Abstract
Background:
People with human immunodeficiency virus (PWH) have an increased risk of cardiovascular disease (CVD). Prior cross-sectional data suggest there is a higher prevalence of abdominal aortic aneurysm (AAA) in PWH than in those without HIV. Whether PWH have an increased risk of incident AAA compared to those without HIV is unknown.
Methods:
We analyzed data among participants without prevalent AAA from the Veterans Aging Cohort Study, a prospective, observational, longitudinal cohort of veterans living with HIV and matched 1:2 with veterans living without HIV infection. We calculated AAA rates by HIV status and assessed the association between HIV infection and incident AAA using Cox proportional hazards models. We defined AAA using ICD-9/ICD-10/CPT codes and adjusted all models for demographics, CVD risk factors, and substance use. Secondary analyses examined the association between time varying CD4+ T cell count or HIV viral load and incident AAA.
Results:
Among 143,001 participants (43,766 with HIV), over a median follow-up of 8.7 years, there were 2,431 incident AAA events (26.4% among PWH). Rates of incident AAA per 1000 person-years were similar among PWH (2.0; 95% confidence interval [CI], 1.9–2.2) and people without HIV (2.2; 95% CI, 2.1–2.3). There was no evidence that HIV infection increased the risk of incident AAA compared to no HIV infection (adjusted hazard ratio [HRadj], 1.02; 95% CI, 0.92–1.13). In adjusted analyses with time-varying CD4+ T cell counts or HIV viral load, PWH with CD4+ T cell counts <200 cells/mm3 (HRadj, 1.29; 95% CI, 1.02–1.65) or HIV viral load ≥ 500 copies/mL (HRadj, 1.29; 95% CI, 1.09–1.52) had an increased risk of AAA compared to those without HIV.
Conclusions:
HIV infection is associated with an increased risk of AAA among those with low CD4+ T cell counts or elevated HIV viral load over time.
Keywords: abdominal aortic aneurysm, aneurysm, human immunodeficiency virus, epidemiology, prospective studies
Brief Summary:
In the Veterans Aging Cohort Study, people with HIV and controlled virus were not at higher risk of developing AAA than people without HIV.
Introduction
Antiretroviral therapy (ART) has greatly increased the lifespan of people with human immunodeficiency virus (PWH).1–4 Nevertheless, even with ART, PWH are faced with an increased risk of cardiovascular disease (CVD), including coronary artery disease (CAD),5,6 stroke,7,8 and peripheral artery disease (PAD).3 This excess risk is a function of the virus itself, some forms of antiretroviral therapy, and a high prevalence of traditional risk factors, especially smoking.9 The combination of HIV infection and traditional risk factors may result in increased levels of systemic inflammation,10 activation of innate and adaptive immune cells,11 and endothelial dysfunction,10 each of which may independently increase the risk of CVD.
Despite multiple studies linking HIV infection to a range of CVDs, reports examining the association between HIV infection and abdominal aortic aneurysm (AAA) are sparse.12,13 The most indicative report to date is a cross-sectional study reporting that PWH have a higher prevalence of AAA than matched uninfected controls.12 Prior data demonstrating T cell infiltration into the AAA vessel wall and perivascular tissue suggest a potential immunologic link between HIV and AAA.14–18 Some have further hypothesized that PWH, particularly those who have poorly controlled infection with lower CD4+ T cell counts and higher viral load, may also experience immunodeficiency-related bacterial invasion of the aortic wall triggering mycotic aneurysm formation, molecular mimicry between HIV proteins and the aortic wall leading to autoimmune-mediated aortic damage, and direct invasion of the aortic wall by the virus leading to extracellular matrix degradation.19,20 Whether HIV infection in the absence of high viral load and low CD4+ T cell count is associated with incident AAA is unknown.
The goal of this study was to determine whether HIV infection in the absence of high viral load and low CD4+ T cell count is associated with incident AAA. Further, we investigated whether lower CD4+ T cell counts, elevated HIV viral load, and established cardiovascular risk factors contributed to AAA risk among PWH.
Methods
The United States Veterans Healthcare Administration (VHA) does not allow identifiable data sets to be used by non-Veterans Affairs (VA) investigators. However, after meeting all requirements per VA regulations, a deidentified data set can be provided to qualified investigators.
Study Sample
The study sample included patients in the Veterans Aging Cohort Study (VACS) receiving clinical care from the VHA (n=146,144). VACS is a prospective, observational, longitudinal cohort study of veterans with HIV, matched 1:2 to veterans without HIV based on age, race/ethnicity, sex, year of enrollment, and geographic location.21,22 We extracted information regarding demographic and clinical data from the VA corporate data warehouse. The VHA Vital Status File (VSF) contains mortality data from multiple VA and non-VA data sources including the VBA Integrated Benefits System (IBS) Death File (formally known as the BIRLS Death file), Medicare and VA fee for service Vital Status File, and the Social Security Administration (SSA) Death Master File.
