Background: The effective self-management of heart failure (HF) is highly dependent on cognitive function. Dementia frequently coexists with HF, but its exact prevalence and impact on health care utilization and death is not well understood. Methods: Residents from 7 southeast Minnesota counties with a first-ever code for HF (ICD-9 428 and ICD-10 I50) between 1/1/2012 and 12/31/2017 were identified. Dementia before and after the HF diagnosis was ascertained with codes recommended by the US Department of Health and Human Services. Patients were followed through 12/31/2018 for death and hospitalizations. Cox and Andersen-Gill models were used to examine associations between dementia (prior and post HF) and death and hospitalizations, respectively. Dementia after HF was analyzed as a time-dependent variable. Results: Among 6,312 patients with HF (mean age 75 years, 49% female), 636 (10%) had a prior diagnosis of dementia. After a mean (SD) follow-up of 3.1 (1.8) years, 601 (9.5%) patients were diagnosed with dementia post HF. The median time from HF to dementia was 1.3 years, with 43% of dementia cases occurring within 1 year and 64% within 2 years post HF. During follow-up, 2,678 deaths and 15,095 hospitalizations occurred. After adjustment, patients with dementia before HF had nearly a 2-times increased risk of death and 10% increased risk of hospitalization compared to those that did not have dementia (Table). Dementia after HF was associated with a 78% increased risk of death and 63% increased risk of hospitalization compared to those that did not have dementia. Conclusions: Approximately 10% of patients had dementia prior to HF and 10% develop dementia shortly after HF diagnosis. Patients with HF and dementia have an increased risk of death and hospitalization compared to dementia-free counterparts. These data underscore the importance of recognizing the presence and impact of dementia on outcomes in HF to optimize care delivery.
Abstract 148: Differences Between Participants and Nonparticipants in a Survey of Community Patients with Heart Failure
Background: Patient reported measures are fundamental to patient centered research and are often collected by questionnaires. Low participation can compromise the validity of the results; transparent reporting and comparing characteristics of participants to nonparticipants is important to assess the generalizability of survey results. We analyzed participation in a survey of social determinants of health among a population-based sample of patients with heart failure (HF). Methods: A total of 7920 residents from 11 Minnesota counties were identified with a first-ever code for HF (ICD-9 428 and ICD-10 I50) between 1/1/2013 and 12/31/2016. Participants completed a battery of 12 questionnaires by mail or telephone. Characteristics and outcomes data were extracted from medical records and compared between participants and nonparticipants. Response rate (RR) was calculated using guidelines of the American Association for Public Opinion Research (AAPOR). The association between nonparticipation and outcomes was examined by Cox proportional hazards regression for death and Andersen-Gill modeling for hospitalizations. Results: Among 7920 patients, 3438 responded to the survey (AAPOR RR#2= 43%). Numerous clinical and demographic differences between participants and non-participants were noted (Table), particularly for education, marital status, and neuropsychiatric conditions. After a mean (±SD) of 1.5±1 years after survey administration, 1,577 deaths and 5,873 hospitalizations had occurred. Nonparticipation was associated with a two-fold increased risk of death (HR: 2.30; 95% CI: 2.06-2.57; p<0.001) and a 10% increased risk of hospitalizations (HR: 1.10; 95% CI: 1.01-1.21; p=0.03) after adjusting for age, sex, marital status, coronary disease, arrhythmia, hyperlipidemia, cancer, chronic kidney disease, depression and anxiety. Conclusions: In a large survey of patients with HF, participation was associated with large differences in clinical and demographic characteristics and outcomes. Examining the impact of participation is critical to draw inference from studies of patient reported measures.
