HIV/HCV coinfection and the risk of cardiovascular disease: A meta‐analysis

Abstract

The emergence of improved antiretroviral therapy has increased the life expectancy of human immunodeficiency virus (HIV)-infected individuals, although there is an increased susceptibility to developing cardiovascular diseases (CVD). The risk for CVD is purported to be even higher among people with HIV and hepatitis C virus (HCV) coinfection because of the increased inflammatory response, which may synergistically impact CVD risk. However, studies comparing CVD outcomes between HIV alone and HIV/HCV individuals have been discordant. Accordingly, we conducted a meta-analysis to clarify and quantify the association between HIV/HCV coinfection and the risk for CVD. We searched EMBASE, CINAHL, Google Scholar, PubMed, and Web of Science from inception to December 2016 to identify studies that provided information on HIV/HCV coinfection and CVD, defined as coronary artery disease, congestive heart failure and stroke. We used a random-effects model to abstract and pool data on the hazard ratios (HRs) for CVD. HRs were adjusted for traditional CVD risk factors including age, sex, smoking, hypertension, diabetes and LDL cholesterol. Among the 283 articles reviewed, four cohort studies met inclusion criteria with a total of 33 723 participants. The pooled adjusted HRs for the association between HIV/HCV coinfection and CVD were 1.24 (95% CI: 1.07-1.40) compared to HIV monoinfection. The test for heterogeneity was not statistically significant (I =0.0%, P=.397). In conclusion, individuals with HIV/HCV coinfection had an increased CVD risk compared to those with HIV monoinfection. More research is needed to further examine the nature of this association, and response to traditional risk-reduction therapies.

Prevalence of and risk factors for cerebral microbleeds among adult patients with haemophilia A or B

“…In this study, HCV infection (active or cleared) was associated with CMBs, similar to what was previously reported in association with ICH in PWH . Although the incidence of CMBs in the HCV‐infected population has not been specifically investigated, it is well established that HCV infection has both neurovascular and cardiovascular toxicity as a consequence of chronic inflammation and accelerated atherosclerosis resulting from viral replication within vascular plaques and cerebral endothelial cells . In addition, HCV eradication reduces risk of ischaemic and haemorrhagic stroke .…”

Association between chronic hepatitis C virus infection and myocardial infarction in people living with HIV in the United States

“…A large body of literature has linked CVD to chronic infection with hepatitis C virus (HCV), a common viral infection impacting an estimated 10 to 30% (22)(23)(24)(25)(26) of PLWH in the United States (US). Observational evidence supports an association between HCV and clinically evident CVD, in both the general population (27,28) and in PLWH (29). Yet studies in the general population focusing on the role of HCV in coronary artery disease risk are inconclusive (27) and, when restricting to MI only, have generally not supported an association (30)(31)(32)(33).…”

Elevated Fatty Liver Index as a Risk Factor for All‐Cause Mortality in Human Immunodeficiency Virus–Hepatitis C Virus–Coinfected Patients (ANRS CO13 HEPAVIH Cohort Study)

“…(39,40) Both infections are associated with elevated cardiovascular risks, with coinfected patients presenting an even higher risk than their HIV-monoinfected counterparts, possibly mediated through synergetic persistent inflammation, microbial translocation, or elevated "traditional" risk factors such as blood pressure. (41) It has been suggested that NAFLD partially mediates CVD risk in HIV patients (2) and that the relationship between HCV and atherosclerosis is mediated by steatosis. (5) In the general population, an FLI ≥ 60 has been associated with the risk of stroke in men.…”

“…A backward procedure based on the Wald test was used to select the adjustment variables kept in the final multivariable model (threshold of significance set at P ≤ 0.05). The final multivariable model was adjusted for gender and three age categories (40)(41)(42)(43)(44)(45)(46)(47)(48)(49), and ≥50 years), irrespective of their P values. We tested for the presence of confounding factors: each nonsignificant variable was tested for its potential confounding effect in the multivariable model, i.e., whether the inclusion of that variable changed at least one of the coefficients of the other variables by >25%.…”