For the present study, we set patient baseline as the first ambulatory clinic visit on or after April 1, 2003 (Figure S1). We excluded patients with prevalent AAA defined by the presence of VHA, VHA fee-for-service, or Medicare International Classification of Disease (ICD)-9, or current procedural terminology (CPT) codes (Table S1) (n=1,283).23 We further excluded patients with no further clinical encounters after baseline (n=319), indeterminate HIV status (i.e., had a negative HIV screening test but had testing for HIV viral load or CD4+ T cell count [n = 866]), and those who seroconverted during the follow up period (n=675). After these exclusions, our final sample size was 143,001 patients (43,766 PWH and 99,235 people without HIV). The Institutional Review Boards of the Tennessee Valley Veterans Affairs Health Care System, West Haven Veterans Affairs Medical Center, and Vanderbilt University Medical Center approved this study. The VACS has a waiver of consent.
Exposure: HIV
We ascertained HIV status based on the presence of at least one inpatient or two outpatient ICD-9 codes for AIDS (042), asymptomatic HIV (V08), and/or diagnostic-related group codes (488–490) in the VA electronic medical record.22 HIV variables included CD4+ T cell count, HIV-1 RNA level, and ART use. We recorded CD4+ T cell count and HIV-1 RNA level, measured as part of routine clinical care, from VA electronic medical record data closest to and up to 180 days after baseline. We determined ART use (yes/no) from VA pharmacy data recorded within 180 days prior to or up to 7 days after the baseline and included the following drug classes: nucleoside reverse-transcriptase inhibitors (NRTI), nonnucleoside reverse-transcriptase inhibitors (NNRTI), and protease inhibitors (PI).24 More than 98% of veterans receive their ART from VA pharmacies.22
Outcome Variable
We defined the primary outcome, incident AAA, as the presence of ≥1 inpatient or ≥2 outpatient VA, VA fee for service, or Medicare ICD-9, ICD-10 or CPT codes for AAA or AAA repair (Table S1). Exploratory analyses separately examined AAA repair alone. We followed all patients from baseline until censoring at the time of incident AAA, death, or the last follow-up date of July 31, 2016. The analysis ended on this date to align with the availability of outcome data from the various data sources (VA, VA fee for service, and Medicare).
Covariates
We obtained covariates closest to the baseline date as previously described.6,25 Briefly, sociodemographic variables of age, sex, and race/ethnicity were determined through VHA administrative data. Additional covariates included smoking status, diabetes mellitus, prevalent CVD (myocardial infarction, stroke, coronary heart disease, or congestive heart failure), alcohol use disorder, hepatitis C infection, body mass index (BMI), hypertension, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides, statin therapy, estimated glomerular filtration rate (eGFR), and white blood cell count. We ascertained these additional covariates using clinical inpatient or outpatient and/or clinical laboratory data. Smoking status was categorized as never, current, or past, and we obtained these validated data from the VA Health Factor Dataset.26 Diabetes (yes/no) was identified using a previously validated metric that incorporates glucose measurements, hemoglobin A1c, antidiabetic agent use, and/or at least one inpatient or two outpatient ICD-9 codes for diabetes.27 We used ICD-9 codes to define prevalent CVD and alcohol use disorder.28 A comorbid condition was considered prevalent if present at any time prior to and up to 180 days after the baseline. Our analysis used detectable hepatitis C virus (HCV) RNA, positive antibody test, and/or documented diagnosis to define HCV infection.27,29 BMI, calculated as kg/m2, was assessed using the VA Health Factor Dataset. We defined hypertension as either a blood pressure of <140/90mmHg with antihypertensive medication use or a blood pressure ≥140/90mmHg using the mean of 3 outpatient clinical blood pressure measures closest to baseline. eGFR was calculated using the Chronic Kidney Disease Epidemiology Collaboration equation based on outpatient and clinical laboratory data.30
Statistical Analysis
Baseline characteristics were stratified by HIV status. We reported medians (interquartile range) for continuous variables and frequencies (percentage) for categorical variables. To assess between group differences in baseline covariates, we used a t-test or Wilcoxon rank-sum test for continuous data and the χ2 test for categorical data. Additionally, we plotted unadjusted Kaplan-Meier survival curves stratified by age and HIV status and performed log-rank tests to compare the various groups. Furthermore, we calculated incident AAA rates per 1000 person years stratified by HIV status as well as baseline CD4+ T cell count and HIV viral load. In supplemental analyses, we plotted unadjusted Kaplan-Meier survival curves of AAA among patients without a history of smoking.