Abstract P157: Association of Rurality With Death in Patients With Heart Failure: a Community Study
Background: Previous studies have indicated that living in a rural or non-urban area may be associated with poor health outcomes. However, data on rurality and death in heart failure (HF) are scarce. Methods: Residents from 11 southeast MN counties with a first-ever code for HF (including codes ICD-9 428 and ICD-10 I50) between 1/1/2013 and 12/31/2016 were identified. Resident address was geo-coded and classified according to the Rural-Urban Commuting Area (RUCA) codes, which classifies US census tracts to measure population density, urbanization and daily commuting. Rurality was defined as living in a non-metropolitan area. Cox proportional hazards regression was used to determine the association between living in a rural vs. urban area and death. Results: Among 6,996 patients (mean age 73 years, 52% male), 54% of patients lived in a rural area. These patients were older and had a lower level of educational attainment and comorbidity burden (p<0.001). After a mean (SD) follow-up of 2.9 (1.3) years, 1,856 deaths occurred. Living in a rural area was univariately associated with a higher risk of death (HR 1.20, 95% CI: 1.09-1.31; Table). After adjustment for age, sex, education status and comorbidity burden, rurality remained associated with an increased risk of death (HR 1.15; 95% CI: 1.04-1.27). Conclusions: Among patients with HF, living in a rural area is associated with an increased risk of death. Further study to identify and address the mechanisms through which rural residence influences mortality in patients with HF is needed.
Abstract MP17: Comorbidity Type and Risk of Hospitalization and Death in Patients With Atrial Fibrillation
Background: Multimorbidity is common in atrial fibrillation (AF); however, the impact of the number and type of comorbid conditions on death and hospitalizations is uncertain. Methods: The prevalence of 17 chronic conditions was obtained in 1430 patients with incident AF from 2000-2010 from Olmsted County, MN. Chronic conditions were ascertained electronically prior to AF and were classified into 3 groups: cardiovascular (CV), other physical, and mental. All hospitalizations and deaths were obtained through 12/31/2014. Associations of the number and type of condition and each individual condition with hospitalizations and death were determined using Andersen-Gill and Cox regression, respectively. Results: Among the 1430 patients with AF (median age 76 years, 48.6% men), the mean (SD) number of chronic conditions was 4.7 (2.7). A total of 4496 hospitalizations and 812 deaths occurred over a mean (SD) follow-up of 5.4 (4.1) years. An increase in the number of conditions of each type was associated with increased risks of death and hospitalizations (Table). Mental conditions (which included depression, anxiety, dementia, schizophrenia, and substance abuse) exhibited the strongest association with death, whereas other physical conditions exhibited the strongest association with hospitalizations. Individual predictors of death included heart failure (HF), hypertension, chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD), depression, dementia, and substance abuse. Predictors of hospitalizations included HF, coronary artery disease, diabetes, COPD, CKD, arthritis, osteoporosis, and substance abuse. Conclusions: Patients with AF have many comorbid conditions which are associated with death and hospitalizations. Although conditions of each type were associated with outcomes, mental conditions exhibited strongest association with death. These data highlight the importance of management of not only CV comorbidities but other physical and mental comorbidities in patients with AF.
Fall Risk and Outcomes Among Patients Hospitalized With Cardiovascular Disease in the Community
Background As the population with cardiovascular disease ages, geriatric conditions are of increasing relevance. A possible geriatric prognostic indicator may be a fall risk score, which is mandated by The Joint Commission to be measured on all hospitalized patients. The prognostic value of a fall risk score on outcomes after dismissal is not well known. Thus, we aimed to determine whether a fall risk score is associated with death and hospital readmissions in patients with a recent incident cardiovascular disease event. Methods and Results In this retrospective cohort study, Olmsted County, MN patients with incident heart failure, myocardial infarction, or atrial fibrillation between August 1, 2005, and December 31, 2011, who were hospitalized within 180 days after the event were studied. Fall risk was measured by the Hendrich II fall risk model. Patients were followed for death or readmission within 30 days or 1 year. Among 2456 hospitalized patients with recent incident cardiovascular disease (549 heart failure, 784 myocardial infarction, 1123 atrial fibrillation; mean [SD] age, 71 [15] years; 55% men), the fall risk score was high in 22% of patients and moderate in 38%. The risk of death was increased if the fall risk score was increased, independent of age and comorbidities (moderate hazard ratio, 1.51; 95% CI, 1.09–2.08; high hazard ratio, 3.49; 95% CI, 2.52–4.85). Similarly, the risk of 30-day readmissions was substantially increased with a greater fall risk score (moderate hazard ratio, 1.29; 95% CI, 1.03–1.62; high hazard ratio, 1.63; 95% CI, 1.23–2.15). Results were similar for readmissions within 1 year. Conclusions More than half of hospitalized patients with recent incident cardiovascular disease have an elevated fall risk score, which is associated with an increased risk in readmissions and death. These results delineate an approach for risk stratification and management that may prevent readmissions and improve survival.
