Killian, Jill M.

Introduction: Guideline-directed medical therapy (GDMT) dramatically improves outcomes in heart failure with reduced ejection fraction (HFrEF). Our goal was to examine GDMT use in community patients with newly diagnosed HFrEF. Methods: We performed a population-based, retrospective cohort study of all Olmsted County, Minnesota residents with newly diagnosed HFrEF (EF≤40%) 2007-2017. We excluded patients with contraindications to medication initiation (allergy, intolerance, heart rate<50 for beta blockers, SBP <80mm Hg for beta blockers, ACEi/ARB/ARNI; high creatinine (>3 mg/dL ACEi/ARB/ARNI, >2.5 men or >2.0 mg/dL women for mineralocorticoid receptor antagonists, MRAs) or hyperkalemia (potassium >5 meQ/L for ACEi/ARB/ARNI, MRA). We examined use and peak dose achieved for beta blockers, HF beta blockers (metoprolol succinate, carvedilol, bisoprolol), ACEi/ARB/ARNI, and MRA in the first year after HFrEF diagnosis. We used logistic regression to evaluate predictors of GDMT use. Results: From 2007-2017, 1160 patients were diagnosed with HFrEF (mean age 69.7 years, 65.6% men). Most eligible patients received beta blockers (92.1%) and ACEi/ARB/ARNI (86.5%) in the first year after HFrEF. However, only 63.6% of patients were treated with a HF beta blocker, and most did not receive MRAs (82.6%). The percentage of treated patients reaching medication target doses was 20.5% for HF beta blockers, 25.3% for ACEi/ARB/ARNI, and 11.2% for MRA. Compared to patients not seen in an HF clinic, patients seen in an HF clinic (n=380, 32.8%) were at greater odds of receiving beta blockers (OR 3.85, 95% CI 1.79-8.33); HF beta blockers (OR 3.85, 95% CI 2.63-5.26); ACEi/ARB/ARNIs (OR 3.85, 95% CI 2.17-6.67); and MRAs (OR 3.03, 95% CI 2.08-4.35). Other independent predictors of GDMT use included younger age (beta blockers, ACEi/ARB/ARNI), male gender (MRAs), higher SBP (beta blockers, ACEi/ARB/ARNI), lower EF (HF beta blockers), higher BMI (MRAs), and diabetes (ACEi/ARB/ARNI, p<0.05 for each). Conclusions: In this population-based study, most patients with newly diagnosed HFrEF received beta blockers and ACEi/ARB/ARNIs, but goal doses were usually not achieved. GDMT use was much higher in patients referred to an HF clinic.

Background: Many patients with atherosclerotic cardiovascular disease (ASCVD) or diabetes mellitus (DM) do not receive guideline-recommended lipid lowering therapy (LLT). We characterized LLT treatment patterns and identified predictors of high intensity statin prescriptions (Rx) in patients with ASCVD and DM. Methods: Olmsted County, MN residents with DM or ASCVD (MI, unstable angina, revascularization, ischemic stroke/TIA) from 2005-2012 were followed for 2 years capturing all LDL-C and LLT Rx. Cox regression examined predictors of high intensity statin Rx, modeling LDL-C as a time-dependent variable. Results: 8408 patients with DM (n=4881) or ASCVD (n=3527) were identified (mean age 63.1, 55.1% male). Over 2 years, mean (SD) number of LDL-C measurements was 2.7 (1.9); 12.1% had none. Among those with ≥1 LDL-C, the first was ≥100 mg/dL in 46.2%. LLT Rx increased within 30 days after the first LDL-C. (Table). However, among those with LDL-C ≥100, 40.1% were not prescribed LLT; these patients were younger (mean age 56.9 vs 60.8), more likely female (52.7% vs 45.6%) and more likely to have DM vs ASCVD (84.5% vs 54.6%) than those prescribed LLT. High intensity statin Rx increased more for those with LDL-C ≥100 than those with LDL-C <100. Men [HR 1.29 (CI 1.13-1.48)] and patients with ASCVD vs DM [6.12 (5.25-7.12)] were more likely to be prescribed high intensity statins. Higher LDL-C was associated with greater high intensity statin Rx, although associations differed between ASCVD and DM (p-interaction=0.004). Compared to DM, ASCVD patients were more likely prescribed high intensity statins at every level of LDL-C [2.73 (1.70-4.37), 6.47 (4.94-8.47), 5.68 (4.45-7.25), and 7.88 (5.89-10.53) for LDL-C <70, 70-99, 100-130, and ≥130]. Conclusions: Although high intensity statin Rx increased in response to increasing LDL-C, a large proportion of patients do not receive guideline-concordant care. Efforts should be made to encourage more aggressive treatment of elevated LDL-C and to understand why treatment is neglected or delayed.

