Brief Report: Prevalence of Peripheral Artery Disease Is Higher in Persons Living With HIV Compared With Uninfected Controls : JAIDS Journal of Acquired Immune Deficiency Syndromes

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Brief Report: Prevalence of Peripheral Artery Disease Is Higher in Persons Living With HIV Compared With Uninfected Controls

Knudsen, Andreas D. MD*,†; Gelpi, Marco MD*; Afzal, Shoaib MD, PhD; Ronit, Andreas MD*; Roen, Ashley MSc§; Mocroft, Amanda MSc§; Lundgren, Jens MD, DMSc║,¶; Nordestgaard, Børge MD, DMSc‡,#; Sillesen, Henrik MD, DMSc**; Lebech, Anne-Mette MD, DMSc¶,††; Køber, Lars MD, DMSc; Kofoed, Klaus F. MD, DMSc; Nielsen, Susanne D. MD, DMSc*

Author Information
JAIDS Journal of Acquired Immune Deficiency Syndromes: November 1, 2018 - Volume 79 - Issue 3 - p 381-385
doi: 10.1097/QAI.0000000000001795

Abstract

INTRODUCTION

People living with HIV (PLWH) now have life expectancies approaching that of the general population and may be more prone to age-related comorbidities.1,2 Among comorbidities, cardiovascular disease (CVD) with atherosclerotic lesions of the coronary and carotid vessels has received much attention as CVD is a leading cause of mortality in PLWH.3

Peripheral artery disease (PAD) is a manifestation of atherosclerosis that may lead to decreased blood supply and ischemic calf pain. With time, occlusive disease may lead to vascular ulcerations, gangrene, and ultimately amputation.4 Although, PLWH are at higher risk of CVD in general, PAD has been comparatively less well-explored in this population.2,5 Existing estimates of the prevalence of PAD in PLWH are conflicting, and studies report both higher and lower disease burden among PLWH compared with that of the uninfected population.1,6–10 PAD can easily and safely be assessed by calculating the ratio of systolic blood pressure (SBP) measured at the ankle to the SBP of the brachial artery. Validated against gold standard angiography, the ankle–brachial index (ABI) has been found to be a sensitive and extremely specific marker for occlusive PAD.11 Using ABI, we sought to investigate the prevalence and risk factors of PAD in a well-characterized population of PLWH compared with an uninfected population from the same geographical area matched on age and sex. We hypothesized that the prevalence of PAD was higher in PLWH than in uninfected, and that HIV is an independent risk factor for PAD.

METHODS

Study Design

From the Copenhagen comorbidity in HIV infection (COCOMO) study, participants older than 40 years were included. The COCOMO study is a longitudinal cohort study with the aim of assessing the burden and mechanism of non-AIDS comorbidities in PLWH. Inclusion criteria were a positive HIV test and 18 years of age or older. The procedures for recruitment and data collection have been described elsewhere.12,13

From the Copenhagen General Population Study (CGPS), age- and sex-matched uninfected participants were included with the aim of 14 controls per PLWH. Because of population size limitations, those younger than 60 years of age were matched 1:11, whereas those older than 60 years were matched 1:14.

Ethical approval was obtained by the Regional Ethics Committee of Copenhagen (COCOMO:H-15017350; CGPS:H-KF-01-144/01). Written informed consent was obtained from all participants.

Data Acquisition

Information about participants' demographics, family history, smoking, and medication was collected using identically structured questionnaires in COCOMO and CGPS. Participants were asked whether they experienced lower extremity pain after having walked some distance with no pain on onset of walking. If they responded affirmatively, they were further asked whether symptoms regressed after standing. “Symptoms of PAD” was defined as affirmative response to all of the above, irrespective of ABI.

Data regarding HIV infection were obtained from a review of medical charts of COCOMO participants.

All physical examinations were performed by trained medical staff, using an identical protocol in both COCOMO and CGPS.

Blood pressure (BP) was measured after 5-minute rest and with the subject in sitting position, using an automatic digital BP monitor.

Ankle–Brachial Index and PAD

ABI was measured in accordance with American Heart Association, American College of Cardiology and European guidelines.4,11 In supine position with head and ankles fully supported using a Doppler instrument (Sonotrax Basic A 294534; Edan, San Diego, CA), the pressure at which the flow in the posterior tibial artery was clamped was determined in both lower extremities.

