Abstract
Background:
Limited systematic data exist on HF phenotypes in contemporary HIV care, and no prior multicenter studies have investigated physician-adjudicated phenotypes and etiologies of HF in PWH.
Methods:
We adjudicated HF events and sub-phenotypes occurring between January 1, 2010 and December 31, 2021 at two large urban clinical centers within the CFAR Network of Integrated Clinical Systems (CNICS) cohort. Using Cox proportional hazard regression, hazard ratios were calculated to examine associations of HIV-specific and cardiometabolic risk factors with incident HF among PWH. Exploratory analyses investigated presence of physician-adjudicated ischemic and non-ischemic etiologies of HF.
Results:
Of 402 individuals with events screened as possible HF, 289 were adjudicated as HF. Of these 289, 77 were prevalent at baseline and 212 were incident. Higher viral load and lower CD4 T cell count were associated with incident HF. In addition, older age, smoking, hypertension, diabetes mellitus, history of myocardial infarction (MI), and renal insufficiency were associated with higher HF risk. Nonischemic HF etiologies were more common than ischemic, and HF with reduced ejection fraction (HFrEF) was more common than preserved ejection fraction (HFpEF). Despite distinct demographic and risk factor compositions between the two sites, HF phenotypes were similar.
Conclusion:
HIV viremia, low CD4 T cell count, traditional CVD risk factors, and renal insufficiency were associated with higher risk for HF. The predominant HF subtype was non-ischemic HF. While further studies are needed, our findings suggest HF prevention and management in PWH will require addressing complex interactions between HIV-related and traditional CVD risk factors.
Key words or phrases: HIV-associated heart failure, heart failure, adjudicated heart failure events, ischemic cardiomyopathy, nonischemic cardiomyopathy
Introduction:
People with HIV (PWH) are living longer and have higher rates of cardiovascular diseases (CVD) including myocardial infarction (MI), heart failure (HF), subclinical myocardial dysfunction, arrhythmias, pulmonary hypertension, and stroke, despite adequate viral suppression.1–5 The increased risk of CVD stems from complex interactions between accelerated atherosclerosis, dyslipidemia (including ART-associated), immune dysregulation and related persistent inflammation, viral co-infection, higher prevalence of traditional CVD risk factors, and social determinants of health associated with CVD.1
PWH are estimated to have a 1.5–2-fold greater risk for HF compared with people without HIV, and this risk is not entirely attributable to MI.1 This increased risk appears to apply for both HF with preserved ejection fraction (HFpEF), and HF with reduced ejection fraction (HFrEF), and is higher in individuals with uncontrolled viral loads (VL) and lower CD4 counts.6 However, individuals on ART without significant immune progression (e.g., CD4 decline) remain at higher risk of HF compared to individuals without HIV.7 Although HFrEF was the most common presentation of HF among PWH in the early ART era and prior, in recent years HFpEF has also been observed as more common in PWH than people without HIV.6 Furthermore, PWH have increased myocardial fibrosis on cardiac magnetic resonance imaging.8,9 Although prior studies have helped define the scope and associated risk factors of HF among PWH, few have investigated different subtypes (e.g., HFpEF versus HFrEF) and no large study to our knowledge has investigated physician-attributed etiologies of HF among PWH.
In the contemporary era, the pathophysiology of HIV-associated HF is diverse and includes metabolic dysregulation related to chronic infection/inflammation and certain antiretroviral drugs, impaired myocardial responses to ischemia,10 autonomic dysregulation, drug toxicity, and smoking.1 Studies have demonstrated an increased risk of CVD associated with certain combinations of ARTs. Specifically, ritonavir (a protease inhibitor [PI]), certain other PIs, and abacavir (a nucleoside reverse transcriptase inhibitor [NRTI]) cause platelet activation, which can eventually lead to accelerated cardiac fibrosis and cardiac dysfunction.11 A study by the D:A:D Study Group demonstrated that an increased exposure to PIs, but not NRTIs, was associated with increased risk of MI, and this risk was only partly explained by dyslipidemia.12
The diagnosis of HF is clinically complex, requiring incorporation of multiple subjective and objective diagnostic criteria. Prior studies have shown high rates of disagreements (>30%) of HF diagnosed using administrative codes compared to physician-adjudicated HF.13,14 Therefore, standardized definitions of HF utilizing physician adjudication, as advised by the American College of Cardiology and American Heart Association Task Force on Clinical Data Standards,15 offer the benefit of incorporating clinician insight and enhancing phenotypic precision; for instance, disentangling diverse physician-assessed etiologies of HF via intensive physician review of notes and procedures.