Background The epidemiology of ventricular arrhythmias (VAs) in patients with advanced heart failure (HF) is not well defined. Methods and Results Residents of Olmsted County, Minnesota, with advanced HF from 2007 to 2017 were identified using the 2018 European Society of Cardiology criteria. Billing codes were used to capture VAs; severe VAs requiring emergency care were defined as events associated with emergency department visits or hospitalizations. The cumulative incidence of VAs postadvanced HF was estimated with the Kaplan–Meier method. Multivariable Cox analyses were used to determine the following: (1) Predictors of severe VAs postadvanced HF; and (2) Impact of severe VAs on mortality. Of 936 patients with advanced HF, 261 (27.9%) had a history of VA. The 1‐year cumulative incidence of severe VAs postadvanced HF was 5.4%. Prior VAs (hazard ratio [HR] 2.22 [95% CI, 1.26–3.89], P =0.006) and left ventricular ejection fraction <40% (HR, 3.79 [95% CI, 1.72–8.39], P <0.001) were independently associated with increased severe VA risk postadvanced HF. New‐onset severe VAs were associated with increased mortality (HR, 4.41 [95% CI, 2.80–6.94]; P <0.001), whereas severe VAs in patients with prior VAs had no significant association with mortality risk (HR, 1.08 [95% CI, 0.65–1.78]; P =0.77). Severe VAs were associated with increased mortality in patients without implantable cardioverter defibrillators (HR, 4.89 [95% CI, 2.89–8.26]; P <0.001), but not in patients with implantable cardioverter defibrillators (HR, 1.42 [95% CI, 0.92–2.19]; P =0.11). Conclusions Patients with left ventricular ejection fraction <40% and prior VAs have increased risk of severe VA postadvanced HF. New‐onset severe VAs or severe VAs without implantable cardioverter defibrillators postadvanced HF are associated with increased mortality.

Background: Patients are surviving longer after myocardial infarction (MI), but little is known about the occurrence and predictors of subsequent hospitalizations. Methods: We identified all Olmsted Count residents with incident MI from 1987-2008 and evaluated Olmsted County hospitalizations through 2009. ICD-9 codes were used to determine the primary reason for hospitalization. To account for repeated events, Andersen-Gill models were used to examine the predictors of hospitalization post-MI. Patients were censored at death or last follow-up. Results: A total of 2617 patients (mean 67 years, 41% female, 32% with ST-elevation MI) were diagnosed with incident MI from 1987-2007 and survived MI hospitalization. Over a mean follow-up of 7.1 years, 10116 hospitalizations occurred equating to a median of 3 (range 0 to 43) per person. Only 37.5% (n=3793) of hospitalizations were due to cardiovascular causes, and of these, most were due to ischemic heart disease (n= 1865, 49.2%) and heart failure (n= 733, 19.3%). The proportion of non-cardiovascular hospitalizations increased over time and was higher in women than men, but did not differ by ST-segment status. Several factors were associated with the risk of hospitalization after adjusting for year of diagnosis and sex (Figure). Biomarker levels were not predictors of hospitalization risk. Conclusions: Two-thirds of hospitalizations among incident MI survivors in the community are for non-cardiovascular reasons, and this proportion has increased. Comorbidities are important predictors of recurrent hospitalizations. Therapies focused solely on MI management may be insufficient to prevent the majority of future admissions.

Background: Participation in cardiac rehabilitation (CR) has been shown to decrease mortality following acute myocardial infarction (MI), but its impact on rehospitalizations requires examination. Methods: We included patients who were hospitalized with first-ever MI in Olmsted County Minnesota from 1987-2010 and survived to hospital discharge. Participation in CR within the first 30 days following MI was determined using billing data and was analyzed as a time-dependent covariate. The association between CR participation and all-cause rehospitalization was analyzed using Andersen-Gill models to account for repeated events. As CR participation is a non-randomized intervention, we adjusted for propensity to participate after fitting a logistic regression model using 13 factors significantly associated with participation on univariate analysis. Patients were censored at the time of death or last follow-up. Results: Among 2991 patients (mean age 67 years, 59% male, 31% ST elevation MI), 1480 (49%) participated in CR following acute MI hospital discharge (first session occurred at a mean of 9 days post-discharge). Most patients (75%) were rehospitalized at least once during a mean follow-up of 7.6 years, and CR participation was associated with reduced risk of rehospitalization. The rehospitalization rates were 39% and 59% at one year for participants and non-participants, respectively. In unadjusted analysis, CR participation was associated with a markedly decreased risk of rehospitalization (HR 0.51, 95% CI 0.49-0.53, p<0.001). After adjusting for propensity to participate, the association between CR participation and all-cause rehospitalization persisted (HR 0.70, 95% CI 0.67-0.73, p<0.001). Conclusions: CR participation is associated with a markedly reduced risk of rehospitalization after incident MI. In addition to reducing mortality, improving CR participation rates may have a large impact post-MI healthcare resource use.