Perceived Social Isolation and Outcomes in Patients With Heart Failure
Background Perceived social isolation has been shown to have a negative impact on health outcomes, particularly among older adults. However, these relationships have not been fully examined among patients with heart failure. Methods and Results Residents from 11 southeast Minnesota counties with a first‐ever International Classification of Diseases, Ninth Revision ( ICD‐9 ) code 428 for heart failure between January 1, 2013, and March 31, 2015 (N=3867), were prospectively surveyed to measure perceived social isolation. A total of 2003 patients returned the survey (response rate, 52%); 1681 patients completed all questions and were retained for analysis. Among these patients (53% men; mean age, 73 years), ≈19% (n=312) had moderate perceived social isolation and 6% (n=108) had high perceived social isolation. After adjustment, patients reporting moderate perceived social isolation did not have an increased risk of death, hospitalizations, or emergency department visits compared with patients reporting low perceived social isolation; however, patients reporting high perceived social isolation had >3.5 times increased risk of death (hazard ratio, 3.74; 95% confidence interval [ CI ], 1.82–7.70), 68% increased risk of hospitalization (hazard ratio, 1.68; 95% CI , 1.18–2.39), and 57% increased risk of emergency department visits (hazard ratio, 1.57; 95% CI , 1.09–2.27). Compared with patients who self‐reported low perceived social isolation, patients reporting moderate perceived social isolation had a 16% increased risk of outpatient visits (rate ratio, 1.16; 95% CI , 1.03–1.31), whereas those reporting high perceived social isolation had a 26% increased risk (rate ratio, 1.26; 95% CI , 1.04–1.53). Conclusions In patients with heart failure, greater perceived social isolation is associated with an increased risk of death and healthcare use. Assessing perceived social isolation during the clinical encounter with a brief screening tool may help identify patients with heart failure at greater risk of poor outcomes.
Multimorbidity and Functional Limitation in Individuals with Heart Failure: A Prospective Community Study
Objectives To characterize the individual and combined effects of multimorbidity and functional limitation on healthcare use and mortality in a large, community cohort of individuals with heart failure (HF). Design Prospective cohort study. Setting Eleven southeastern Minnesota counties. Participants Individuals (mean age 74, 54% male) with a first‐ever HF code ( International Classification of Diseases, Ninth Revision code 428 or Tenth Revision code I50) between January 1, 2013 and March 31, 2016 (N=2,692). Measurements Eight activities of daily living measured using a survey on a Likert scale (1=without any difficulty, 5=unable to do; median=8). Participants with a score greater than 8 were categorized as having functional limitation. Multimorbidity was defined as having 2 or more noncardiac comorbidities. Results Twenty‐five percent of participants had neither multimorbidity nor functional limitation, 35% had multimorbidity, 9% had functional limitation, and 31% had both. After adjustment, participants with multimorbidity and functional limitation had greater risks of all outcomes (death: hazard ratio (HR)=4.92, 95% confidence interval (CI)=3.03–8.00; emergency department (ED) visit: HR=3.67, 95% CI=2.94–4.59; hospitalization: HR=3.66, 95% CI=2.85–4.70; outpatient visit: HR=1.73, 95% CI=1.52–1.96) than those with neither. Participants with functional limitation alone had greater risks of death (HR=4.84, 95% CI=2.78–8.43), ED visits (HR=2.35, 95% CI=1.75–3.16), and hospitalizations (HR=2.10, 95% CI=1.52–2.88) but not outpatient visits. Those with multimorbidity alone had similar risks of ED visits and hospitalizations as those with functional limitation alone but were more likely to have outpatient visits (HR=1.50, 95% CI=1.34–1.67). Conclusion Individuals with both multimorbidity and functional limitation have the highest risk of death and healthcare use. Individuals with only functional limitation have similar rates of hospitalizations and ED visits as those with only multimorbidity, underscoring the need to consider both when managing individuals with HF.