We used age- and sex-adjusted as well as fully adjusted Cox proportional hazards regression models to compute hazard ratios estimating the risk of incident AAA in PWH versus those without HIV.31 We verified fulfillment of the proportional hazards assumptions through examination of Schoenfeld residuals over time. We further categorized PWH by CD4+ T cell count or HIV viral load to assess the association between AAA risk and HIV severity. The fully adjusted Cox proportional hazards regression model included the following covariates: age, sex, race, hypertension, diabetes, LDL-C, HDL-C, triglycerides, statin use, prevalent CVD, hepatitis C, smoking status, eGFR, hemoglobin, BMI, and alcohol use disorder. We repeated the analysis using CD4+ T cell count or HIV viral load data as time-varying variables. This means that each participant contributed person-time to the CD4+ T cell count or HIV viral load category reflecting their status every time these biomarkers were measured.6 Therefore, follow-up time was broken into segments of time based on updated HIV biomarker data, where an individual’s HIV biomarker values were assigned the most recent values from the date until the next measurement. As a sensitivity analysis, we restricted the cohort to never smokers to investigate whether associations persisted in this cohort. This sensitivity analysis included the following Cox proportional hazards regression models: age- and sex-adjusted, fully adjusted, and fully adjusted with time varying CD4+ T cell count and HIV viral load data. Statistical significance for the two-sided p-value was set at 0.05.
To determine which of our covariates were associated with incident AAA in PWH, we then limited our analytic cohort to PWH. In these analyses, we further adjusted for HIV-specific factors, including continuous CD4+ T cell count, continuous HIV viral load, and ART regimen at baseline and as time-varying covariates (CD4+ T cell count and HIV viral load only).
Missing data were imputed using multiple imputation by chained equations with five separate imputed datasets based on predictive mean matching using the mice library (version 3.11.0) of R programming language.32 Cox survival models were fitted in each imputed dataset and then combined to obtain pooled regression coefficients and their standard errors. Matching was performed when VACS was created and was based on age, race/ethnicity, site of care, and gender using grouped matching when incident cases were added to the cohort on an annual basis. No additional matching was performed for the present analyses. All analyses were performed using R software (version 4.0.2; www.r-project.org).
Results
The total population of 143,001 veterans included 43,766 PWH and 99,235 people without HIV. The mean age was 49.6 years among PWH and 50.6 years among people without HIV (Table 1). The majority of both groups were male, and nearly half were Black. At baseline, PWH had a higher prevalence of current smoking, but a lower prevalence of diabetes, CVD, hypertension, and statin use compared to people without HIV. Among PWH, the median CD4+ T cell count at baseline was 386 cells/mm3 with a median HIV-1 viral load of 1,004 copies/mL (37% achieved viral suppression).
Table 1.
Baseline characteristics of included patients
| People with HIV (n=43,766)* | People without HIV (n=99,235)† | |
|---|---|---|
| Age, mean (SD) | 49.6 (10.7) | 50.6 (10.5) |
| Male, N (%) | 42553 (97.2) | 96,418 (97.2) |
| Race, N (%) | ||
| White | 17,471 (39.9) | 39,758 (40.1) |
| Black | 20,909 (47.8) | 46,837 (47.2) |
| Hispanic | 3,465 (7.9) | 8,416 (8.5) |
| Other | 1,921 (4.4) | 4,224 (4.3) |
| Smoking status, N (%) | ||
| Current | 16,845 (38.5) | 35,256 (35.5) |