Background: Acute aortic syndrome (AAS) includes aortic dissection (AD), intramural hematoma (IMH) and penetrating aortic ulcer (PAU) and confers high rates of aortic related events. However, the risk of cardiovascular (CV) events in this patient group is unknown. The aim of this study was to define the rates of CV events in an incident cohort of AAS patients. Methods: Medical records and death certificates of all Olmsted County, MN residents with a diagnosis of AAS from 1995-2015 were reviewed and compared to age- and sex- matched population controls. Primary outcome was non-aortic CV mortality. Secondary outcome was overall mortality and first time non-fatal CV event (myocardial infarction (MI), heart failure (HF) or stroke). Events were analyzed using Cox proportional hazards regression adjusting for comorbidities. Results: Of 133 patients with AAS (77 AD, 21 IMH, 35 PAU) 57% were male, median age was 72 (SD 14) and median follow-up was 10 years. Overall survival in AAS cases and controls was 62% versus 83% at 5 years and 44% versus 60% at 10 years (adj HR 1.8, p<.001, 95% CI 1.3-2.4). CV death occurred in 21 (29%) of 73 AAS decedents due to HF (9), MI (5), other cardiac causes (5), stroke (1) and peripheral vascular disease (1). CV-related survival at 5 and 10 years after AAS diagnosis (91% and 81%) was not significantly different from controls (95% and 86%) after adjustment for comorbidities (adj HR 1.8, p=.1, 95% CI 0.9-3.6). AAS was associated with an increased risk of any first time CV event (adj HR 2.6, p<.001, 95% CI 1.6-4.4; Figure), first time diagnosis of MI (adj HR 2.8, p<.001, 95% CI 1.7-4.7) and HF (adj HR 3.2, p<.001, 95% CI 1.6-6.2) but not stroke. When excluding acute events within 14 days of diagnosis, AAS was still associated with a significantly higher mortality (adj HR 1.6, p=.011, 95% CI 1.1-2.4) and an increased risk of any first time CV event (adj HR 2.2, p=.018, 95% CI 1.1-4.1), first time MI (adj HR 2.2, p=.012, 95% CI 1.2-4.1) and HF (adj HR 2.9, p=.006, 95% CI 1.4-6.2) but not stroke. Conclusions: AAS is associated with a higher overall mortality and an increased risk of any first time CV event, first time MI and HF that persists beyond the acute phase. These data highlight the risk of CV events among those with AAS and implicate the need for long-term cardiovascular management in these patients.

Background: Hospital readmissions are considered to be a quality of care indicator, yet little is known about their occurrence and predictors after myocardial infarction (MI) in the community. Methods: We identified all Olmsted County residents with incident MI from 1987-2007 and evaluated 30-day rehospitalizations. The reason for readmission was categorized based on ICD-9 code. Safety endpoints of revascularization (percutaneous coronary intervention [PCI] or coronary artery bypass grafting [CABG]) or fibrinolysis included stroke, acute kidney injury (rise in creatinine post-procedure of >0.5 mg/dL), access site complication (PCI), and gastrointestinal or other bleeding. Cox proportional hazard regression models were used to examine the predictors of readmission. Results: A total of 2617 patients (mean age 67 years, 41% female) had incident MI (32% with ST-elevation) from 1987-2007 and survived their initial hospitalization. A total of 583 readmissions occurred within 30 days among 512 (19.6%) patients. Approximately half (n=286, 49.1%) of readmissions were due to cardiovascular causes, and of these, most were due to ischemic heart disease (n=175, 61.2%) or heart failure (n=56, 19.6%). The proportion of non-cardiovascular rehospitalizations increased over time, from 42.2% from 1993-97 to 59.4% from 2003-07 (p for trend=0.01). A minority of those readmitted for cardiovascular reasons required repeat angiogram (n=110, 38.5%) or revascularization (n=88, 50 PCI, 38 CABG). After adjustment for confounders, key factors were associated with increased rehospitalization risk ( Figure ). Following PCI (n=1230), a stroke or bleeding event (adjusted HR 1.69, 95% CI 1.09-2.61, p=0.02) and acute kidney injury (HR 2.50, 95% CI 1.61-3.87, p<0.01) were associated with markedly increased readmission risk. Conclusions: Half of readmissions within 30 days of MI are for non-cardiovascular reasons, and this proportion has increased. Comorbidity and complications of revascularization are key predictors of readmission.

