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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 rate3 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 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.

Introduction: Advanced or “Stage D” heart failure (Adv HF) patients are at high risk of poor outcomes. However, recognition of Adv HF is limited as diagnostic criteria are complex. Administrative algorithms to identify Adv HF could enable better understanding of who has advanced HF and lead to enhanced therapeutics development, dissemination, and outcomes. Methods: In a population-based cohort of all Olmsted County, Minnesota residents with ≥1 HF billing code 2007-2017 (n=9881), we identified all patients with Adv HF (n=753) by applying the gold standard European Society of Cardiology Adv HF criteria via manual medical review by a HF cardiologist. The Adv HF index date was the date the patient first met all ESC criteria. We then developed candidate algorithms to identify Adv HF using only administrative data (billing codes and HF prescriptions or comorbidities known to affect HF outcomes), applied them to the entire HF cohort and assessed their ability to identify patients with Adv HF on or after their Adv HF index date. Results: A single hospitalization (Hsp) for HF or ventricular arrhythmias (VA, 2007-2017) identified all patients with Adv HF (sensitivity 100%), but the PPV was low (36.4%). Requiring more Hsp, other signs of Adv HF such as hyponatremia, acute kidney injury, hypotension or high-dose diuretic use decreased the sensitivity but improved specificity and PPV. As Adv HF was relatively uncommon, negative predictive values (NPV) were high regardless of algorithm characteristics. Conclusions: Algorithms using administrative data can identify patients with Adv HF with clinically useful accuracy.

Introduction: Some patients with heart failure (HF) will go on to develop advanced HF, characterized by severe HF symptoms despite attempts to optimize medical therapy. Our understanding of advanced HF at a population level remains limited. The goals of this study were to determine the risk of developing advanced HF in patients with newly diagnosed HF, identify risk factors for developing advanced HF, and evaluate the impact of advanced HF on outcomes. Methods: This was a population-based, retrospective cohort study of Olmsted County, Minnesota residents with a new clinical diagnosis of HF between 2007-2017. The primary outcome was development of advanced HF, defined using the 2018 European Society of Cardiology Criteria. Risk factors for development of advanced HF from the time of incident HF diagnosis were examined using cause-specific Cox proportional hazard regression models. The associations of development of advanced HF with risks of hospitalization and mortality were examined using Andersen-Gill and Cox models, respectively, with advanced HF treated as a time dependent covariate. Results: There were 4597 residents with incident HF from 2007 to 2017. The cumulative incidence of advanced HF was 6.0%, 9.1%, and 11.5% at 2, 4, and 6 years after incident HF diagnosis. Characteristics independently associated with development of advanced HF included older age, male sex, diabetes, chronic obstructive pulmonary disease, peripheral vascular disease, lower serum sodium, worse right ventricular function, left atrial enlargement, higher estimated filling pressures, and higher right ventricular systolic pressure (p Conclusions: In this population-based study, clinical, laboratory and echocardiographic characteristics at the time of incident HF diagnosis were associated with future risk of advanced HF. Development of advanced HF was associated with markedly increased morbidity and mortality.

Many individuals living with heart failure (HF) rely on unpaid support from their partners, family members, friends, or neighbors as caregivers to help manage their chronic disease. Given the advancements in treatments and devices for patients with HF, caregiving responsibilities have expanded in recent decades to include more intensive care for increasingly precarious patients with HF—tasks that would previously have been undertaken by healthcare professionals in clinical settings. The specific tasks of caregivers of patients with HF vary widely based on the patient’s symptoms and comorbidities, the relationship between patient and caregiver, and the complexity of the treatment regimen. Effects of caregiving on the caregiver and patient range from physical and psychological to financial. Therefore, it is critically important to understand the needs of caregivers to support the increasingly complex medical care they provide to patients living with HF. This scientific statement synthesizes the evidence pertaining to caregiving of adult individuals with HF in order to (1) characterize the HF caregiving role and how it changes with illness trajectory; (2) describe the financial, health, and well-being implications of caregiving in HF; (3) evaluate HF caregiving interventions to support caregiver and patient outcomes; (4) summarize existing policies and resources that support HF caregivers; and (5) identify knowledge gaps and future directions for providers, investigators, health systems, and policymakers.