To address this gap we investigated, at two geographically and demographically distinct sites within the Centers for AIDS Research Network of Integrated Clinical Systems (CNICS) prospective cohort, incident adjudicated HF and associated risk factors, as well as explored adjudicated HF etiologies.
Methods:
Study population:
This study represents the first analysis of adjudicated HF within CNICS, a prospective observational cohort that integrates clinical data on ~48,000 PWH 18 years of age or older who have received routine clinical care at one of 9 sites in the United States (currently expanding to 10 sites).16 The present analysis includes the 2 sites selected based on their geographic, demographic, and clinical diversity to complete adjudication of HF events from January 1, 2010 to December 31, 2021 [University of Washington, Seattle (UW) and University of Alabama, Birmingham (UAB)]. Adjudication of HF events is now expanding to other CNICS sites. Institutional review boards at each study site reviewed and approved CNICS protocols for patient protection and provided general approval for secondary data analysis.
CNICS Data Repository:
Each CNICS site captures comprehensive clinical data from all outpatient and inpatient encounters, including laboratory test results such as VL, CD4 T cell count, cardiac biomarkers, medication data assessed from physician prescribing records and pharmacy system fill data, clinician diagnoses, and historical clinical information. In more recent years, participants engage in patient reported outcomes (PROs) to assess information on behaviors and outcomes such as smoking, substance use, and depression.
HF Adjudication:
First, we identified all eligible CNICS participants with possible HF, using an intentionally sensitive protocol that screens for the presence of any of the following: (1) any single inpatient or outpatient administrative code of HF or cardiomyopathy (International Classification of Diseases, Ninth Revision [ICD-9] codes 398.91, 402.X1, 404.X1, 404.X3, 415.0, 416.9, 428.XX; and/or ICD-10 codes I09.81, I11.0, I13.0, I13.2, I50.xx); and/or (2) Any B-type natriuretic peptide (BNP) >400 pg/mL or N-Terminal-proBNP (NT-proBNP) >450 pg/mL (age <50), >900 pg/dL (age 50–75), or >1,800 pg/dL (age >75). This information was captured from any type of visit (inpatient, outpatient, emergency department, HIV-treating physician, or other specialists). Following this screening protocol, two physician adjudicators independently implemented a validated protocol adapted from MESA (Multi-Ethnic Study of Atherosclerosis).17,18 Diagnosis of HF required all 3 of: (1) symptoms such as dyspnea or lower extremity swelling (or clearly documented HF by physicians, and on chronic HF medications if symptoms not noted), (2) physician written diagnosis of HF or cardiomyopathy in clinical notes, and (3) HF medication use. Physician diagnosis was defined as the presence of HF or an acceptable synonym. HF medication use included beta-blocker, angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, aldosterone antagonist, or a diuretic; of note, the vast majority of follow-up occurred prior to clinical trial- and guideline-driven adoption of sodium glucose cotransporter-2 inhibitors in HF management. In addition to the “probably HF” criteria, objective data was required for a diagnosis of “definite HF”, including (1) chest radiography with mention of volume overload/congestion, (2) echocardiogram with at least one of the following: left ventricular ejection fraction (LV EF) less than 50%, regional wall motion abnormalities, LV chamber dysfunction, diastolic dysfunction, moderate or greater valve disease. Physician adjudicators then determined the type of HF (not HF, probable HF, definite HF) and further classified HF based on EF (preserved, mid-range, reduced, or unknown EF), as well as etiology (ischemic, non-ischemic, mixed, or unknown). Non-ischemic HF was further sub-classified into valvular, infiltrative, inflammatory myocarditis, obstructive, toxic-recreational drugs, toxic-prescription drugs, hypertensive, uremic/renal, or other, with the ability for adjudicators to identify more than one etiology. The two physician reviewers performed adjudication independently. Disagreements were resolved by consensus or a third physician adjudicator if no consensus was reached. We combined probable and definite HF into a single HF end point for these analyses.