| Former | 5,023 (11.5) | 13,431 (13.5) |
| Never | 8,901 (20.3) | 22,861 (23.0) |
| Diabetes, N (%) | 4,986 (11.4) | 19,057 (19.2) |
| Prevalent CVD, N (%) | 5,591 (12.8) | 17,018 (17.1) |
| HCV infection, N (%) | ||
| HCV negative | 28,590 (65.3) | 63,155 (63.6) |
| HCV positive viral load | 9,619 (22.0) | 10,335 (10.4) |
| HCV positive antibody only | 2,918 (6.7) | 3,241 (3.3) |
| Never tested/unknown | 2,602 (5.9) | 22,432 (22.6) |
| History of alcohol use disorder, N (%) | 11,188 (25.6) | 26,483 (26.7) |
| Body mass index, mean (SD), kg/m2 | 25.9 (4.9) | 29.6 (6.1) |
| Hypertension, N (%) | 24,270 (55.5) | 66,905 (67.4) |
| LDL cholesterol, median (Q1, Q3), mg/dL | 101 (79, 126) | 112 (89, 137) |
| HDL cholesterol, median (Q1, Q3), mg/dL | 40 (32, 50) | 43 (36, 52) |
| Triglycerides, median (Q1, Q3), mg/dL | 138 (93–216) | 124 (83–191) |
| Statin therapy, N (%) | 7,789 (17.8) | 31,280 (31.5) |
| eGFR, median (Q1, Q3), mL/min/1.73 m2 | 93.3 (77.6–109.8) | 89.5 (75.7–104.1) |
| Hemoglobin, median (Q1, Q3), g/dL | 14.1 (12.9–15.2) | 14.7 (13.8–15.5) |
| White blood cell count, median (Q1, Q3), cells/mm | 5.3 (4.1–6.8) | 6.7 (5.4–8.2) |
| HIV Specific Variables | ||
| CD4+ T cell count, cells/mm3 | -- | |
| <200 | 8,360 (19.1) | |
| 200–500 | 14,725 (33.6) | |
| ≥500 | 12,539 (28.7) | |
| HIV-1 RNA, copies/mL | -- | |
| <500 | 16,385 (37.4) | |
| ≥500 | 19,202 (43.9) | |
| ART Regimen | -- | |
| NRTI + PI | 17,068 (39.0) | |
| NRTI + NNRTI | 16,988 (38.8) | |
| NRTI + NNRTI + PI & other combinations | 1,274 (2.9) | |
| No ART | 25,384 (58.0) |
ART, antiretroviral therapy; CVD, cardiovascular disease; eGFR, estimated glomerular filtration rate; HCV, hepatitis C virus; HDL, high-density lipoprotein; HIV, human immunodeficiency virus; LDL, low-density lipoprotein; NNRTI, non-nucleoside reverse transcriptase inhibitors; NRTI, nucleoside reverse transcriptase inhibitors; PI, protease inhibitor; RNA, ribonucleic acid; SD, standard deviation
Between group differences were assessed using a t-test or the Wilcoxon rank-sum test for continuous data and the χ2 test for categorical data. Groups were different in a statistically significant manner (p < 0.05) for all covariates except for male sex (p=0.40).
Number missing: 12,997 (smoking status); 37 (hepatitis C); 1,619 (body mass index); 572 (hypertension); 8,323 (LDL-C); 7,845 (HDL-C); 7,317 (triglycerides); 2,452 (eGFR); 2,140 (hemoglobin); 2,133 (white blood cell count); 8,142 (CD4+ count); 8,179 (HIV viral load)
Number missing: 27,687 (smoking status); 72 (hepatitis C); 6,043 (body mass index); 3,805 (hypertension); 19,613 (LDL-C); 18,823 (HDL-C); 18,934 (triglycerides); 9,636 (eGFR); 10,581 (hemoglobin); 10,670 (white blood cell count)
Over a median follow-up period of 8.7 years, there were a total of 2,431 incident AAA events (26.4%, 641 among PWH), including 357 cases of surgical AAA repair (25.5%, 91 among PWH). Kaplan-Meier AAA-free survival curves showed a greater occurrence of AAA with increasing age, but these curves did not show evidence of higher unadjusted risk for PWH (log-rank p-value <0.001) (Figure 1).
Figure 1: Kaplan-Meier Curves of AAA-Free Survival Stratified by HIV Status and Age.

Individuals are stratified by baseline age in years as well as HIV status at the time of entry into the cohort. Kaplan-Meier curves are unadjusted.
AAA, abdominal aortic aneurysm; HIV, human immunodeficiency virus
Unadjusted AAA incidence rates were similar among PWH compared to those without HIV (Table 2). This finding persisted regardless of baseline CD4+ T cell count, baseline HIV viral load (Table 2), or stratification by age group (Table S2). Similarly, there was no difference in rates of AAA repair by HIV and age status (Table S2).