Type 2 diabetes mellitus is a risk factor for incident heart failure and increases the risk of morbidity and mortality in patients with established disease. Secular trends in the prevalence of diabetes mellitus and heart failure forecast a growing burden of disease and underscore the need for effective therapeutic strategies. Recent clinical trials have demonstrated the shared pathophysiology between diabetes mellitus and heart failure, the synergistic effect of managing both conditions, and the potential for diabetes mellitus therapies to modulate the risk of heart failure outcomes. This scientific statement on diabetes mellitus and heart failure summarizes the epidemiology, pathophysiology, and impact of diabetes mellitus and its control on outcomes in heart failure; reviews the approach to pharmacological therapy and lifestyle modification in patients with diabetes mellitus and heart failure; highlights the value of multidisciplinary interventions to improve clinical outcomes in this population; and outlines priorities for future research.

Background— In 2000, the definition of myocardial infarction (MI) changed to rely on troponin rather than creatine kinase (CK) and its MB fraction (CK-MB). The implications of this change on trends in MI incidence and outcome are not defined. Methods and Results— This was a community study of 2816 patients hospitalized with incident MI from 1987 to 2006 in Olmsted County, Minnesota, with prospective measurements of troponin and CK-MB from August 2000 forward. Outcomes were MI incidence, severity, and survival. After troponin was introduced, 278 (25%) of 1127 incident MIs met only troponin-based criteria. When cases meeting only troponin criteria were included, incidence did not change between 1987 and 2006. When restricted to cases defined by CK/CK-MB, the incidence of MI declined by 20%. The incidence of non–ST-segment elevation MI increased markedly by relying on troponin, whereas that of ST-segment elevation MI declined regardless of troponin. The age- and sex-adjusted hazard ratio of death within 30 days for an infarction occurring in 2006 (compared with 1987) was 0.44 (95% confidence interval, 0.30 to 0.64). Among 30-day survivors, survival did not improve, but causes of death shifted from cardiovascular to noncardiovascular ( P =0.001). Trends in long-term survival among 30-day survivors were similar regardless of troponin. Conclusions— Over the last 2 decades, a substantial change in the epidemiology of MI occurred that was only partially mediated by the introduction of troponin. Non–ST-segment elevation MIs now constitute the majority of MIs. Although the 30-day case fatality improved markedly, long-term survival did not change, and the cause of death shifted from cardiovascular to noncardiovascular.

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 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.

Introduction: Various risk models have been used to predict mortality after implantation of continuous-flow ventricular assist devices (CF-VADs). Discriminatory power and predictive accuracy vary, and there is a need to develop and validate a contemporary risk score in a large multicenter patient cohort. Hypothesis: We sought to develop an early mortality risk score utilizing a large voluntary research registry of patients implanted with CF-VADs, with the focus on increased discriminatory power. Methods: From May 2004 to May 2015, 1150 patients in the Mechanical Circulatory Support Research Network (MCSRN) registry were randomly divided into equal-sized derivation and validation samples (n=575, each group). Candidate predictors from the derivation sample were subjected to backward stepwise logistic regression until the model with lowest Akaike information criterion value was identified for predicting 90-day mortality. A risk score was developed based on the variables and their respective regression coefficients in the final model. Discriminatory power of the risk score was evaluated using receiver operating characteristic analysis, and calibration was assessed using Hosmer-Lemeshow goodness of fit test. Results: Overall 90-day mortality was 9.4% (n=99). The final logistic regression model consisted of 9 predictors: Age at implant, preoperative mechanical ventilation, serum total bilirubin, hemoglobin, tricuspid valve regurgitation severity, left ventricular end-diastolic diameter, cardiac index, pulmonary capillary wedge pressure, and destination therapy (DT) as an indication for pump placement. The area under the curve was 0.86 in the derivation sample (95% CI, 0.75-0.97) and 0.75 in the validation sample (95% CI, 0.63-0.86). Hosmer-Lemeshow goodness of fit test yielded insignificant values in both samples (p=0.75, p=0.58) consistent with good calibration. Conclusions: The proposed 90-day mortality MCSRN risk score provides highest-to-date discriminatory power when compared to already published models. The risk score is applicable to a contemporary large cohort of patients implanted with CF-VADs for either indication (bridge or DT).

