Heart Failure Risk in Systemic Lupus Erythematosus compared to Diabetes Mellitus and General Medicaid Patients

Abstract

Background:

Patients with systemic lupus erythematosus (SLE) have a similar risk of myocardial infarction as those with diabetes mellitus (DM). Whether the risk of heart failure (HF) in SLE is similar to the elevated risk in DM is unknown. We sought to estimate the rates and risks for HF hospitalization among US Medicaid patients with SLE and to compare them to those for DM and the general Medicaid population.

Methods:

Using U.S. Medicaid data from 2007–2010, we identified patients with SLE or DM, and a matched cohort from the general Medicaid population and calculated incidence rates (IR), incidence rate ratios (IRR) and adjusted hazard ratios (HR) of a first HF hospitalization.

Results:

We identified 37,902 SLE (93% female, mean age 40.1±12.1), 76,657 DM (93% female, mean age 40.0±12.1), and 158,695 general Medicaid patients (93% female, mean age 40.2±12.1). The IR per 1000-person years was 6.9 (95% CI 6.3–7.5) for SLE, 6.6 (95% CI 6.2–7.0) for DM, and 1.6 (95% CI 1.5–1.8) for general Medicaid patients. The highest IRR compared to general Medicaid was seen among SLE patients in age group 18–39 (14.7, 95% CI 13.9–15.5). Multivariable-adjusted HRs for HF compared to general Medicaid population were similar for SLE (2.7, 95% CI 2.3–3.1) and DM (3.0, 95% CI 2.6–3.4).

Conclusion:

The incidence of HF among SLE patients was 2.7-fold higher than general Medicaid patients, and similar to DM. Further investigation into the biologic mechanism of HF among SLE compared to non-SLE and DM patients may shed light on the findings of this study.

Introduction

Atherosclerotic cardiovascular disease (ASCVD) risk and mortality are increased among patients with systemic lupus erythematosus (SLE), compared to patients without SLE^1,2. Most studies demonstrating this increased risk have focused on myocardial infarction (MI) and stroke as the primary outcomes³. In contrast, few studies among SLE patients have examined the incidence and risk of heart failure (HF)^4,5, which is associated with high morbidity and mortality and is often the end-stage of cardiac disease⁶.

Along with ischemic heart disease, hypertension, and smoking, type 2 diabetes mellitus (DM) is a strong risk factor for HF⁷. Patients with DM have been shown to have up to five-fold higher risk of HF compared to those without DM⁸. Recent studies have revealed that rates of ASCVD are similar among patients with SLE and age- and sex-matched DM patients, and both groups have rates that are higher than the general population^9,10. How the risk of HF among SLE patients compares to that among patients with DM and to the general population is unknown.

The aim of this study was to investigate rates and risks of incident HF in patients with SLE compared to two groups: patients with DM and to individuals from the general Medicaid population. We hypothesized that the risk of HF in patients with SLE would be similar to that observed in patients with diabetes, and that both groups would have a substantially higher risk than that observed in the general Medicaid population.

Methods

Data source

We employed data from the Medicaid Analytic eXtract which includes billing claims, demographic information, and medication dispensing data for patients in Medicaid, the U.S. health insurance for low-income individuals. We identified adults of ages 18–65 years residing in the 29 most populated states in the U.S., who were enrolled in Medicaid between January 1, 2007 and December 31, 2010. We excluded patients >65 years old as > 90% are dually enrolled in Medicare and thus not all claims are captured in Medicaid.

Study design and cohort definition

Prevalent SLE was defined as having ≥ 3 International Classification of Diseases, Ninth Revision (ICD-9) codes specific for SLE (710.0) from hospital discharge diagnoses or physician visit claims, each ≥ 30 days apart, an approach used in prior studies^11,12. We required a six-month period of continuous enrollment for collection of baseline covariable data prior to the index date, defined as the date on which SLE criteria was met. In the event that the date of the third ICD-9 code for SLE occurred prior to the required six-month continuous enrollment, the next SLE-related claim that would allow for a 6-month baseline period thereafter was selected as the index date.

