Manemann, Sheila M.

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.

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.

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.

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.

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 .

Objective The goal of this study was to identify distinct frailty trajectories (clusters of individuals following a similar progression of frailty over time) in an ageing population and to determine social and behavioural factors associated with frailty trajectories. Design Population-based cohort study. Setting Olmsted County, Minnesota. Participants Olmsted County, Minnesota residents aged 60–89 in 2005. Primary outcome measure Changes in frailty over an 8-year period from 2005 to 2012, measured by constructing a yearly frailty index. Frailty trajectories by decade of age were determined using k-means cluster modelling for longitudinal data. Results After adjustment for age and sex, all social and behavioural factors (education, marital status, living arrangements, smoking status and alcohol use) were significantly associated with frailty trajectories in those aged 60–69 and 70–79 years. After further adjustment for baseline frailty, the likelihood of being in the high frailty trajectory was greatest among those reporting concerns from relatives/friends about alcohol consumption (OR (95% CI) 2.26 (1.19 to 4.29)) and those with less than a high school education (OR (95% CI) 1.98 (1.32 to 2.96)) in the 60–69 year olds. In the 70–79 year olds, the largest associations were observed among those with concerns from oneself about alcohol consumption (OR (95% CI) 1.92 (1.23 to 3.00)), those with less than a high school education (OR (95% CI) 1.57 (1.12 to 2.22)), and those living with family (vs spouse; OR (95% CI) 1.76 (1.05 to 2.94)). No factors remained associated with frailty trajectories in the 80–89 year olds after adjustment for baseline frailty. Conclusions Social and behavioural factors are associated with frailty, with stronger associations observed in younger ages. Recognition of social and behavioural factors associated with increasing frailty may inform interventions for individuals at risk of worsening frailty, specifically when targeted at younger individuals.

Objectives To identify distinct frailty trajectories (clusters of individuals following a similar progression of frailty over time) in an aging population and to estimate associations between frailty trajectories and emergency department visits, hospitalizations, and all‐cause mortality. Design Population‐based cohort study. Setting Olmsted County, Minnesota. Participants Olmsted County, Minnesota residents aged 60–89 in 2005. Measurements Longitudinal changes in frailty between 2005 and 2012 were measured by constructing a yearly Rockwood frailty index incorporating body mass index, 17 comorbidities, and 14 activities of daily living. The frailty index measures variation in health status as the proportion of deficits present of the 32 considered (range 0–1). Results Of the 16,443 Olmsted County residents aged 60–89 in 2005, 12,270 (74.6%) had at least 3 years of frailty index measures and were retained for analysis. The median baseline frailty index increased with age (0.11 for 60–69, 0.14 for 70–79, 0.19 for 80–89). Three distinct frailty trajectories were identified in individuals aged 60–69 at baseline and two trajectories in those aged 70–79 and 80–89. Within each decade of age, increasing frailty trajectories were associated with greater risks of emergency department visits, hospitalization, and all‐cause mortality, even after adjustment for baseline frailty index. Conclusion The number of frailty trajectories differed according to age. Within each age group, those in the highest frailty trajectory had greater healthcare use and worse survival. Frailty trajectories may offer a way to target aging individuals at high risk of hospitalization or death for therapeutic or preventive interventions.

Background— Contemporary data are lacking on the prognostic importance of heart failure (HF) after myocardial infarction (MI). We evaluated the prognostic impact of HF post MI according to preserved/reduced ejection fraction and the timing of its occurrence. Methods and Results— All Olmsted County, Minnesota, residents (n=2596) with incident MI diagnosed in 1990 to 2010 and no prior HF were followed through March 2013. Cox models were used to examine (1) the hazard ratios for death associated with HF type and timing and (2) secular trends in survival by HF status. During a mean follow-up of 7.6 years, there were 1116 deaths, 634 in the 902 patients who developed HF (70%) and 482 in the 1694 patients who did not develop HF (28%). After adjustment for age and sex, HF as a time-dependent variable was strongly associated with mortality (hazard ratio =3.31, 95% confidence interval: 2.93–3.75), particularly from cardiovascular causes (hazard ratio =4.20, 95% confidence interval: 3.50–5.03). Further adjustment for MI severity and comorbidity, acute treatment, and recurrent MI moderately attenuated these associations (hazard ratio =2.49 and 2.94 for all-cause and cardiovascular mortality, respectively). Mortality did not differ by ejection fraction, but was higher for delayed- versus early-onset HF ( P for heterogeneity =0.002). The age- and sex-adjusted 5-year survival estimates in 2001 to 2010 versus 1990 to 2000 were 82% and 81% among HF-free and 61% and 54% among HF patients, respectively ( P for heterogeneity of trends =0.05). Conclusions— HF markedly increases the risk of death after MI. This excess risk is similar regardless of ejection fraction but greater for delayed- versus early-onset HF. Mortality after MI declined over time, primarily as a result of improved HF survival.