Table 2:
Rates and Risk of Overall AAA Stratified by HIV Status, CD4+ T Cell Count, and Viral Load
| AAA events/N§ | Rates/1000 PY (95% CI)§ | Age+sex adjusted AAA risk (95% CI) | Fully adjusted AAA risk (95% CI)* | Time-updated fully adjusted AAA risk (95% CI)† | |
|---|---|---|---|---|---|
| Stratified by HIV status | |||||
| People without HIV | 1,790/99,235 | 2.23 (2.13–2.34) | 1.00 | 1.00 | 1.00 |
| PWH | 641/43,766 | 2.01 (1.86–2.17) | 1.03 (0.94–1.13) | 1.02 (0.92–1.13) | 1.02 (0.92–1.13) |
| Stratified by HIV status and CD4+ T cell count | |||||
| People without HIV | 1,790/99,235 | 2.23 (2.13–2.34) | 1.00 | 1.00 | 1.00 |
| PWH, CD4+ ≥ 500 cells/mm3 | 178/12,539 | 1.82 (1.57–2.10) | 1.02 (0.89–1.17) | 0.99 (0.86–1.14) | 0.92 (0.81–1.05) |
| PWH, 200 ≤ CD4+ < 500 cells/mm3 | 214/14,725 | 1.87 (1.63–2.13) | 1.00 (0.87–1.15) | 1.00 (0.86–1.16) | 1.07 (0.93–1.24) |
| PWH, CD4+ < 200 cells/mm3 | 103/8,360 | 1.88 (1.54–2.27) | 1.11 (0.90–1.37) | 1.17 (0.94–1.45) | 1.29 (1.02–1.65) |
| PWH, missing CD4+ | 146/8,142 | 2.85 (2.41–3.34) | -- | -- | -- |
| Stratified by HIV status and viral load | |||||
| People without HIV | 1,790/99,235 | 2.23 (2.13–2.34) | 1.00 | 1.00 | 1.00 |
| PWH, VL < 500 copies/mL | 274/16,385 | 2.12 (1.88–2.38) | 1.01 (0.89–1.13) | 0.99 (0.87–1.12) | 0.95 (0.85–1.07) |
| PWH, VL ≥ 500 copies/mL | 224/19,202 | 1.63 (1.42–1.85) | 1.06 (0.93–1.20) | 1.07 (0.94–1.22) | 1.29 (1.09–1.52) |
| PWH, missing viral load | 143/8,179 | 2.79 (2.36–3.27) | -- | -- | -- |
AAA, abdominal aortic aneurysm; HIV, human immunodeficiency virus; PWH, people with HIV; PY, person years; VL, viral load
Stratification was done using baseline values of CD4+ and HIV viral load.
Adjusted for age, sex, race, hypertension, diabetes, LDL-C, HDL-C, triglycerides, statin use, prevalent CVD, hepatitis C, smoking status, eGFR, hemoglobin, BMI, and alcohol use disorder. Missing values were imputed using multiple imputation. Stratification was performed using baseline CD4+ count and viral load.
Adjusted for all factors in (*) but stratification was performed using time-updated CD4+ count and viral load.
Missing values were imputed using multiple imputation.
In age- and sex-adjusted models, there was no evidence that HIV infection was associated with an increased risk of AAA (hazard ratio [HR], 1.03; 95% confidence interval [CI], 0.94–1.13). This finding persisted in the fully adjusted models (HRadj, 1.02; 95% CI, 0.92–1.13) (Table 2). Models stratified by baseline CD4+ T cell count and HIV viral load similarly did not show that HIV infection was associated with incident AAA. However, when CD4+ T cell count and HIV viral load were treated as time-varying covariates, the presence of CD4+ T cell counts <200 cells/mm3 (HRadj, 1.29; 95% CI, 1.02–1.65) or HIV viral loads >500 copies/mL (HRadj, 1.29; 95% CI, 1.09–1.52) was associated with higher risks of incident AAA compared to those without HIV infection.
Among PWH, age, current and former smoking, prevalent CVD, and hypertension were all significantly associated with an increased risk of incident AAA (Table 3). In contrast, Black and Hispanic (as compared to White) patients as well as those with prevalent diabetes or elevated HDL-C were significantly associated with a lower risk of incident AAA. These associations remained unchanged even after adjusting for time varying CD4+ T cell counts or HIV viral load.
Table 3.
Associations Between Clinical Characteristics and Overall AAA Among People with HIV
| Hazard Ratio (95% CI) Using Baseline Covariates | Hazard Ratio (95% CI) Using Time-Updated CD4+ Count and Viral Load | |
|---|---|---|
| Age, 10 y | 2.18 (1.99–2.38) | 2.19 (2.00–2.39) |
| Male sex | 1.11 (0.57–2.17) | 1.10 (0.56–2.15) |
| Race | ||
| Black vs. White | 0.82 (0.68–0.98) | 0.81 (0.67–0.97) |
| Hispanic vs. White | 0.67 (0.48–0.93) | 0.67 (0.48–0.94) |
| Other vs. White | 0.86 (0.53–1.39) | 0.87 (0.54–1.40) |
| Smoking status | ||
| Current vs. never | 1.95 (1.57–2.43) | 2.04 (1.62–2.58) |
| Former vs. never | 1.48 (1.06–2.06) | 1.50 (1.13–1.99) |
| Diabetes | 0.72 (0.56–0.93) | 0.72 (0.56–0.92) |
| Prevalent CVD | 1.77 (1.46–2.14) | 1.75 (1.45–2.12) |
| HCV infection | ||
| Positive vs. negative | 0.96 (0.77–1.19) | 0.94 (0.76–1.17) |