We identified prevalent type 1 or type 2 DM patients as those having ≥ 3 ICD-9 codes for DM (249.XX, 250.XX, 357.2, 362.0×, 366.41) from hospital discharge diagnoses or physician visit claims each separated by ≥ 30 days, without any claims for SLE^13,14. We required 6 months of continuous enrollment prior to the index date as the baseline period. The index date was the date of the third ICD-9 code, or in the event that the third ICD-9 code date occurred before the 6-month baseline period could be established, the next DM-related claim thereafter that would allow for a 6-month baseline period was selected as the index date. Patients who met criteria for both SLE and DM cohorts were not included in either cohorts.

We identified non-SLE and non-DM general Medicaid patients who had ICD-9 codes for any non-SLE, non-DM diagnoses from hospital discharge diagnoses or physician visit claims on the same index date as each SLE patient. We again required a 6-month baseline period of continuous enrollment prior to the index date, and patients with any SLE or DM ICD-9 codes during the baseline period were excluded from the general Medicaid cohort. We used a SAS greedy matching algorithm to identify the first closest match for each SLE patient by sex and age at index date (within 1 month) to two DM and four general Medicaid population patients¹⁵. For all three matched cohorts, we subsequently excluded patients with any diagnosis codes for HF (ICD-9 codes 402.01, 402.11, 402.91, 404.01, 404.11, 404.91, 404.03, 404.13, 404.93, and 428.xx, excluding 398.91) during the 6-month baseline period¹⁶.

Assessment of covariables

Patient characteristics for all cohorts were collected during the baseline period: age, sex, self-reported race/ethnicity, U.S. region of residence, and zip code-level median household income in quartiles from 2007–2010 U.S. Census data¹⁷. In the SLE cohort, lupus nephritis patients were defined as having ≥ 2 ICD-9 hospital discharge diagnoses or physician billing claims for nephritis, proteinuria, and/or renal failure, occurring ≥ 30 days apart, on or after the SLE criteria were met^11,18. Among the DM patients, diabetic nephropathy patients were defined as having ≥ 2 ICD-9 hospital discharge or physician billing codes for nephritis, proteinuria, and/or renal failure ≥ 30 days apart on or after DM criteria was met¹⁹.

Using ICD-9, Diagnosis Related Group code and/or Current Procedural Terminology codes, we collected covariables in the baseline period, including the number of outpatient physician visits, smoking, obesity, hypertension, diabetes, hyperlipidemia, chronic kidney disease (CKD), thyroid disease (hypo- or hyperthyroidism), and valvular disease^{13,14,19–25}. ASCVD at baseline was defined as the presence of any of the following diagnosis codes during the baseline period: acute MI, old MI, angina, percutaneous coronary intervention, coronary artery bypass graft, coronary atherosclerosis, cerebrovascular accident, peripheral vascular disease, and carotid artery stenosis^24,26–30.

We calculated a Charlson comorbidity index for all patients³¹. We identified filled prescriptions using National Drug Codes and summed the number of unique medications filled per subject during the baseline period. We assessed baseline prescriptions filled for anticoagulants, beta-blockers, statins, and angiotensin converting enzyme inhibitor/angiotensin receptor blockers. We assessed glucocorticoid use of ≥ 10 mg/day of prednisone ever during the baseline period (prednisone, methylprednisolone, dexamethasone, hydrocortisone, prednisolone, and cortisone, defined as prednisone equivalents) during the baseline period.

Outcomes

The primary outcome was first HF hospitalization defined by ICD-9 codes (402.01, 402.11, 402.91, 404.01, 404.11, 404.91, 404.03, 404.13, 404.93, and 428.xx, excluding 398.91) for HF submitted as either primary or secondary hospital discharge diagnosis codes during the observation period¹⁶. Patients were followed from index date until first HF hospitalization, death, disenrollment or end of follow-up.