Continuous ABI was calculated as the ratio of the lower of the SBPs of the left and right legs to the highest brachial SBP.

High ABI (≥1.4) is frequently due to arterial noncompressibility with concomitant vessel stenosis, but PAD cannot be diagnosed or excluded in these cases using ABI alone.14 As such, ABI ≥1.4 was coded as noncompressible and excluded.

PAD was defined as ABI ≤0.9 in one or both legs regardless of symptoms.

Symptomatic PAD was defined as symptoms of PAD in a person with PAD.

Biochemistry

Nonfasting venous blood was collected and analyzed for low-density lipoprotein cholesterol (LDL-C), glycated hemoglobin (HbA1c), high-sensitivity C-reactive protein (hsCRP), and glucose. All blood samples from both COCOMO and CGPS participants were analyzed at the same laboratory.

Hypertension, Body Mass Index, and Lipids

In accordance with the Joint National Committee on high BP,15 hypertension was defined as current antihypertensive treatment and/or SBP ≥140 and/or diastolic BP ≥90 mm Hg.

Body mass index (BMI) was defined according to the WHO classification (<18.5 underweight, 18.5–24.99 normal weight, 25–29.99 overweight, and ≥30 obese).16

Elevated LDL-C (eLDL-C) was defined as LDL-C ≥160 mg/dL (4.14 mM) and/or current lipid-lowering treatment.17,18

Statistics

A 95% binomial proportion confidence interval (CI) for PAD was calculated. Student t tests or Mann–Whitney U tests were used for comparison of continuous data, and χ2 tests were used for categorical data. Crude odds ratios (ORs) were calculated. We assessed whether independent variables were associated with a PAD or symptomatic PAD using multivariable logistic regression analyses adjusted for known predictors for PAD in the general population. We prespecified 2 models: model 1 included known predictors of vascular disease: age, sex, hypertension, diabetes, eLDL-C, and smoking status19; model 2 included all covariates in model 1 and additionally contained hsCRP, a marker of inflammation. A priori, we aimed to assess the interaction between PAD and HIV with age, hypertension, and smoking status, in a fully adjusted model. To investigate the impact of setting a lower threshold for eLDL-C, we conducted a sensitivity analysis with eLDL-C defined as LDL-C ≥116 mg/dL (3.00 mM).

A P value less than 0.05 was used to infer statistical significance. All analyses were generated using SAS software v9.4 (SAS Institute Inc., Cary, NC).

RESULTS

From the COCOMO study and CGPS, 908 PLWH and 11,106 uninfected controls included. PLWH were slightly younger, had a higher proportion of current smokers and persons of non-Scandinavian descent but a lower mean BMI, and a lower proportion with hypertension. PLWH were more likely to have symptoms of PAD (Table 1). Most PLWH were well-treated (Table, Supplemental Digital Content, https://links.lww.com/QAI/B192).

T1
TABLE 1.:
Demographic Characteristics

Peripheral Artery Disease

PAD was found in 112 PLWH [12% (95% CI: 10 to 14)] and in 623 controls [6% (95% CI: 5 to 6)] (P < 0.001). The mean ABI in PLWH and controls did not differ [1.1 (1.1–1.1) vs 1.1 (1.1–1.1) P = 0.942]. In univariate analyses, PAD was associated with HIV [OR: 2.4 (95% CI: 1.9 to 2.9)], age [OR per decade: 1.4 (95% CI: 1.3 to 1.6)], diabetes [OR: 2.0 (95% CI: 1.5 to 2.7)], smoking status [OR if current smoker: 3.1 (95% CI: 2.5 to 3.9)], hypertension [OR: 1.9 (95% CI: 1.6 to 2.3)], kidney function [OR per 10 mL decrease in estimated glomerular filtration rate: 1.2 (95% CI: 1.1 to 1.3)], and symptoms of PAD [OR: 11.6 (95% CI: 8.1 to 16.6)]. Being overweight or obese (BMI ≥ 25) compared with normal weight was negatively associated with PAD [OR: 0.8 (95% CI: 0.7 to 0.9)]. After adjusting for CVD risk factors (model 1), these associations did not change, and in addition, we found female sex to be associated with PAD. Further adjustment for hsCRP (model 2) did not alter these findings (Fig. 1) nor did lowering the threshold of eLDL-C from 160 mg/dL to 116 mg/dL. Reported outcomes in Figure 1 are adjusted for model 2.

