Weston, Susan A.

Background: Recent findings suggest a role for heart failure in the etiology of osteoporotic fractures, but the nature of the relationship is unclear and community data are lacking. Methods and Results: We conducted a community-based case-control study comparing prior osteoporotic fractures among Olmsted County, Minnesota, residents newly diagnosed with heart failure in 1979-2002 (cases) to age- and sex-matched community controls without heart failure (961 pairs; mean age: 76 years; 54% women). Subjects were then followed forward in time to July 2009 to evaluate the risk of fracture subsequent to the heart failure diagnosis. Prior fractures were more frequent in heart failure cases than controls: 23% versus 19%, P =0.02; adjusted odds ratio (OR) for any osteoporotic fracture 1.39 (95% CI: 1.07-1.81). This was related to hip fractures (OR: 1.82; 95% CI: 1.25-2.66) with little or no association with other fractures. Over a mean follow-up of 7.5 years, 536 new osteoporotic fractures occurred in 444 individuals. The adjusted fracture risk was higher among heart failure patients compared to controls (hazard ratio [HR]: 1.32; 95% CI: 0.98-1.79), again largely attributable to hip fractures (HR: 1.58; 95% CI: 1.03-2.41). Conclusions: Patients diagnosed with heart failure experience an excess risk of fractures both before and after the diagnosis of heart failure, which is related to hip fractures. These findings suggest common underlying and co-occurring mechanisms for heart failure and hip fracture and underscore the crucial importance of preventing falls in elderly heart failure patients.

Background: Echocardiography is an important component of the assessment of patients with heart failure (HF). However, its longitudinal use after initial HF diagnosis has not been evaluated. Methods: We studied patterns of echocardiogram use after HF diagnosis among a random sample of validated incident HF cases in Olmsted County, Minnesota, from 1987 to 2006. Results: Among 1472 HF patients (mean age 76.0 years, 45% male), 4817 echocardiograms were obtained over a mean follow-up of 5.1 years. The majority were transthoracic (n=3952, 82%), with fewer transesophageal (n=604, 13%) and stress (n=250, 5%) studies obtained. Most patients died during follow-up (n=1126, 76%), and thus had their entire lifetime after HF diagnosis captured. The number of echocardiograms per person ranged from 0-38 (Figure) with a median (25 th , 75 th percentile) of 2 (1, 4). The mean rate of echocardiograms obtained per 10 years of follow-up was 6.4, and increased over time with mean echocardiograms per 10 years follow-up of 4.9, 5.9, 7.2, and 7.8 for persons diagnosed from 1987-1991, 1992-96, 1997-2001, and 2002-06, respectively (p for trend <0.001). Men had echocardiograms more frequently than women (7.2 vs. 5.7 per 10 person years follow-up, p<0.001). Patients who were younger at diagnosis had more frequent echocardiography with rates of 7.1, 6.8, and 5.2 per 10 years follow-up for those who were <70 years, 70-79 years, and 80 years or older at diagnosis (p for trend <0.001). Conclusions: Most patients have multiple echocardiograms performed after HF diagnosis, and echocardiography use in patients with HF has increased over time. Men and younger patients have higher rates of use after HF diagnosis.

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<0.05 for each). Development of advanced HF was associated with increased risks of all-cause hospitalization (adjusted HR 3.00; 95% CI 2.65-3.41, p<0.001), HF hospitalization (HR 10.24, 95% CI 8.67-12.10), all-cause mortality (HR 5.00, 95% CI 4.46-5.59, p<0.001), and cardiovascular mortality (HR 7.84, 95% CI 6.74-9.12). 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.