Statistical analysis

We calculated unadjusted first HF incidence rates (IRs) per 1,000 person-years with 95% confidence intervals (CI) using Poisson regression for all cohorts overall and stratified by covariates. We also calculated first HF incidence rate ratios (IRRs) with 95% CI for SLE and DM with general Medicaid as the reference, overall and stratified by covariates. For SLE, we calculated the HF IR after stratifying patients by hydroxychloroquine use versus non-use. We fit multivariable Cox sub-distribution proportional hazards models, calculating cause-specific risk while accounting for the competing risk of death, for incident HF hospitalization among SLE, DM and the general Medicaid cohort using the Fine and Gray model³². As our cohorts were no longer age- and sex-matched after excluding patients with baseline HF, our models were adjusted for age and sex. In our first model, we adjusted for age, sex, and race/ethnicity. We then examined the addition of other covariable in separate models, including region of residence, zip code level median household income, hypertension, obesity, hyperlipidemia, thyroid disease, valvular disease, peri/myocarditis, renal disease (lupus nephritis/diabetic nephropathy/CKD), Charlson comorbidity index, and ASCVD. We included the covariates that were found to be confounders, with significant change of greater than 10% in the effect estimates in the partial models. Our final Cox regression model included age, sex, race/ethnicity, hypertension, lupus nephritis/diabetic nephropathy/CKD, Charlson comorbidity index, and ASCVD.

Data were obtained from Centers for Medicare and Medicaid Services through approved Data Use Agreements and presented in accordance with CMS policies (cell sizes <11 were suppressed). We performed all analyses using SAS version 9.4. The Partners’ Institutional Review Board approved this study.

Results

We identified 40,212 SLE patients, who were matched by age at index date and sex to 80,424 DM patients, and 160,848 general Medicaid patients (Table 1). After excluding patients with baseline history of hospitalization for HF (5.7% for SLE, 4.6% for DM, and 1.3% for general Medicaid), our cohorts consisted of 37,902 SLE patients (93% female, mean age 40.1±12.1), 76,657 DM patients (93% female, mean age 40.0±12.1), and 158,695 general Medicaid patients (93% female, mean age 40.2±12.1). There was a higher proportion of Black patients within the SLE cohort compared to the DM and general Medicaid cohorts, while the general Medicaid cohort had the highest proportion of Hispanic patients. Renal disease due to lupus nephritis was present in 16% of SLE patients and 4% of the DM cohort had diabetic nephropathy. Hypertension, hyperlipidemia, and obesity were more common among patients with DM, while the presence of baseline ASCVD was higher among SLE patients compared to DM (10% vs 8%).

Table 1.

Baseline Characteristics of SLE, DM and General Medicaid cohorts, 2007–2010

	SLE	DM	General Medicaid
Matched cohort size, after exclusion of baseline heart failure (N)	37,902	76,657	158,695
Female (%)	93	93	93
Mean age in years (age, SD)	40.1 (12.1)	40.0 (12.1)	40.2 (12.1)
Race/Ethnicity
White (%)	35	46	46
Black (%)	41	30	21
Hispanic (%)	16	18	26
Asian (%)	3	3	3
American Indian/Alaskan Native (%)	1	1	1
U.S. Region of Residence
West (%)	20	19	29
Northeast (%)	22	20	19%
South (%)	38	39	33%
Midwest (%)	20	22	19%
Lupus nephritis/Diabetic nephropathy/CKD (%)	16	4	1%
Hypertension (%)	31	37	11
Hyperlipidemia (%)	9	22	6
Obesity (%)	4	11	2
Smoking (%)	6	5	4
Valvular disease (%)	5	2	1
Presence of ASCVD* (%)	10	8	3
Thyroid disease (%)	7	7	3
Pericarditis/Myocarditis (%)	1	<1	<1
Mean total number of medications (#, SD)	9.7 (9.1)	10.0 (9.1)	3.4 (5.3)
Beta-blocker use (%)	10	10	4
ACE inhibitor/ARB use (%)	18	31	5
Glucocorticoid use (%)	41	9	4
Hydroxychloroquine use (%)	37	0.3	0.2
Charlson Comorbidity Index (mean, SD)	1.7 (1.2)	1.6 (1.2)	0.4 (1.2)

^*ASCVD: Baseline presence of any atherosclerotic cardiovascular disease by ICD-9 codes for angina, myocardial infarction, old myocardial infraction, percutaneous coronary intervention, coronary artery bypass graft, atherosclerosis, cerebrovascular accident, peripheral vascular disease, carotid stenosis