Contemporary Risk Stratification After Myocardial Infarction in the Community: Performance of Scores and Incremental Value of Soluble Suppression of Tumorigenicity‐2
Background Current American Heart Association/American College of Cardiology guidelines recommend the GRACE (Global Registry of Acute Coronary Events) and TIMI (Thrombolysis in Myocardial Infarction) scores to assess myocardial infarction ( MI ) prognosis. Changes in the epidemiological characteristics of MI and the availability of new biomarkers warrant an assessment of the performance of these scores in contemporary practice. We assessed the following: (1) the performance of GRACE and TIMI to predict 1‐year mortality in a cohort of patients stratified by ST ‐segment elevation MI (STEMI) and non‐STEMI ( NSTEMI ) and (2) the incremental discriminatory power of soluble suppression of tumorigenicity‐2, a myocardial fibrosis biomarker. Methods and Results Olmsted County, Minnesota, residents with incident MI (N=1401) were recruited prospectively from November 1, 2002 to December 31, 2012 (mean age, 67 years; 61% men; 79% with NSTEMI ). Baseline data were used to calculate risk scores; soluble suppression of tumorigenicity‐2 was measured in stored plasma samples obtained at index MI . C ‐statistics adapted to survival data were used to assess the discriminatory power of the risk scores and the improvement gained by adding other markers. During the first year of follow‐up, 190 patients (14%) died. The discriminatory performance to predict death was reasonable for GRACE and poor for TIMI , and was generally worse in those with NSTEMI versus those with STEMI. In people with NSTEMI , sequential addition of comorbidities and soluble suppression of tumorigenicity‐2 substantially improved the c ‐statistic over GRACE (from 0.78 to 0.80 to 0.84) and TIMI (from 0.61 to 0.73 to 0.81), respectively (all P ≤0.05). Conclusions Guideline‐recommended scores for risk assessment after MI underperform in contemporary community patients, particularly those with NSTEMI, which now represents most infarcts. Incorporating comorbidities and soluble suppression of tumorigenicity‐2 substantially improves risk prediction, thereby delineating opportunities to improve clinical care.
Multimorbidity in Heart Failure: Effect on Outcomes
Objectives To investigate the effect of the number and type of comorbid conditions on death and hospitalizations in individuals with incident heart failure ( HF ). Design Population‐based cohort study. Setting Olmsted County, Minnesota. Participants Olmsted County, Minnesota, residents with incident HF from 2000 to 2010 (mean age 76 ± 14, 56% female) (N = 1,714). Measurements The prevalence of 16 chronic conditions obtained at HF diagnosis classified into three groups: cardiovascular ( CV ) related, other physical, and mental. Results The mean number of conditions per participant was 2.6 ± 1.5 for CV ‐related conditions, 1.3 ± 1.1 for other physical conditions, and 0.30 ± 0.61 for mental conditions. After a mean follow‐up of 4.2 years, 1,073 deaths and 6,306 hospitalizations had occurred. After adjustment for age, sex, ejection fraction, in‐ or outpatient status, and number of other conditions, an increase of one other physical condition was associated with a 14% ( HR = 1.14, 95% CI = 1.08–1.20) greater risk of death and a 26% ( HR = 1.26, 95% CI = 1.20–1.32) greater risk of hospitalization, and an increase of one mental condition was associated with a 31% ( HR = 1.31, 95% CI = 1.19–1.44) greater risk of death and an 18% ( HR = 1.18, 95% CI = 1.07–1.29) greater risk of hospitalization. In contrast, an increase of one CV ‐related condition was not associated with greater risk of death and was associated with a 10% ( HR = 1.10, 95% CI = 1.06–1.15) greater risk of hospitalization. Conclusion CV ‐related conditions are the most common type of comorbid conditions in individuals with HF , but other physical and mental conditions are more strongly associated with death and hospitalizations. This underscores the effect of non‐ CV conditions on outcomes in HF .