Introduction: Heart failure (HF) is a clinical syndrome with high mortality. Left ventricular ejection fraction (EF) determines clinical phenotyping and HF is classified most often as preserved (HFpEF) or reduced (HFrEF) EF. The importance of expanding phenotyping beyond EF is recognized. We hypothesized that machine learning applied to echocardiography will provide information important for deep phenotyping. Methods: We collected clinical and echo data in a HF community cohort between 2013 and 2017. Unsupervised clustering was applied to 23 echo variables using partitioning around medoids (PAM), with Gower dissimilarity used to address the mixed variable types. Proportional hazards regression examined the association between cluster assignment and death. Results: We identified 4978 persons with HF [mean age 73.9 years (SD 13.9), 47% women] with echocardiography within 6 months of diagnosis. We identified 2 primary clusters using echo variables, as depicted using t-Distributed Stochastic Neighbor Embedding (t-SNE) applied to the dissimilarity matrix (Figure). Diastolic function variables exhibited the largest differences by clusters as shown by absolute standardized differences (Table). After 3.2 + 1.9 years of follow up, 2001 deaths occurred. Assignment to cluster 2 was associated with a near 20% excess risk of death independent of age, sex, comorbidity, and EF [HR 1.17 (1.07, 1.28) p<0.001]. Conclusions: Unsupervised clustering applied to echocardiography in a large community HF cohort identified 2 distinct clusters, which defined HF subgroups with different characteristics and were independently associated with risk of death.

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.

Abstract Background Cognitive function is essential to effective self‐management of heart failure (HF). Alzheimer's disease and Alzheimer's disease‐related dementias (AD/ADRD) can coexist with HF, but its exact prevalence and impact on health care utilization and death are not well defined. Methods Residents from 7 southeast Minnesota counties with a first‐ever diagnosis code for HF between January 1, 2013 and December 31, 2018 were identified. Clinically diagnosed AD/ADRD was ascertained using the Centers for Medicare and Medicaid (CMS) Chronic Conditions Data Warehouse algorithm. Patients were followed through March 31, 2020. Cox and Andersen‐Gill models were used to examine associations between AD/ADRD (before and after HF) and death and hospitalizations, respectively. Results Among 6336 patients with HF (mean age [SD] 75 years [14], 48% female), 644 (10%) carried a diagnosis of AD/ADRD at index HF diagnosis. The 3‐year cumulative incidence of AD/ADRD after HF diagnosis was 17%. During follow‐up (mean [SD] 3.2 [1.9] years), 2618 deaths and 15,475 hospitalizations occurred. After adjustment, patients with AD/ADRD before HF had nearly a 2.7 times increased risk of death, but no increased risk of hospitalization compared to those without AD/ADRD. When AD/ADRD was diagnosed after the index HF date, patients experienced a 3.7 times increased risk of death and a 73% increased risk of hospitalization compared to those who remain free of AD/ADRD. Conclusions In a large, community cohort of patients with incident HF, the burden of AD/ADRD is quite high as more than one‐fourth of patients with HF received a diagnosis of AD/ADRD either before or after HF diagnosis. AD/ADRD markedly increases the risk of adverse outcomes in HF underscoring the need for future studies focused on holistic approaches to improve outcomes.