Introduction: Axial and centrifugal-flow left ventricular assist devices (LVAD) have varied response to changes in loading conditions. Whether ventricular size modulates the response to LVAD therapy between the axial flow Heartmate II (HMII) and centrifugal flow Heartware (HVAD) is unknown. Hypothesis: Adverse event and survival rates between devices are affected by recipient pre-op left ventricular end-diastolic diameter (LVEDD). Methods: Data on 1,149 continuous-flow LVAD recipients from May 2004 to May 2015 was pooled from the Mechanical Circulatory Support Research Network (MCSRN). The effect of pre-op LVEDD on the instantaneous hazard of death and adverse events was evaluated between HMII (n=864) and HVAD (n=283). Results: The average LVEDD was 7.0cm and did not differ between the device recipients. Patients with a smaller LVEDD (≤ 6.3cm) were more likely female 39% v. 24% (p < 0.0001) and to have an ischemic cardiomyopathy (30% v. 24%, p = 0.045). For every 1cm increase in pre-op LVEDD, the adjusted hazard ratio (HR) for mortality increased with HVAD (HR 1.31, 95% CI 0.94-1.82, p = 0.005) and decreased with HMII (HR 0.78, 95% CI 0.67-0.92, p = 0.005), Figure 1a. Other predictors of mortality included age (HR 1.31, 95% CI 1.12 - 1.53 per 10y, p < 0.001) and bilirubin (HR 1.15, 95% CI 0.94-1.42 per mg/dL, p = 0.027). LVEDD by device type interaction was not a significant predictor of gastrointestinal bleeding or pump thrombosis. The risk of stroke increased with LVEDD for HVAD and decreased for HMII, but this did not reach statistical significance, Figure 1b. Ischemic etiology of heart failure (HR 1.7 95% CI 1.14 - 2.55, p = 0.01) and HVAD device use (HR 1.47 95% CI 1.00 - 2.17, p = 0.03) were significant predictors of stroke. Conclusions: Our data suggest important differences exist in patient outcomes between HMII and HVAD based on pre-op ventricular size. Studies are needed to determine if these differences in outcome are due to device or flow-specific differences in patient support.

Introduction: Frailty has recently been shown to be associated with increased risk of death after continuous-flow left ventricular assist device (CF-LVAD) implantation as destination therapy (DT), but no data exists specifically analyzing its association with specific early and late adverse events. Methods: Between February 2007 and May 2014, 251 patients (205 male) underwent primary implantation of CF-LVAD at our institution; 157 (63%) were implanted as DT and preoperative frailty assessment was available in 96 pt. Frailty was identified in 58/96 (60%) patients according to the deficit index (31 impairments, disabilities and comorbidities) and defined as > 25% deficits. Age (67 vs. 64 years, p=0.12), male sex (79% vs. 87%, 0.63), chronic kidney disease (64% vs. 63%, p=0.74), creatinine (1.7 vs. 1.5, p=0.1), hemoglobin (11.6 vs. 11.5, p=0.98), and albumin levels (3.7 vs. 3.8, p=0.53) were similar between frail and non-frail pt, while diabetes (59% vs. 13%, p Results: All patients underwent CF-LVAD implantation and cardiopulmonary bypass time was similar between groups (102 vs. 111 min., p=0.3). There were no significant differences in early adverse events between frail and non-frail pt, including inotrope duration (120 vs. 96 hr., p=0.11), right ventricular failure (19% vs. 13%, p=0.44), respiratory failure (26% vs. 18%, p=0.34), acute renal failure (16% vs. 13%, p=0.69), and hepatic dysfunction (16% vs. 13%, p=0.69). Median length of stay (20 vs. 16 days, p=0.25) and early mortality (12% vs. 8%, p=0.48) were also similar. During a median follow up of 2 years with 224 patient/years of support, any GI bleed (43% vs. 42%, p=0.79), any thromboembolic event (34% vs. 39%, p=0.74), and driveline infection (10% vs. 26%, p=0.052). Conclusions: In this select cohort of patients, frailty did not portend higher risk of adverse events after CF-LVAD implantation for DT despite prior observation that late survival is reduced in these patients. These findings are extremely important in patient selection and counseling of patients prior to LVAD implantation.