Covariates:
We evaluated baseline age, sex, and race/ethnicity, as well as several clinical covariates. Baseline date was defined as 6 months after participants’ initial CNICS visit or date of HF surveillance by site (2002 for UW and 2010 for UAB), whichever was later. Participants with prevalent HF at their initial CNICS visit were excluded from the study. Baseline body mass index (BMI; kg/m2) was determined by the height and weight measurements closest to the baseline date for each participant. We defined diabetes using a previously validated approach as any one of the following: hemoglobin A1c ≥6.5%, a clinical diagnosis of diabetes and prescription of a diabetes-related medication, or prescription of a diabetes-specific medication.19 We defined treated hypertension as a clinical diagnosis of hypertension and prescription of an antihypertensive medication. Statin use was defined as prescription of an HMG-CoA reductase inhibitor. Ever-smoker and ever-methamphetamine use were defined by the presence of tobacco-use or methamphetamine-use diagnoses. The FIB-4 score, a noninvasive index developed to predict significant liver fibrosis in people with Hepatitis C and HIV coinfection, was used as a marker of liver disease.20 Estimated glomerular filtration rate (eGFR), calculated using the CKD-EPI 2021 equation21, was used as a marker of kidney function. Time-updated CD4 cell count, HIV VL, and history of MI were also assessed.
Statistical Analysis:
Baseline characteristics for PWH were reported as mean and standard deviation (SD) or as absolute values and percentages, as appropriate. Multivariable Cox survival analyses were used to determine associations of exposures and covariates with incident HF and incident non-ischemic HF. Analyses were performed in Stata18, and p<0.05 indicated statistical significance. Participants were followed until the first of a) HF event, b) death, c) loss to follow-up (defined as 9 months after last lab or CNICS visit), and d) end of HF adjudication by site (administrative censoring 2020 for UW and 2021 for UAB).
Results:
Out of 9,542 PWH followed beginning January 1, 2002 through December 31, 2021, records of 402 individuals were reviewed due to positive screens for possible HF based on administrative codes and/or B-type natriuretic peptide levels. Of these, 289 were determined to have physician-adjudicated HF, with the rest being determined as not HF. Reviewer concordance for adjudicated HF was high: of 289 HF events, 260 (90.0%) were agreed upon as HF by two independent, blinded reviewers, with the remaining 29 events determined to be HF by a third independent reviewer following discordance between the first two reviewers. Of the 113 positively screened events deemed not HF, the first two independent, blinded reviewers agreed that 98 (86.7%) were not HF; for the remaining 15, the third reviewer determined the event to be not HF following discordance between the first two reviewers. Concordance regarding HF etiology was likewise high; the two primary reviewers for each event determined presence/absence of ischemic and nonischemic etiologies separately, with mixed ischemic and nonischemic etiologies being possible if one or more reviewers noted both etiologies. The two primary reviewers for each event agreed on whether an ischemic etiology of HF was present in 262 out of 289 (90.7%) HF events; for nonischemic etiology presence versus absence, this concordance occurred in 232 out of 289 (80.3%) HF events.
Of the 289 individuals with adjudicated HF events, we excluded the 77 with HF at baseline; the remaining 212 individuals with adjudicated HF were considered as having incident HF. Demographic and clinical characteristics of PWH with adjudicated HF and PWH without adjudicated HF are shown in Table 1 (with supplemental Table 1 for each site, and supplemental table 2 by LVEF status). As expected, prevalence of cardiovascular risk factors such as smoking, hypertension, obesity, and diabetes was higher among those with versus without HF. The mean CD4 count was slightly lower and the mean VL slightly higher in the HF group compared to non-HF group. A higher proportion of PWH with HF also had a history of MI compared to the non-HF group. The mean year of baseline visit and mean years of follow-up were similar for HF and non-HF groups, and the mean year of HF diagnosis in the HF group was 2018. Use of ART by core class was shown by HF status and LVEF status, with slightly higher proportion of PWH with HF that are not on ART compared to those without HF, and a higher proportion of PWH with HF that are on PIs compared to those without HF (supplemental table 3).