| Antibody only vs. negative | 1.17 (0.85–1.59) | 1.14 (0.83–1.56) |
| Never test/unknown vs. negative | 1.01 (0.73–1.39) | 0.99 (0.72–1.37) |
| History of alcohol use disorder | 1.09 (0.89–1.33) | 1.06 (0.87–1.30) |
| Body mass index* | 0.93 (0.85–1.02) | 0.94 (0.86–1.03) |
| Hypertension | 1.53 (1.24–1.89) | 1.53 (1.24–1.89) |
| LDL cholesterol* | 1.09 (0.99–1.19) | 1.09 (1.00–1.18) |
| HDL cholesterol* | 0.87 (0.79–0.96) | 0.87 (0.78–0.96) |
| Triglycerides* | 0.99 (0.90–1.07) | 0.98 (0.90–1.08) |
| Statin therapy | 1.07 (0.88–1.30) | 1.09 (0.90–1.33) |
| eGFR* | 0.93 (0.84–1.02) | 0.94 (0.85–1.03) |
| Hemoglobin* | 1.01 (0.92–1.12) | 1.00 (0.92–1.10) |
| White blood cell count, cells/mm* | 1.04 (0.96–1.13) | 1.03 (0.96–1.10) |
| HIV Specific Variables | ||
| CD4+ T cell count, cells/mm | ||
| 200–499 vs. ≥ 500 | 1.02 (0.83–1.24) | 1.14 (0.95–1.36) |
| <200 vs. ≥ 500 | 1.14 (0.86–1.50) | 1.27 (0.95–1.70) |
| HIV-1 RNA, copies/mL | ||
| ≥500 vs. < 500 | 0.98 (0.81–1.18) | 1.21 (0.98–1.48) |
| ART Regimen | ||
| NRTI + PI vs. no ART | 1.43 (0.44–4.65) | 1.44 (0.44–4.67) |
| NRTI + NNRTI vs. no ART | 0.59 (0.18–1.92) | 0.61 (0.19–1.97) |
| Other vs. no ART | 1.38 (0.68–2.79) | 1.45 (0.71–2.94) |
AAA, abdominal aortic aneurysm; ART, antiretroviral therapy; CVD, cardiovascular disease; eGFR, estimated glomerular filtration rate; HCV, hepatitis C virus; HDL, high-density lipoprotein; HIV, human immunodeficiency virus; LDL, low-density lipoprotein; NNRTI, non-nucleoside reverse transcriptase inhibitors; NRTI, nucleoside reverse transcriptase inhibitors; PI, protease inhibitor; RNA, ribonucleic acid
Cox regression models included all covariates listed in Table 3.
Hazard ratio per standard deviation increase
Exploratory analyses among never smokers did not show evidence that HIV infection was associated with an increased risk of incident AAA (HRadj, 1.04; 95% CI, 0.81–1.35) (Table 4). This lack of evidence persisted in models stratified by baseline CD4+ T cell count or HIV viral load. Among never smokers, models examining time-varying CD4+ T cell count and HIV viral load also showed no evidence of association for either low CD4+ T cell count (<200 cells/mm3) or high HIV viral load (>500 copies/mL) with incident AAA. Kaplan-Meier AAA-free survival curves among never smokers did not differ by HIV status (log-rank p-value <0.001) (Figure S2).
Table 4:
Rates and Risk of Overall AAA Stratified by HIV Status, CD4+ T Cell Count, and Viral Load Among Never Smokers
| AAA events/N | Rates/1000 PY (95% CI) | Age+sex adjusted AAA risk (95% CI) | Fully adjusted AAA risk (95% CI)* | Time-updated fully adjusted AAA risk (95% CI)† | |
|---|---|---|---|---|---|
| Stratified by HIV status | |||||
| People without HIV | 208/22,861 | 1.20 (1.04–1.37) | 1.00 | 1.00 | 1.00 |
| PWH | 73/8,901 | 1.20 (0.95–1.50) | 1.02 (0.80–1.31) | 1.04 (0.81–1.35) | 1.05 (0.81–1.37) |
| Stratified by HIV status and CD4+ T cell count | |||||
| People without HIV | 208/22,861 | 1.20 (1.04–1.37) | 1.00 | 1.00 | 1.00 |
| PWH, CD4+ ≥ 500 cells/mm3 | 19/2,746 | 0.99 (0.61–1.51) | 0.82 (0.53–1.24) | 0.83 (0.55–1.25) | 0.73 (0.48–1.11) |
| PWH, 200 ≤ CD4+ < 500 cells/mm3 | 25/3,026 | 1.13 (0.74–1.63) | 1.04 (0.75–1.44) | 1.07 (0.76–1.50) | 1.24 (0.90–1.70) |
| PWH, CD4+ < 200 cells/mm3 | 17/1,569 | 1.70 (1.01–2.64) | 1.40 (0.88–2.21) | 1.47 (0.89–2.45) | 1.80 (0.99–3.27) |
| PWH, missing CD4+ | 12/1,560 | 1.30 (0.69–2.18) | -- | -- | -- |
| Stratified by HIV status and viral load | |||||
| People without HIV | 208/22,861 | 1.20 (1.04–1.37) | 1.00 | 1.00 | 1.00 |
| PWH, VL < 500 copies/mL | 36/3,456 | 1.41 (1.00–1.92) | 1.00 (0.73–1.36) | 1.00 (0.73–1.37) | 1.01 (0.75–1.34) |
| PWH, VL ≥ 500 copies/mL | 24/3,869 | 0.93 (0.61–1.35) | 1.06 (0.79–1.43) | 1.10 (0.79–1.52) | 1.18 (0.73–1.92) |
| PWH, missing viral load | 13/1,576 | 1.40 (0.77–2.31) | -- | -- | -- |
AAA, abdominal aortic aneurysm; HIV, human immunodeficiency virus; PWH, people with HIV; PY, person years; VL, viral load
Adjusted for age, sex, race, hypertension, diabetes, LDL-C, HDL-C, triglycerides, statin use, prevalent CVD, hepatitis C, smoking status, eGFR, hemoglobin, BMI, and alcohol use disorder. Missing values were imputed using multiple imputation. Stratification was performed using baseline CD4+ count and viral load.