Background: Heart failure (HF) patients are experiencing an epidemic of hospitalizations. Nevertheless, data on the frequency and distribution of hospitalizations over the course of the disease are lacking. Methods: We determined the rates of hospitalizations during periods of follow-up in Olmsted County, MN residents with incident HF from 2000-2010. HF was identified using ICD-9 code 428 and validated by the Framingham criteria. All hospitalizations were obtained for the 2 years following incident HF and each was categorized as due to HF, other cardiovascular (ICD-9 codes 390-427, 429-459), or non-cardiovascular causes. Follow-up was divided into discrete time periods (epochs): 0-30, 31-182, 183-365, and 366-730 days. Negative binomial regression examined associations between epochs of follow-up time and hospitalizations. Results: Among 1702 incident HF patients (mean age 76, 44% male), 1143 (67%) were hospitalized at index. Over the 2 year follow-up, 3008 hospitalizations were observed among 1136 patients, and 351 patients were hospitalized within 30 days of incident HF (median time from HF to hospitalization: 11 days). The majority of hospitalizations were due to non-cardiovascular causes (63% vs. 14% HF, 23% other cardiovascular); however, a larger proportion of HF and other cardiovascular hospitalizations were observed within the first 30 days (52% non-cardiovascular, 18% HF, 30% other cardiovascular) compared to the other time periods. The rate of hospitalization was highest within the first 30 days and was similar across sex, presentation of incident HF (inpatient, outpatient), and type of HF (preserved (≥50%), reduced ( Conclusions: HF patients experience high rates of hospitalizations, particularly within the first 30 days, and the majority of hospitalizations are for non-cardiovascular causes. Continued efforts to manage comorbid conditions and reduce hospitalizations in HF patients are needed.

Background: Contemporary community data on the prognostic importance of heart failure (HF) after myocardial infarction (MI) according to (1) preserved or reduced ejection fraction (EF) and (2) the time of its occurrence are lacking. We examined HF-associated mortality and secular trends in survival among patients with and without HF in a geographically defined cohort of MI survivors. Methods: All residents of Olmsted County, Minnesota (n=2,596) who had a first MI diagnosed in 1990-2010 and no prior HF were followed through 2012 for HF incidence and mortality. Framingham Heart Study criteria were used to define HF, which was further classified according to EF. Cox models were used to examine (1) the hazard ratios (HRs) for death associated with HF type (preserved or reduced) and timing (early- or late-onset); and (2) secular trends in survival by HF status. Results: During a mean (SD) follow-up of 4 (3) years, 748 patients developed HF (519 within 30 days) and 673 died. After adjusting for age, sex, and year of index MI, HF as a time-dependent variable was strongly associated with mortality (HR=3.33 vs. HF-free subjects). Mortality did not differ by HF type, but was markedly higher for late-onset (>30 days) than for early-onset HF. Further adjustment for indicators of MI severity and comorbidity burden, acute intervention, and recurrent MI attenuated the association (Table). The age- and sex-adjusted HRs for mortality in 2001-2010 vs. 1990-2000 were 0.71 (95% CI: 0.58-0.88) in HF and 0.74 (95% CI: 0.59-0.93) in HF-free patients. These estimates equate to 10.18 (95% CI: 3.82-16.54) and 3.75 (95% CI: 0.90-6.61) fewer deaths per 100 subjects at 5 years of follow-up in participants with and without HF, respectively. Conclusions: HF markedly increases the risk of death after MI. The magnitude of this excess risk is similar between preserved and reduced EF but greater for late- vs. early-onset HF. Mortality declined over time in all patients with MI, and the absolute reduction in the risk of death was substantially greater for those with HF.

Background: Multimorbidity is common in heart failure (HF), yet differences in co-morbid chronic conditions by type of HF (HF with preserved vs. reduced ejection fraction (EF)) are not well documented. Methods: We determined the prevalence and distribution of 25 chronic conditions by preserved vs. reduced EF among patients with incident HF enrolled in a community study from 9/2003-6/2012. HF was validated by the Framingham criteria, and an EF ≥50% defined preserved EF. Chronic conditions were identified within the 5 years prior to HF by codes defined by Centers for Medicare & Medicaid Services. Logistic regression determined associations of each comorbidity with type of HF (preserved vs. reduced EF) after adjusting for age and sex. Results: Among 668 incident HF patients (mean age 74±14, 51% male), the most common co-morbid conditions were hypertension, hyperlipidemia, and ischemic heart disease. Cataracts, rheumatoid arthritis/osteoarthritis, and anemia were also common, occurring in >1/3 of HF patients. On average, patients with preserved EF had 1 extra co-morbid condition compared to those with reduced EF (6 vs. 5, respectively). After adjusting for age and sex, comorbidities associated with HF with preserved EF include hypertension, hyperlipidemia, cataracts, rheumatoid arthritis/osteoarthritis, anemia, chronic kidney disease, chronic obstructive pulmonary disease, and depression, whereas a prior myocardial infarction was associated with presenting with reduced EF (figure). The remaining co-morbid conditions (including some not shown in the figure, such as breast, colorectal, lung, endometrial, and prostate cancer, and benign prostatic hyperplasia) were not associated with type of HF. Conclusions: HF patients presenting with preserved EF have more co-morbid chronic conditions compared to those with reduced EF. This excess comorbidity burden is important to characterize and understand as it may explain differences in outcomes and healthcare utilization between HF patients with preserved and reduced EF.