Abbreviations: ACE inhibitor/ARB, angiotensin converting enzyme inhibitor/angiotensin receptor blocker; ASCVD, atherosclerotic cardiovascular disease; CKD, chronic kidney disease; DM, diabetes mellitus; SLE, systemic lupus erythematosus

During a mean follow-up time of 1.9±1.1 years for SLE, 1.8±1.1 years for DM, and 1.6±1.2 for general Medicaid cohort, there were 479 HF hospitalization events for SLE, 921 for DM and 397 for general Medicaid. There were 1,393 (3.7%) deaths for SLE, 1,949 (2.5%) deaths for DM, and 2,947 (1.9%) deaths for the general Medicaid cohort. The IR of HF per 1,000-person years was 6.9 (95% CI 6.3–7.5) among SLE, 6.6 (95% CI 6.2–7.0) among DM and 1.6 (95% CI 1.5–1.8) within general Medicaid (Table 2). The IR among SLE patients in the 18–39 age group was elevated at 6.1 (95% CI 5.3–7.0), compared to 6.2 (95% CI 5.2–7.4) in the 40–49 age group, and 8.7 (95% CI 7.4–10.2) in the 50–65 age group. Among DM patients, the IR increased more dramatically with age compared to the SLE patients, with IR of 2.8 (95% CI 2.4–3.2) in the 18–39 age group, 7.3 (95% CI 6.5–8.2) in the 40–49 age group, and 13.1 (95% CI 12.0–14.4) in the 50–65 age group. The IR of HF among the general Medicaid group remained lower than the IRs of the SLE and DM cohorts in all age groups.

Table 2.

Incidence Rates of First Hospitalizations for Heart Failure among SLE, DM and General Population Patients in Medicaid, stratified by baseline covariables

	Events	Number of Patients	Person-Years	Incidence Rate (95% CI)
All patients
SLE	479	37,902	70,979	6.8 (6.2–7.4)
DM	921	76,657	142,993	6.4 (6.0–6.9)
General Medicaid	397	158,695	275,498	1.4 (1.3–1.6)
Age 18–39
SLE	212	18,846	34,836	6.1 (5.3–7.0)
DM	196	38,632	71,133	2.8 (2.4–3.2)
General Medicaid	54	78,614	131,291	0.4 (0.3–0.5)
Age 40–49
SLE	116	9,906	18,700	6.2 (5.2–7.4)
DM	274	19,903	37,449	7.3 (6.5–8.2)
General Medicaid	96	41,633	73,875	1.3 (1.1–1.6)
Age 50–65
SLE	151	9,150	17,444	8.7 (7.4–10.2)
DM	451	18,122	34,411	13.1 (12.0–14.4)
General Medicaid	247	38,448	70,332	3.5 (3.1–4.0)
Sex Female
SLE	431	35,118	65,897	6.5 (6.0–7.2)
DM	839	70,952	132,536	6.3 (5.9–6.8)
General Medicaid	350	146,839	255,078	1.4 (1.2–1.5)
Sex Male
SLE	48	2,784	5,082	9.5 (7.1–12.5)
DM	82	5,705	10,458	7.8 (6.3–9.7)
General Medicaid	47	11,856	20,419	2.3 (1.7–3.1)
Race/Ethnicity White
SLE	94	13,422	24,393	3.9 (3.2–4.7)
DM	363	35,099	66,209	5.5 (4.9–6.1)
General Medicaid	176	73,389	130,436	1.4 (1.2–1.6)
Race/Ethnicity Black
SLE	295	15,608	29,955	10.0 (8.8–11.0)
DM	381	22,630	42,916	8.9 (8.0–9.8)
General Medicaid	169	33,160	61,763	2.7 (2.4–3.2)
Race/Ethnicity Hispanic
SLE	59	6,245	11,561	5.1 (4.0–6.6)
DM	126	13,439	23,812	5.3 (4.4–6.3)
General Medicaid	30	40,516	64,985	0.5 (0.3–0.7)
Race Ethnicity Asian
SLE	-	-	-	4.4 (2.4–8.1)
DM	20	2,201	4,049	4.9 (3.2–7.7)
General Medicaid	-	-	-	0.5 (0.2–1.3)
Race/Ethnicity American Indian/Alaskan Native
SLE	-	-	-	7.0 (2.9–16.8)
DM	13	1,096	2,023	6.4 (3.7–11.1)
General Medicaid	-	-	-	1.4 (0.5–3.7)
Without renal disease
SLE	240	31,992	57,854	4.2 (3.7–4.7)
DM	611	73,217	135,012	4.5 (4.2–4.9)
General Medicaid	366	157,367	273,455	1.3 (1.2–1.5)
With renal disease
SLE	239	5,910	13,124	18.2 (16.1–20.7)
DM	310	3,440	7,981	38.8 (34.8–43.4)
General Medicaid	31	1,328	2,043	15.2 (10.7–21.6)
Without valvular disease
SLE	414	35,937	67,378	6.1 (5.6–6.8)
DM	862	75,148	140,242	6.2 (5.8–6.6)
General Medicaid	371	157,046	272,760	1.4 (1.2–1.5)
With valvular disease
SLE	65	1,965	3,601	18.1 (14.2–23.0)
DM	59	1,509	2,751	21.5 (16.6–27.7)
General Medicaid	26	1,649	2,738	9.5 (6.5–14.0)
Without ASCVD*
SLE	387	34,296	64,364	6.0 (5.4–6.6)
DM	663	70,552	131,638	5.0 (4.7–5.4)
General Medicaid	327	153,620	266,926	1.2 (1.1–1.4)
With ASCVD*
SLE	92	3,606	6,614	13.9 (11.3–17.1)
DM	258	6,105	11,355	22.7 (20.1–25.7)
General Medicaid	70	5,075	8,572	8.2 (6.5–10.3)