Table 1:
Baseline demographic and clinical characteristics of PWH from 2 clinical sites by heart failure (HF) status. N (%) or mean (SD).
| Variable | No HF | HF | Overall |
|---|---|---|---|
| N | 9330 | 212 | 9542 |
| Age | 40 (11) | 47 (11) | 40 (11) |
| Female | 1710 (18%) | 51 (24%) | 1761 (18%) |
| Other | 345 (4%) | 5 (2%) | 350 (4%) |
| Ever smoking | 4590 (49%) | 116 (55%) | 4706 (49%) |
| Treated hypertension | 1680 (18%) | 100 (47%) | 1780 (19%) |
| Diabetes | 494 (5%) | 47 (22%) | 541 (6%) |
| Statin use | 907 (10%) | 53 (25%) | 960 (10%) |
| eGFR | 98 (21) | 86 (28) | 98 (22) |
| FIB-4 | 1.14 (1.18) | 1.55 (1.25) | 1.15 (1.18) |
| Missing | 1212 (13%) | 44 (21%) | 1256 (13%) |
| HIV viral load (log 2) | 7.2 (4.5) | 8.0 (4.9) | 7.3 (4.5) |
| CD4 count | 479 (293) | 433 (318) | 478 (294) |
| On Antiretroviral Therapy (ART) | 6853 (73%) | 144 (68%) | 6997 (73%) |
| During follow-up | 245 (3%) | 33 (16%) | 278 (3%) |
| Yes | 1289 (14%) | 26 (12%) | 1315 (14%) |
| Yes | 1303 (14%) | 44 (21%) | 1347 (14%) |
| Yes | 182 (2%) | 14 (7%) | 196 (2%) |
| Mean baseline year | 2011 (5) | 2010 (5) | 2011 (5) |
| Mean years of follow-up | 6.8 (4.9) | 6.3 (4.7) | 6.8 (4.9) |
| Year of HF diagnosis | NA | 2018 (5) | NA |
eGFR: estimated glomerular filtration rate; FIB-4: index for liver fibrosis
Among those with adjudicated HF, nonischemic etiologies were nearly five-fold more prevalent than ischemic etiologies: 115 out of 212 HF events (54%) were non-ischemic only, 24 (11%) were ischemic only, 36 (17%) were mixed, and 37 (17%) had no consensus (supplemental Table 2). Hypertension and substance use were the most common factors cited as contributing factors for nonischemic etiologies of HF (supplemental table 4).
Table 2 displays associations of demographic and clinical variables with incident adjudicated HF. A higher VL was associated with incident HF (hazard ratio (HR) 1.08 per VL doubling, 95% confidence interval (CI) 1.04–1.11). A higher CD4 T cell count was associated with lower hazard of incident HF (HR 0.94 per 100 cells/mm3, 95% CI 0.90–0.99). As predicted, history of MI was strongly associated with incident HF (HR 4.34, 95% of CI 3.0–6.2). Similarly, older age was associated with incident HF (HR 1.45 per 10 years, 95% CI 1.24–1.69). Smoking was not significantly associated with incident HF in this model (HR 1.17, 95% CI 0.88–1.56). Higher eGFR, indicative of better renal function, was associated with lower risk of incident HF (HR 0.74 per 30 ml/min increase, 95% CI 0.61–0.89). When investigating the different sites, the association of CD4 count, hypertension, and diabetes with incident HF is significant at the UAB site, whereas the association of kidney disease was significant at the UW site (supplemental Table 5). When separately considering risk factors associated with incident HF for those with reduced LVEF (including HFrEF and HFmrEF individuals, all with LVEF <50%) versus preserved LVEF (supplemental tables 6 and 7), associations of HIV viral load, lower CD4, hypertension, and diabetes were generally similar. The most notable differences were the association of a history of MI, which had a HR of 6.43 (95% CI 4.23–9.77) for HFrEF/HFmrEF and 1.83 (95% CI 0.87–3.83) for HFpEF; and the significant association of higher BMI with incident HFpEF but not HFrEF. To explore the possibility of collinearity between CD4 count and VL, a sensitivity analysis was performed to investigate the association of CD4 count and incident HF, excluding VL. Similar results were observed where higher CD4 T cell count was associated with lower risk of incident HF (HR per 100 cells/mm3 0.91, 95% CI 0.86–0.95).