Introduction: Heart failure (HF) is a chronic illness that occurs within a context of multiple comorbidities, including osteoporosis and fractures. While the causal pathway leading to elevated fracture risk in HF has yet to be determined, a potential mechanism may be increased sympathetic activation that inhibits bone formation and enhances resorption. By antagonizing sympathetic tone, β-blockers may protect against bone loss and, thereby, fractures. We assessed the association of HF with subsequent osteoporotic fractures by β-blocker use in a community setting. Methods: Olmsted County, Minnesota, residents meeting Framingham criteria for incident HF from 1990-2002 and community controls without HF, who were matched (1:1) to cases on age, sex, and index year, were studied using the resources of the Rochester Epidemiology Project. Major osteoporotic fracture (proximal femur, lumbar/thoracic vertebrae, distal forearm, or proximal humerus) risk in HF was compared directly with that in their matched controls utilizing a stratified Cox model with the case/control pairs forming the strata. Death as a competing risk was accounted for using the Fine & Gray model. Results: Among 1,050 participants (50% women; 525 with HF and 525 controls) 229 developed osteoporotic fractures during a mean follow-up of 6 years. The incidence rates of osteoporotic fracture per 1,000 person-years were 47.5 in HF cases and 30.4 in controls ( P =0.001). After adjustment for prior fracture and Charlson comorbidity score, the hazard ratio (HR) for fracture in HF cases vs. controls was 1.70 (95% CI: 1.17-2.47). β-blockers were prescribed in 45% of HF cases after diagnosis. The association between HF and fractures differed according to β-blocker usage. The HRs were 1.45 (95% CI: 0.86-2.47) and 2.16 (95% CI: 1.23-3.79) in HF cases prescribed and not prescribed β-blockers, respectively, when compared with their matched controls. Accounting for death as a competing risk, the HRs were 1.06 (95% CI: 0.64-1.76) and 1.63 (95% CI: 0.99-2.70) in HF cases on and off β-blockers, respectively. Conclusion: These findings suggest a modifying effect of β-blockers on the association between HF and osteoporotic fractures, which warrants a more thorough evaluation.

Background: Contemporary data on survival after incident acute coronary syndrome (ACS), including both myocardial infarction (MI) and unstable angina (UA), are limited. Objective: To describe survival after incident ACS, to determine if it differs by ACS type (MI or UA) and to determine whether it has improved over time. Methods: Olmsted County, MN residents hospitalized between 1/1/2005-12/31/2010 were screened for incident ACS. ACS was defined as either MI validated by standard epidemiological criteria or UA validated by the Braunwald classification. Patients were followed for death from any cause. Cox proportional hazards regression was used to determine whether survival differed by ACS type, while adjusting for year of diagnosis, age, sex and comorbidities. Results: Among 1,160 incident ACS cases (mean±SD age 66.9±14.8, 60% male), 35% were UA and 65% were MI. After a mean (SD) follow up of 3.7 (2.1) years, 274 deaths occurred. The 3-year Kaplan-Meier survival estimate for MI was 79.6% (95% CI: 76.7%-82.6%) and for UA was 84.9% (95% CI: 81.3%-88.6%) (log-rank p=0.011). The association of ACS type with survival differed by age (p=0.056). After adjustment for year of diagnosis, sex and comorbidities, no difference in survival was observed between ACS types among those aged Conclusions: Survival did not differ between UA and MI patients younger than 60, however among patients 60 or older, survival was worse among those with an MI. Survival after ACS did not change over the study period.