^*ASCVD: Baseline presence of any atherosclerotic cardiovascular disease by ICD-9 codes for angina, myocardial infarction, old myocardial infraction, percutaneous coronary intervention, coronary artery bypass graft, atherosclerosis, cerebrovascular accident, peripheral vascular disease, carotid stenosis

Abbreviations: ASCVD, atherosclerotic cardiovascular disease; DM, diabetes mellitus; SLE, systemic lupus erythematosus

^-Cell sizes under 11 are suppressed according to Federal Reporting Requirements.

Unadjusted IRR of HF for SLE and DM compared to general Medicaid were similar at 4.65 (95% CI 4.31–4.50) and 4.44 (95% CI 4.31–4.57), respectively (Figure 1). However, in the 18–39 age group, the IRR of HF was 14.70 (95% CI 13.92–15.53) for SLE compared to 6.68 (95% CI 6.32–7.06) for DM, while in the higher age groups, the IRR were slightly higher for DM. The IR of HF were higher in patients with valvular disease for all cohorts (Table 2), but the IRR of SLE and DM compared to general Medicaid were higher in patients without valvular disease compared to those with valvular disease (Figure 1). A similar trend was noted in stratified analysis of patients with and without ASCVD. Among SLE patients, we stratified patients by baseline hydroxychloroquine use and found IR per 1,000 person-years of 6.88 (95% CI 6.14–7.71) for the 23,718 patients without baseline hydroxychloroquine use and 6.54 (95% CI 5.65–7.57) for the 14,184 patients with baseline use of hydroxychloroquine.

Figure 1. Incidence rate ratios (95% CI) of first hospitalization for heart failure for SLE and DM cohorts with general Medicaid as reference, overall and stratified by covariates.

