strategies. ECG abnormalities were classified using the Minnesota Code. Cox proportional hazards analysis was used to examine the association between baseline ECG abnormalities and incident cardiovascular disease (CVD).
Results: More than half of the participants (n = 2325, or 51.5%) had either minor or major ECG abnormalities. Minor ECG abnormalities (48.6%) were more common than major ECG abnormalities (7.7%). During a median follow-up of 28.7 months, 155 participants (3.4%) developed incident CVD. After adjusting for the study-treatment arms, the presence of major, minor, and either minor or major ECG abnormalities was significantly predictive of incident CVD (hazard ratio [95% confidence interval]: 2.76 [1.74-4.39], P < .001; 1.58 [1.14-2.20], P = .006; 1.57 [1.14-2.18], P = .006, respectively). However, after adjusting for demographics, CVD risk factors, and HIV characteristics (full model), presence of major ECG abnormalities were still significantly predictive of CVD (1.83 [1.12-2.97], P = .015) but not minor or major abnormalities taken together (1.26 [0.89-1.79], P = .18; 1.25 [0.89-1.76], P = .20, respectively). Individual ECG abnormalities that significantly predicted CVD in the fully adjusted model included major isolated ST-T abnormalities, major prolongation of QT interval, minor isolated ST-T, and minor isolated Q-QS abnormalities.
Conclusion: Nearly 1 in 2 of the HIV-infected patients in our study had ECG abnormalities; 1 in 13 had major ECG abnormalities. Presence of ECG abnormalities, especially major ECG abnormalities, was independently predictive of incident CVD. These results suggest that the ECG could provide a convenient risk-screening tool in HIV-infected patients.
Copyright © 2011 Elsevier Inc. All rights reserved.