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 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: Heart failure (HF) care constitutes an increasing economic burden on the healthcare system, and has become a key focus in the healthcare debate. Costs incurred at the end of life can be particularly high in some populations, however, end of life costs among a community population of HF patients have not been well delineated. Methods: Olmsted County residents with incident HF from 1987-2006 were identified and followed until death. Direct medical costs incurred in the last 6 months prior to death were obtained using population-based administrative data through 2010. For those that died within 6 months of HF diagnosis, costs were included from diagnosis until death. Costs were inflated to 2010 U.S. dollars using the general Consumer Price Index (CPI). Results: A total of 862 HF patients were identified, died during follow-up, and had complete cost data (mean age 79.4 years, 46.4% male, 56.5% EF≥50%). Median costs within the last 6 months of life were $12,069 per person (25 th -75 th percentile $1768 - $30,841, mean $24,052), with the majority accumulated during hospitalizations (median $8849 per person, mean $20,263, 84.2% total costs for population). A total of 596 (69.1%) patients were hospitalized in the last 6 months of life, and 235 (27.3%) died in the hospital. Costs progressively increased in the months prior to death (Figure), with nearly half (43.4%) of total costs in the last 6 months of life accumulated during the month before death. End of life costs did not change over the study period (p=0.154 adjusted for age and sex). Conclusions: End of life costs are high among community HF patients, particularly in the final month of life. Most of these costs are accumulated during hospitalizations, and a large proportion of HF patients died in the hospital. Among patients with HF nearing the end of life, alternative strategies of care that avoid hospitalizations may be particularly cost-saving.

Introduction: Mortality among patients with heart failure (HF) is high. Though individual biomarkers have been studied to determine their value in risk prediction, the role of a multimarker strategy in predicting mortality above established risk indicators requires evaluation in a relevant cohort using robust analytical methods. Objective: To determine whether adding C-reactive protein (CRP), B-type natriuretic peptide (BNP), and troponin T (TnT) to established risk indicators improved HF mortality risk prediction. Methods: Olmsted County residents presenting with HF from July 2004 to September 2007 were prospectively recruited to undergo biomarker measurement. We investigated whether addition of CRP, BNP, and TnT to a model including established risk indicators improved 6-month mortality risk prediction using multiple methods ( c statistic, net reclassification index, integrated discrimination improvement). Results: Of 566 participants (mean age 77±13 years, 48% male), 87(15%) patients died after 6 months follow-up. Patients with CRP (c statistic from 0.747 to 0.832 (p Conclusions: The combined use of CRP, BNP, and TnT markedly improved the prediction of 6-month mortality in HF beyond established risk indicators. Implementation of a multimarker strategy including CRP, BNP, and TnT for risk prediction in HF should be considered. This research has received full or partial funding support from the American Heart Association, AHA Midwest Affiliate (Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, South Dakota & Wisconsin).

Background— Tumor necrosis factor-α (TNFα), an inflammatory cytokine, was reported to be elevated in trials of heart failure (HF) with reduced ejection fraction (EF) and associated with mortality. Whether this is true for HF with preserved EF is unknown, and community data are lacking. We evaluated the distribution of TNFα, its association with baseline characteristics and mortality, and its benefit in assessing risk in community HF patients. Methods and Results— Olmsted County residents with active HF from July 2004 to March 2007 (n=486; mean age, 76.7 years; EF ≥50%, 55%) were prospectively recruited. Clinical characteristics and TNFα were measured. Elevated TNFα (more than the assay limit of normal of 2.8 pg/mL) was present in 143 (29%). Higher TNFα was associated with decreased creatinine clearance, nonsmoking status, anemia, and greater comorbidity ( P trend P =0.016), with 1-year mortality estimates of 16%, 18%, 23%, and 32% from the lowest to highest quartile, respectively. After adjustment for age, sex, and EF, the hazard ratios for death were 1.24, 1.37, and 1.90 from the second to the highest TNFα quartile, respectively ( P trend =0.007). TNFα contributed to risk assessment as indicated by increases in the area under the receiver operating characteristic curves in all models examined ( P P =0.60 interaction term of TNFα and EF). Conclusions— TNFα was elevated in a large portion of community HF patients, was associated with a large decrease in survival, and provided a significant incremental increase in risk assessment above established indicators. TNFα is useful for risk assessment in HF patients with preserved and reduced EF.