*ASCVD: Baseline presence of any atherosclerotic cardiovascular disease by ICD-9 codes for angina, myocardial infarction, old myocardial infraction, percutaneous coronary intervention, coronary artery bypass graft, atherosclerosis, cerebrovascular accident, peripheral vascular disease, carotid stenosis

Abbreviation: ASCVD, atherosclerotic cardiovascular disease; DM, diabetes mellitus; SLE, systemic lupus erythematosus

In multivariable Cox regression models adjusted for age, sex, and race/ethnicity, the risk of incident HF was greater than four-fold in the SLE [subdistribution hazard ratio (HR_SD) 4.2, 95% CI 3.6–4.7] and DM (HR_SD 4.4, 95% CI 3.9–4.9) cohorts, with overlapping 95% CIs, compared to the age- and sex-matched general Medicaid patients as reference group (Table 3). When assessed individually in these models, baseline hypertension, renal disease (lupus nephritis/diabetic nephropathy/CKD), Charlson comorbidity index, and ASCVD variables were important confounders or mediators of the relationships between SLE and DM and risk of HF, significantly influencing comparative HRs for incident HF. In our final model, which additionally adjusted for baseline hypertension, renal disease, Charlson comorbidity index and ASCVD, the risk of HF hospitalization remained elevated in both disease groups: HR_SD 2.7 (95% CI 2.3–3.1) for SLE and 3.0 (95% CI 2.6–3.4) for DM compared to general Medicaid patients.

Table 3.

Multivariable Hazard Ratios for Hospitalizations for Heart Failure among SLE, DM and General Medicaid Population, 2007–2010

Cohort	HRSD (95% CI) Model 1	HRSD (95% CI) Model 2
General Medicaid	1.0 (ref)	1.0 (ref)
SLE	4.2 (3.6–4.7)	2.7 (2.3–3.1)
Diabetes Mellitus	4.4 (3.9–4.9)	3.0 (2.6–3.4)

HR_SD: Hazard ratio for first HF hospitalization event, competing risk analysis taking risk of death into account

Model 1: Adjusted for age, sex, and race/ethnicity

Model 2: Model 1 and additionally adjusted for hypertension, lupus nephritis/diabetic nephropathy/chronic kidney disease, Charlson comorbidity index and atherosclerotic cardiovascular disease

Abbreviations: DM, diabetes mellitus; SLE, systemic lupus erythematosus

Discussion

In this prospective cohort study of nearly 38,000 U.S. Medicaid patients with SLE, we found that the incidence rate of HF hospitalization was more than 4 times higher than among age- and sex-matched general Medicaid patients. Furthermore, SLE patients had a similar risk of HF hospitalization as patients with DM, a disease population with recognized elevated HF risk⁸. While the overall rate of HF was similar in patients with SLE and DM, the relative increase in HF risk for patients with SLE appeared to be concentrated among patients aged 18–39. In contrast, the relative increase in HF incidence among those with diabetes was evident first for patients in their 40s, and then continued among those aged 50–65. Finally, the increased risk of HF among patients with SLE persisted after adjustment for a number of important potential confounders, such as the Charlson comorbidity index and ASCVD.

Unlike in DM, a disease condition generally well recognized as associated with elevated risk of HF^8,33,34, the increased risk of incident HF among SLE patients has not been well studied or recognized. HF has been reported previously to have increased prevalence among SLE patients with ASCVD events^2,35–37. Female SLE patients had a 3.8-fold increased likelihood of being hospitalized for HF in a study of California hospital discharges from 1991–1994⁴. A more recent analysis by Kim et al. of SLE patients and controls from 26 commercial U.S. healthcare systems from 1999 to 2016 also revealed that SLE increased the odds of HF by 3.2 fold compared to non-SLE controls⁵.

The higher relative IR of HF among young SLE patients compared to age-and sex-matched DM and non-SLE patients is consistent with previous findings. In the California study, SLE patients in the 18–44 year age group were 3.8-fold more likely than those without SLE to be hospitalized for HF, compared to 1.39-fold higher for those in the age group 45–64 and 1.25-fold higher for those aged ≥65 years old⁴. Similarly, in the study by Kim et al., the relative risk of HF was extremely high [49.5 (95% CI 37.3–65.5)] in the youngest age group of 20–24 and the relative gap decreased with increasing age⁵. These findings are consistent with the current study, in which young SLE patients in the 18–39 age group had over twice the IR of HF than did DM patients of the same age, demonstrating the excess risk among young patients with SLE. These data suggest that patients with SLE are at risk for a condition associated with significant morbidity and mortality at a much younger age than patients from the general population or with DM. By contrast, compared to general Medicaid patients, the IRR of HF for those with DM in the age group 50–65 was higher (HR 3.69, 95% CI 3.51–3.88) than those with SLE in that same age group (HR 2.45, 95% CI 2.29–2.62). The lower risk of HF among older SLE patients may be due to the fact that patients with SLE tend to develop HF at a younger age, and are then excluded from our analysis of older age groups because they have already developed prevalent HF.