F1
FIGURE 1.:
Adjusted OR of PAD. Odds ratio of PAD, adjusted for a predefined model with known cardiovascular risk factors including age, sex, hypertension, diabetes, eLDL-C, smoking status, and high-sensitivity C-reactive protein (adjusted for model 2).

Each 10-year increase in age doubled the risk of PAD among PLWH [OR 2.02 (95% CI: 1.48 to 2.76)] but raised it only by 36% among uninfected controls [1.36 (95% CI: 1.23 to 1.50)] (P = 0.0517, test for interaction). There was no interaction between HIV and smoking or HIV and hypertension for PAD (P values for interaction were 0.5668 and 0.8852, respectively). HIV was not associated with symptomatic PAD (P = 0.1189, adjusted P = 0.3216).

Within PLWH, age, female sex, smoking status, hypertension, intermittent claudication, and kidney function were associated with PAD (Fig. 1). By contrast, HIV-related factors including a previous diagnosis of AIDS, CD4 nadir, CD4 count, CD4:CD8-ratio, hepatitis C virus coinfection, duration of combination antiretroviral therapy, and duration of HIV infection were not associated with PAD (all P > 0.05).

DISCUSSION

PLWH had higher prevalence of PAD and symptoms of PAD than uninfected controls matched on age and sex and recruited from the same geographical area. HIV remained a risk factor for PAD after adjusting for traditional CVD risk factors. Regardless of HIV status, traditional risk factors of CVD were associated with PAD, but we did not find any associations between PAD- and HIV-specific variables in PLWH.

From previous studies, no consensus has been reached on whether HIV infection poses an independent risk of PAD, and both higher and lower prevalence of PAD in PLWH compared with the general population has been reported.1,6–8,20–23 However, few of these studies have included controls, and as PAD prevalence increases with age, direct comparison with general population studies has been difficult. This study uses a very well-characterized control population with all variables collected in identical fashion by trained medical staff, using the same equipment in PLWH and uninfected controls. Furthermore, both populations were enrolled over the same period, live in the same geographical area, and are of the same age. As such, we have excellent comparability between the PLWH and the uninfected controls. Of note, PLWH and controls were asked identical, but not validated questions regarding symptoms of PAD. Hence, we may falsely have classified differential diagnoses (eg, neurospinal disease) as symptoms of PAD, but this misclassification would apply to both PLWH and controls equally. The Edinburgh claudication questionnaire24 or similar would have allowed us to describe the level of symptomatic disease with a greater degree of certainty. Because of logistic reasons, it was not possible to include the Edinburgh claudication questionnaire in our study.

HIV-related variables have been shown to predict CVD including atherosclerotic carotid artery disease,18–20,25 but data are less clear with regard to lower extremity PAD.21,26 We found traditional CVD risk factors but not HIV-related variables to predict PAD. This is in agreement with previous findings,6,10,21 although one study found a CD4+ T cell count of <200 cells/µL to predict PAD.8 Few COCOMO participants have detectable viral replication or current CD4+ T cell count below 200 cells/µL. To elucidate why HIV-related factors predict coronary and carotid atherosclerotic disease and not PAD requires studies in populations that are less well-treated. Although hsCRP is an inflammatory marker often found to be associated with CVD in HIV,27,28 additional adjustment for hsCRP did not alter the association between HIV and PAD in this study. Thus, we found no evidence to support that inflammation explains the excess risk of PAD among PLWH, but we cannot rule out that unmeasured inflammatory indices may contribute to the pathogenesis.

As evidenced by a borderline statistically significant interaction between HIV and age, age may influence risk of PAD to a greater extent among PLWH than among controls. Although we cannot rule out the impact of unknown confounders, this observation may support the notion of an accelerated or premature ageing/atherosclerotic process attributable to HIV status in itself.29,30

CONCLUSIONS

Prevalence of PAD and symptoms of PAD was higher among PLWH compared with uninfected controls, and remained so after adjusting for common CVD risk factors. We found some evidence that this relationship was more pronounced among older individuals. Our findings expand the evidence base that PLWH have excess arterial disease to also include PAD. To explain the exact biological mechanisms causing this excess risk requires focused investigation, as does the clinical implications from our findings. Further understanding of the modifiable CVD risk factors remains important in reducing the burden of PAD among PLWH.

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Keywords:

peripheral arterial disease; HIV infections; comorbidity; peripheral vascular diseases; cross-sectional studies

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