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: The increasing prevalence of heart failure (HF) and high associated costs has spurred investigation of factors related to adverse outcomes in these patients. Reports to date present discrepant evidence regarding the link between depression and HF outcomes, and only scarce data related to healthcare utilization in the form of emergency department (ED) visits are available. Purpose: To evaluate the relationship of depression with healthcare utilization and death among HF patients in the community. Methods: Residents of Olmsted, Dodge, and Fillmore, MN counties with HF were prospectively recruited between October 2007 and December 2010, and completed a 9-item Patient Health Questionnaire (PHQ-9) for depression categorized as: none-minimal (PHQ-9 score 0-4), mild (5-9), or moderate-severe (≥10). Anderson-Gill models were used to determine if depression predicted hospitalizations and ED visits while proportional hazards regression estimated hazard ratios for death. Results: Among 411 HF patients (mean age 73±13, 58% male), 15% had moderate-severe depression, 27% mild, and 58% none-minimal. Over a mean follow-up of 1.5 years, 613 hospitalizations, 786 ED visits, and 75 deaths occurred. The risk of all adverse outcomes increased stepwise with increasing severity of depression (Table). After adjustment for key clinical characteristics, moderate-severe depression was associated with nearly a 2-fold increased risk of hospitalization and ED visits, and almost a 4-fold increased risk of death. These results are independent of coexisting comorbidities. Conclusions: Depression is frequent among HF patients in the community and independently predicts a significant increase in the use of healthcare resources and mortality. Greater attention to the recognition and management of depression in HF may improve clinical outcomes and decrease healthcare utilization and expenditures in these patients. Hazard Ratios (95%CI) for Hospitalizations and All-Cause Mortality by Severity of Depression None-Minimal Mild Moderate-Severe P for trend Hospitalizations Crude 1.00 (ref) 1.23 (0.91-1.66) 2.01 (1.39-2.89) <0.001 Fully-Adjusted * 1.00 (ref) 1.15 (0.86-1.54) 1.93 (1.37-2.71) 0.001 Emergency Department Visits Crude 1.00 (ref) 1.42 (1.03-1.96) 1.99 (1.42-2.79) <0.001 Fully-Adjusted * 1.00 (ref) 1.39 (1.00-1.93) 1.98 (1.40-2.79) <0.001 All-Cause Mortality Crude 1.00 (ref) 1.53 (0.87-2.68) 3.33 (1.95-5.70) <0.001 Fully-Adjusted * 1.00 (ref) 1.55 (0.88-2.74) 3.84 (2.21-6.68) <0.001 * Adjusted for age, sex, and Charlson comorbidity index

Objective: To determine among community heart failure (HF) patients whether frailty is associated with an increased risk of hospitalization, emergency department (ED) visits and death, independently of comorbidities. Background: Frailty is associated with adverse outcomes in some populations; however the prognostic value of frailty among HF patients is not fully documented, particularly for healthcare utilization. Methods: Olmsted, Dodge and Fillmore County residents with HF between 10/2007 and 12/2010 were prospectively recruited to undergo frailty assessment. Frailty was defined as 3 or more of the following: unintentional weight loss >10 lbs. in 1 year, physical exhaustion, weak grip strength, and slowness and low activity measured by the SF-12 physical component score. Intermediate frailty was defined as having 1-2 components. To account for repeated events, Anderson-Gill modeling was used to determine if frailty predicted hospitalization or ED visits. Cox proportional hazards regression examined associations between frailty and death. Results: Among 409 patients (mean age 73±13, 58% male), 19% were frail and 55% had intermediate frailty. Within one year, 449 hospitalizations, 523 ED visits and 34 deaths occurred. There was a positive graded association between frailty and hospitalization and ED visits (Table). After adjustment for age, sex, ejection fraction and comorbidity, frailty was associated with an 80% increased risk of hospitalization and a 60% increased risk of ED visits. Frailty was also associated with more than a 2-fold increased risk of death after adjustment. Conclusion: In the community, frailty is prevalent and is a strong and independent predictor of hospitalizations, ED visits and death among HF patients. As it is independent from coexisting comorbidities, frailty defines new avenues for intervention and should be formally assessed clinically. Hazard Ratios (95% CI) for Hospitalizations, Emergency Department Visits and Death by Frailty Status Not Frail Intermediate Frail Frail P for trend Hospitalization Crude 1.00 1.46 (1.05-2.02) 2.15 (1.45-3.19) <0.001 Fully-adjusted 1.00 1.29 (0.94-1.77) 1.82 (1.22-2.73) 0.005 Emergency Department Visits Crude 1.00 1.59 (1.14-2.21) 1.88 (1.22-2.90) 0.002 Fully-adjusted 1.00 1.46 (1.05-2.05) 1.58 (1.01-2.48) 0.034 Death Crude 1.00 1.40 (0.73-2.69) 3.98 (2.01-7.90) <0.001 Fully-adjusted 1.00 0.87 (0.44-1.73) 2.42 (1.19-4.95) 0.003