Adjusted for age, sex, race, hypertension, diabetes, LDL-C, HDL-C, triglycerides, statin use, prevalent CVD, hepatitis C, smoking status, eGFR, hemoglobin, BMI, alcohol use disorder. Missing values were imputed using multiple imputation. Stratification was performed using time-updated CD4+ count and viral load.
Discussion
In this large, racially diverse national cohort of more than 143,000 veterans without a clinical history of AAA, there was no evidence that HIV infection was associated with an increased risk of incident AAA after adjusting for traditional CVD risk factors, substance use, and other important comorbidities. In contrast, patients with low CD4+ T cell counts or high HIV viral loads over time did have an increased risk of incident AAA compared to those without HIV infection. Among PWH, age, current and former smoking, prevalent CVD, hypertension, and elevated LDL-C were all significantly associated with an increased risk of incident AAA whereas Black and Hispanic (as compared to White) patients as well as those with prevalent diabetes and elevated HDL-C were significantly associated with a lower risk of incident AAA. In exploratory analyses, there was also no evidence that HIV was associated with incident AAA among never smokers.
To our knowledge, this is the largest and only study examining the association between HIV infection and incident AAA that also accounts for time-updated measures of viral suppression. Our findings suggest that, compared to people without HIV, there is an excess risk of AAA among PWH but only among those who have sustained low CD4+ T cell counts or elevated HIV viral load. Further, we also reported that among PWH, traditional risk factors, like smoking and hypertension, were associated with an increased risk of AAA. Until recently there were only rare case reports linking various aortic pathologies to HIV infection.33,34 In 2021, a study reported a higher prevalence of AAA among PWH compared to matched controls.12 In contrast to our study, the Copenhagen Comorbidity in HIV Infection (COCOMO) study assessed the prevalence of both AAA and thoracic aortic aneurysms using screening computed tomography (CT) imaging of the aorta. AAA was defined as an abdominal aorta measuring at least 3.0 cm. Using this definition, the prevalence of AAA was 5.4% and 1.9% for people with and without HIV, respectively. The strongest risk factors for AAA were age and male sex; associations with traditional AAA risk factors such as smoking, hypertension, and hyperlipidemia did not reach statistical significance.
The inconsistencies between these two studies may be explained in part due to differences in study design, sample size, and definitions used for AAA. For example, the COCOMO study was a cross-sectional screening study involving 1,782 participants with largely controlled HIV designed to image the abdominal aorta to identify AAA of any size. The VACS was a prospective observational study involving 143,001 participants with varying degrees of HIV viral control and immunodeficiency designed to look at incident AAA and large AAA requiring surgery using administrative data across a national health care system. COCOMO had the advantage of detecting AAA of any size, whereas the VACS has the statistical power to examine HIV and other important risk factors with incident events and to further stratify these analyses by time updated HIV viral load and CD4+ T cell count. Taken together, these studies suggest that the HIV virus, particularly when not controlled, as well as traditional risk factors like smoking cigarettes and hypertension may be contributing to the development of AAA among PWH. Whether people with HIV are at risk for future smaller aneurysms and whether these smaller aneurysms are at risk of rupture at smaller sizes even with HIV viral control remains unclear.