Table 2.
Demographic and clinical characteristics associated with incident physician-adjudicated heart failure (n=212)
| Variable | HR | p-value | 95% CI | |
|---|---|---|---|---|
| Viral load (per doubling) | 1.08 | <0.001 | 1.04 | 1.11 |
| CD4 (per 100 cells/mm3) | 0.94 | 0.02 | 0.90 | 0.99 |
| History of myocardial infarction | 4.34 | <0.001 | 3.04 | 6.19 |
| Age (per 10) | 1.45 | <0.001 | 1.24 | 1.69 |
| Female | 1.00 | 1.0 | 0.71 | 1.40 |
| Other/missing | 1.01 | 1.0 | 0.41 | 2.53 |
| Ever smoking | 1.17 | 0.3 | 0.88 | 1.56 |
| Treated hypertension | 1.77 | 0.001 | 1.27 | 2.48 |
| Diabetes | 2.65 | <0.001 | 1.83 | 3.84 |
| Statin use | 1.17 | 0.4 | 0.82 | 1.68 |
| eGFR (per 30 ml/min/1.73m2) | 0.74 | 0.002 | 0.61 | 0.89 |
| Missing | 0.58 | 0.2 | 0.27 | 1.27 |
| Missing | 1.36 | 0.2 | 0.89 | 2.06 |
eGFR: estimated glomerular filtration rate; FIB-4: index for liver fibrosis
Cox proportional hazards model with time updated VL, CD4, and MI. Other variables at baseline.
An exploratory analysis showing the associations of demographic characteristics and clinical variables with incident non-ischemic HF (versus freedom from incident HF) was performed (Table 3). The associations were similar to overall incident HF, except history of MI was not associated with incident non-ischemic HF (HR 1.65, 95% CI 0.86–3.18).
Table 3.
Demographic and clinical characteristics associated with non-ischemic heart failure (n=115)
| Variable | HR | p-value | 95% CI | |
|---|---|---|---|---|
| Viral load (per doubling) | 1.08 | 0.001 | 1.03 | 1.12 |
| CD4 (per 100) | 0.93 | 0.03 | 0.86 | 0.99 |
| History of myocardial infarction | 1.65 | 0.1 | 0.86 | 3.18 |
| Age (per 10) | 1.24 | 0.04 | 1.01 | 1.52 |
| Female | 0.89 | 0.6 | 0.56 | 1.42 |
| Other/missing | 1.45 | 0.5 | 0.51 | 4.13 |
| Ever smoking | 1.14 | 0.5 | 0.77 | 1.68 |
| Treated hypertension | 2.28 | <0.001 | 1.46 | 3.57 |
| Diabetes | 2.39 | 0.002 | 1.39 | 4.10 |
| Statin use | 0.99 | 1.0 | 0.58 | 1.71 |
| eGFR (per 30 ml/min/1.73m2) | 0.63 | <0.001 | 0.50 | 0.80 |
| Missing | 0.39 | 0.1 | 0.09 | 1.63 |
| Missing | 1.21 | 0.7 | 0.62 | 1.98 |
eGFR: estimated glomerular filtration rate; FIB-4: index for liver fibrosis
Cox proportional hazards model with time updated VL, CD4, and MI. Other variables at baseline.