In previous studies, IRs of HF in the general population have been demonstrated to be highest among Black patients compared to those of other races^38,39. In the current study, the IR for incident HF was indeed highest among Black patients in all three cohorts, including the SLE cohort. As there was substantial variation in the racial make-up of our three cohorts, we adjusted our initial multivariable model for race/ethnicity among other demographic factors and SLE patients were still found to have a 4.2-fold increased risk of incident HF hospitalization compared to the general Medicaid patients, and a similar risk compared to the DM patients.

Known risk factors for HF include hypertension, ischemic heart disease, valvular heart disease, smoking, and obesity, and less common risk factors include myocarditis, which is rare, but is more prevalent among patients with SLE^7,33,40–42. However, even after adjusting for covariates that were found to significantly lower the effect estimates for the risk of HF, the HR for incident HF for SLE remained elevated at 2.7, suggesting that these risk factors do not fully explain the increased HF risk in SLE. Renal impairment is also associated with risk of HF⁴³, and was included as a confounder in our final model, which continued to reveal elevated HRs of HF for both SLE and DM.

In the general population, markers of inflammation including tumor necrosis factor-alpha, interleukin-6, and C-reactive protein, are associated with HF, suggesting inflammation may itself contribute to HF pathogenesis^44,45. In DM, poor glycemic control has been associated with microvascular disease and increased HF risk⁴⁶. Cardiac microvascular dysfunction likely plays a role in HF development, and in a prospective population-based study of patients who have had retinal photographs, retinopathy, revealing microvascular disease, has been a predictor of HF⁴⁷. The etiology of HF in SLE is likely to include myocardial microvascular dysfunction resulting from chronic inflammation, as well as a combination of premature epicardial coronary disease and valvular heart disease⁴⁸. Furthermore, while hydroxychloroquine use can lead to cardiomyopathy, we did not see a difference in IR of HF in SLE patients stratified by baseline hydroxychloroquine use⁴⁹. Further research to clarify the pathobiological processes driving HF risk in SLE, and to identify strategies for HF prevention in this vulnerable population, are needed.

The strengths of our study include the large nationwide population of patients studied with SLE with age- and sex-matched comparison groups of DM and the general Medicaid populations. Our analysis included important covariables including race/ethnicity, previously associated with HF. However, although we included many baseline characteristics that are important factors of HF risk, use of administrative claims data may fail to adequately capture several important covariables such as obesity, smoking, and hyperlipidemia. We were also unable to include the presence of antiphospholipid syndrome, which may be particularly important among patients with SLE, although not so among diabetes or in the general population⁴¹.

We excluded patients who met criteria for both SLE and DM cohorts. However, our cohort inclusion criteria required ≥3 ICD-9 codes for DM at least 30 days apart, and a small proportion (0.4%) of our SLE patients had used insulin during the baseline period and may have had DM. Other limitations of our study include lack of information regarding disease duration for SLE and DM cohorts and disease activity among SLE patients, as well as inability to accurately assess severity, type (preserved or reduced ejection fraction), and stage of HF diagnosis in claims databases. Additionally, the findings of our study in the Medicaid database may not be generalizable to patients with commercial insurance with variations in access to care.

Conclusions

In this large U.S. Medicaid cohort study, we found that the adjusted risk for incident HF hospitalization among patients with SLE was almost 3-fold higher than general Medicaid patients, and was very similar to that seen among patients with DM. In line with previous reports of elevated rates of MI and stroke in SLE patients, this study demonstrates that patients with SLE are at particularly high risk for HF, similar to patients with DM, and that this risk is concentrated among young patients. Further studies to investigate the underlying mechanisms of HF in SLE, and strategies to target HF prevention in SLE patients are needed.