The exact mechanism underlying the association of AAA among PWH who have low CD4+ T cell counts or poor HIV viral control compared to those without HIV remains unclear. This pattern is consistent with prior reports examining HIV and other CVD including acute myocardial infarction,6 stroke,7,8 and PAD.3 Prior work demonstrates that low CD4+ T cell counts and unsuppressed HIV viremia are associated with increases in systemic inflammation, immune activation, monocyte activation, altered coagulation, and endothelial dysfunction.11,25 Each of these may play an important role in the development of AAA.10,35–37 Whether a lack of HIV suppression and immunodeficiency also leads to HIV viral invasion of the aortic wall, extracellular matrix degradation, and subsequent AAA development is unclear.19,20 Characterization of ex vivo human AAA tissue suggest that inflammation and T cell infiltration are key features of AAA formation, and it is possible that immune cell dysregulation in poorly controlled HIV may similarly play a role in AAA development in this patient population.14–18 In this study, traditional AAA risk factors identified in the general population were also associated with incident AAA among those with HIV.
These findings have important implications for PWH. First and foremost, viral suppression and prevention of immunodeficiency remain critical in this population. While this is not a randomized controlled trial, we observed no excess risk of AAA among those who had suppressed HIV viral loads or elevated total CD4+ T cell counts over time. Second, the management of modifiable AAA risk factors, such as hypertension, and management of existing CVDs, are likely very important for the prevention of AAA. Successful treatment of cigarette smoking, however, may be essential. As with PAD, cigarette smoke is a major risk factor for AAA.38 Smoking is common among PWH and rarely treated; even when treated, it frequently results in relapse.9,39 However, recent studies demonstrate that pharmacotherapy can result in smoking cessation even among high-risk PWH who have multimorbidity and polysubstance use.40–42 In contrast, people of color and those with diabetes had a lower risk of incident AAA in the VACS. While etiologies underlying these associations are not clear, lower rates and risk of AAA in the Black community38 as well as in those with diabetes43 is a well described phenomenon in the general population.
There are several limitations of the current analysis. First, the study population is predominantly male, and our findings may not generalize to women. Second, subjects underwent AAA detection as part of clinical care rather than universal screening for the purposes of our study. It is possible that universal AAA screening could have impacted our findings through the identification of additional small AAAs, although the clinical significance of these remains unclear. Third, our outcomes were identified through administrative claims data and not manually adjudicated. Finally, our observational study design is potentially subject to residual confounding.
Conclusions
In a large, prospective epidemiologic assessment of incident AAA in a racially diverse population of over 143,000 people, we found evidence that HIV infection was associated with an increased risk of AAA among PWH who had low CD4+ T cell counts or lacked HIV viral suppression over time. Among PWH, the presence of established AAA risk factors was associated with an increased risk of AAA. Our results suggest that successful treatment of HIV and the identification and treatment of traditional, modifiable AAA risk factors may be important for the prevention of incident AAA among PWH. Future studies should examine the association between HIV and incident AAA and, if confirmed in other cohorts, should examine the underlying mechanisms for AAA among PWH.
Supplementary Material
Clinical Perspective.
1. What is new?
HIV infection was associated with an increased risk of incident AAA among people with HIV (PWH) who had low CD4+ T cell counts or lacked HIV viral suppression over time.
2. What are the clinical implications?
PWH with controlled virus are not at higher risk of AAA than people without HIV.
If confirmed in additional reports, screening for AAA among PWH with inadequate HIV control may be warranted.
Acknowledgments
This work uses data provided by patients and collected by the VA as part of their care and support. Resources from the Veteran Affairs Medical Center largely supported this work. The views in this paper are that of the authors and do not necessarily convey the view of any said department.
Sources of Funding
This work was supporting by funding from the American Heart Association 882067 and the National Institutes of Health K23 HL151871 (Aday) and U24 AA020794 (Justice). Access to VA/CMS data was provided by the Department of Veterans Affairs, Veterans’ Health Administration, Office of Research and Development, Health Services Research and Development, and the VA Information Resource Center.
Non-standard Abbreviations and Acronyms
- AAA
abdominal aortic aneurysm
- ART
antiretroviral therapy
- BMI
body mass index
- CAD
coronary artery disease
- CPT
current procedural terminology
- CVD
cardiovascular disease
- eGFR
estimated glomerular filtration rate
- HCV
hepatitis C virus
- HDL-C
high-density lipoprotein cholesterol
- IBS
Integrated Benefits System
- ICD
International Classification of Disease
- LDL-C
low-density lipoprotein cholesterol
- NNRTI
nonnucleoside reverse-transcriptase inhibitors
- NRTI
nucleoside reverse-transcriptase inhibitors
- PAD
peripheral artery disease
- PI
protease inhibitors
- PWH
people with HIV
- SSA
Social Security Administration
- VA
Veterans Affairs
- VACS
Veterans Aging Cohort Study
- VHA
Veterans Healthcare Administration
- VSF
Vital Status File
Footnotes
Disclosures
Dr. Beckman reports receiving consulting fees from JanOne, Janssen, and Novartis and research funds from Bristol Myers Squibb outside of the current work. Dr. Aday reports receiving consulting fees from OptumCare, CRC Oncology, and Aeglea outside of the current work. All other authors report no conflicts.
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