Discussion:
To our knowledge, this is the first multisite investigation of adjudicated HF events in PWH. In this study of PWH from two CNICS sites with adjudicated HF endpoints, we examined the incidence of HF and the clinical as well as HIV-related factors associated with incident HF. Our data add to the limited but growing literature on HF in PWH. Key strengths include the multisite nature of this study, rigorous CNICS data collection as well as systematic HF adjudication and assessment of contributing etiologies to HF (including ischemic and non-ischemic).7
The primary finding that is new in the present study is the observation, in a contemporary HIV care setting, that nonischemic etiologies of HF comprise a high proportion of HF events among PWH. Furthermore, the strong association of renal dysfunction with HF, and particularly nonischemic HF, warrants further study, which will be possible as adjudication of HF events continues for other CNICS sites. Similar to previous studies,6,7,22 we found that PWH who develop HF had a higher burden of CVD risk factors.23 As expected, we also observed an association between high HIV VL and low CD4 T cell count with incident HF. BMI was not associated with overall incident HF, but was associated with incident HFpEF in the subtype-specific sub-analysis. This warrants confirmation in future studies as adjudicated events from more CNICS sites become available. In addition, approximately one-fifth of individuals with nonischemic etiologies of HF also had moderate or worse valvular dysfunction; while this is not dissimilar from the general population,24 it warrants confirmation in future, larger studies, as well as ultimately investigation into whether functional valvular abnormalities (e.g., as a result of myocardial dysfunction) or primary valvular abnormalities predominate. Finally, we did not observe an association between statin use and incident HF (overall HF, non-ischemic HF, HFpEF, or HFrEF); changes in statin use over time could potentially impact outcomes in this population, which would be interesting to formally investigate in the future.
The demonstrated high burden of nonischemic etiologies of HF among PWH warrants further study. The pathophysiology of HF in PWH is heterogeneous and informed by limited data. Likely contributors include metabolic dysregulation, myocardial dysfunction from chronic inflammation and immune dysfunction, higher burden of traditional CVD risk factors, drug toxicity (such as methamphetamine, cocaine, and others), and other factors.25,26 It has been demonstrated that PWH with HF had higher risk of all-cause mortality and HF-associated readmissions compared to people without HIV.27 Therefore, it will be important to further understand the etiologies and risk factors of HF among PWH in order to inform prevention strategies and therapies.
While this study highlights the importance of disentangling sub-etiologies of HF to better understand pathophysiology and ultimately prevention and treatment, there are several limitations. We included 2 CNICS sites with systematically applied HF adjudication, however, the overall number of incident HF events (N=212) at these 2 sites were limited. Nevertheless, our primary findings were largely consistent with prior studies in different cohorts, with the main new contribution being a description of adjudicated HF etiologies. Given potential variability of HF etiology attribution, we used a systematic approach to event ascertainment and data standards previously used for HF adjudication requiring pre-specified clinical diagnoses and/or objective findings on imaging to make etiological determinations. Supporting the validity of our approach, our adjudicators, who were blinded to one another’s etiology determinations, had relatively high levels of agreement on the presence or absence of HF as well as presence or absence of ischemic etiology. Also, due to the limited number of events in this study (N=212), an analysis linking subtypes of ART with incident HF was not performed due to power considerations. As events from more CNICS sites are adjudicated, validation of our findings at multiple sites and expansion to formally investigate factors associated with specific etiologies of HF, including ART subtype, will become possible. Lastly, classification of smoking and cocaine use was defined by a tobacco use and cocaine use diagnosis respectively, which may lead to misclassification and systematic underclassification. In future studies with larger sample sizes able to restrict analyses only to subsets of participants that completed data on smoking status, this will be valuable to investigate further.
Conclusion:
Traditional CVD risk factors, high VL, low CD4 T cell count, as well as renal insufficiency were associated with incident adjudicated HF among PWH in care since 2010, and the majority of HF events were of non-ischemic etiology.
Supplementary Material
Clinical Perspective:
-
What is new?
This is the first multisite investigation of adjudicated heart failure events in people with HIV examining the clinical and HIV-related factors associated with incident HF. We observed that nonischemic etiologies of HF comprise the majority of HF events in people with HIV in the modern HIV treatment era.
-
What are the clinical implications:
Despite widespread antiretroviral therapy uptake, people with HIV have significantly higher risk of HF compared to people without HIV. Understanding the etiologies of HF in this population may inform prevention, diagnosis, and therapy.
Acknowledgments/Funding:
NIH: R01HL156792; R01HL126538; R24 AI067039; P30 AI027757; K23HL172699; K24 AI112393.
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