Background: Whether age alone explains the comorbidity burden in heart failure (HF) is unclear. In particular, differences in the burden of co-morbid conditions in HF patients compared to population controls has not been well documented. Methods: The prevalence of 17 chronic conditions defined by the US Department of Health and Human Services were obtained in 1746 incident HF patients from 2000-2010 and controls matched 1:1 on sex and age from Olmsted County, MN. Conditions were ascertained requiring 2 occurrences of a diagnostic code. Logistic regression determined associations of each condition with HF. Results: Among the 1746 matched pairs (mean age 76.2 years, 43.5% men), the prevalence was higher in HF cases for all conditions (p<0.05) except dementia and osteoporosis. After adjusting for all conditions, hypertension, coronary artery disease, arrhythmia, asthma, chronic kidney disease, chronic obstructive pulmonary disease, diabetes, hepatitis, and substance abuse were significantly more common in HF (figure). More than a 2-fold increased odds of hepatitis, arrhythmia, and coronary artery disease was observed among HF cases. Arrhythmia (34.2%), hypertension (31.1%), and coronary artery disease (27.8%) had the largest attributable risk of HF; for example, assuming a causal relationship, if arrhythmias were eliminated, 34% of HF would be avoided. Conclusions: Compared to age- and sex-matched controls, HF patients have a higher prevalence of many chronic conditions, indicating the excess comorbidity in HF is not due to age alone. Some cardiovascular conditions, including arrhythmia, coronary artery disease, and hypertension were more common in HF. Of the non-cardiovascular conditions, hepatitis had the strongest association with HF and was an unanticipated finding that deserves additional investigation. It is important to understand comorbidities as they play a key role in the excess mortality and healthcare utilization experienced by HF patients.

Background: Differences in the prevalence and duration of co-morbid conditions in atrial fibrillation (AF) patients compared to population controls have not been well documented. Methods: The prevalence and duration of 17 chronic conditions defined by the US Department of Health and Human Services, as well as anxiety, obesity, and smoking status, was obtained in a random sample of 1430 patients with incident AF from 2000-2010 and 1430 controls from Olmsted County, MN. Controls were matched to cases 1:1 on sex and age (within 5 years). Chronic conditions were ascertained electronically requiring 2 occurrences of a diagnostic code; the duration of each condition (up to 25 years) was calculated. Logistic regression determined associations of each condition with AF after adjustment for all other conditions. Results: Among the 1430 matched pairs (median age 76 years, 48.6% men), the prevalence of chronic conditions was higher in AF cases compared to controls for all conditions except asthma, dementia, depression, hepatitis, and osteoporosis (figure). However, the duration of the conditions were similar in AF compared to controls, except for hypertension (median duration 12.3 and 9.9 years in AF cases and controls, respectively; p=0.002). After adjusting for all other conditions, obesity, hypertension, congestive heart failure, coronary artery disease, chronic kidney disease, and chronic obstructive pulmonary disease remained significantly more common in AF compared to controls (figure). Conditions with the largest attributable risk of AF were hypertension (25.4%), coronary artery disease (17.7%), and congestive heart failure (12.3%). Conclusions: AF patients have a higher prevalence of many chronic conditions compared to population controls. However, besides hypertension, these comorbidities do not develop earlier in AF. Nevertheless, the excess comorbidity burden in AF is important to characterize and understand as it may partly explain the excess mortality and healthcare utilization experienced by AF patients.

BACKGROUND Epidemiological cohorts can assist with post-marketing surveillance as they provide community-based outcomes data. Concern was raised about the adverse impact of sulfonylureas (SU) drugs on the outcome of diabetes after myocardial infarction (MI). We evaluated the outcome of MI according to treatment among diabetic persons compared to non-diabetic counterparts in a community-based cohort. METHODS All MIs that occurred in Olmsted County, MN between 1979 and 2002 were validated by standardized epidemiological including cardiac pain, biomarkers and ECG Minnesota coding. Diabetes mellitus (DM) was defined by the National Diabetes Data Group criteria. RESULTS Among 2732 persons with MI (mean age 70 ± 12 years, 44% men), 486 (18%) had DM. Subjects with DM were treated with second generation SU (SU2) (24%), insulin (47%) or diet alone (22%) Diabetic subjects were more likely to be overweight, hyperlipidemic and to receive reperfusion therapy during hospitalization than non-diabetic subjects. One year after the MI, 518 subjects died. Diabetic subjects taking SU2 experienced better survival than subjects without diabetes, while subjects treated with diet alone or insulin experienced worse survival. (Figure ). After adjusting for age, sex, reperfusion and duration of DM, an excess risk of death was detected among persons with insulin-treated DM, particularly those with long-standing DM. No association was found for DM patients treated with SU2 or diet. CONCLUSION These data do not support the concern for an adverse impact of SU2 on survival and underscore the potential role of community studies for population surveillance.