Roger, Véronique L.

Introduction: Chronic kidney disease affects nearly half of heart failure (HF) patients, underscoring the importance of regular kidney function monitoring. However, longitudinal trajectories of kidney function in HF are not well characterized. Identifying clinical factors linked to long-term changes is critical for improving monitoring and informing early clinical decisions. Hypothesis: We hypothesized that longitudinal kidney function and its associations with clinical variables in HF patients differ from that of demographically similar comparators from the same community. Methods: We analyzed patients with validated HF from a community-based cohort and comparators individually matched to age and sex selected from participants in the Mayo Clinic Biobank cohort. Individuals with end-stage kidney disease, dialysis or kidney transplantation prior to enrollment were excluded. Serum creatinine-based estimated glomerular filtration rate (eGFR) from outpatient and inpatient visits was assessed from enrollment for up to 10 years of follow-up. The median of eGFR for 90-day intervals was used to estimate the follow-up eGFR (Figure 1) . We modeled percentage change from baseline and fit linear mixed-effect models with time, HF status, and their interaction to test whether the eGFR trajectories differed between the two groups. In addition, we examined the association between eGFR trajectories and clinical variables. Results: We studied 1182 HF patients and 825 comparators with at least three eGFR measurements. Median follow-up was 5 years (IQR: 3-10) for HF patients and 8 years (6-9) for comparators. In total, 16245 serum creatinine measurements from HF patients and 9858 from comparators were analyzed. Median age at enrollment was 76 years (67-84) for HF patients and 78 years (70-83) for comparators. A greater decline in percentage change in eGFR was observed in HF patients (-4.23%, 95% CI: -4.75 to -3.70% per year) than in comparators (-1.90%, 95% CI: -2.51 to -1.29% per year; P<0.001, Figure 2 ). Among HF patients, the decline in percentage change in eGFR was greater in the presence of diabetes, hyperlipidemia, or a higher comorbidity burden. Conclusions: In this community study, HF patients exhibited a greater percentage decline in eGFR compared to community comparators. Among HF patients, eGFR decline was more strongly associated with comorbidities—particularly metabolic risk factors—highlighting the relevance of the cardiovascular-kidney-metabolic syndrome in HF.

Background Multimorbidity is common in patients with atrial fibrillation (AF); however, the impact of the number and type of comorbid conditions on outcomes remains uncertain. Methods This cohort study included patients with new‐onset AF from a Midwest region between 2013 and 2017. Eighteen chronic conditions at the time of AF were classified into groups: cardiometabolic, other somatic, and mental health. Cox regression determined associations between the number of each condition type with death, ischemic stroke/transient ischemic attack, and congestive heart failure, stratified by age. Results Among 16 509 patients with AF (mean age, 74 years; 43% women), the mean number of cardiometabolic, other somatic, and mental health conditions was 2.7, 1.4, and 0.5, respectively. The number and type of conditions had a varying impact on outcomes and differed by age. A higher number of cardiometabolic conditions were associated with increased risk of death within 90 days only in people aged ≥85 years (≥4 conditions versus 0: hazard ratio [HR], 1.74 [95% CI, 1.05–2.87]), whereas for death after 90 days, associations were strongest in the youngest age group (<65 years: HR, 1.83 [95% CI, 1.35–2.46]; 65–74 years: HR, 1.34 [95% CI, 1.04–1.73]; 75–84 years: HR, 1.32 [95% CI, 1.09–1.60]; ≥85 years: HR, 1.14 [95% CI, 0.96–1.35]). Associations with outcomes were generally strongest in the youngest age group and attenuated with older age for higher number of other somatic conditions, whereas the pattern was less consistent for mental health conditions. Conclusions Along with cardiometabolic‐related conditions, other somatic and mental health conditions are important predictors of outcomes in AF, with effects differing by age, and should be considered when caring for these patients.

Hypertension is the single most important modifiable risk factor for preventable disability and death worldwide and disproportionately affects socially disadvantaged populations. We face a paradox—blood pressure control is low and recent trends suggest it is even declining, despite the availability of inexpensive and effective therapies. A variety of barriers on the system, patient, and healthcare provider side hinder effective drug-based risk factor management. Clinical inertia represents a major barrier on the clinician side, as well as workload and limited education. Common barriers on the patient side include limited English proficiency, low health literacy, and nonadherence with misaligned incentives, limited resources, lack of structured clinical pathways, and reimbursement issues. New innovations in the field of RNA-targeted therapies and device-based interventions could prevent and potentially even cure diseases previously designated as chronic health conditions, such as hypertension. Such novel therapies could potentially overcome several major barriers to effective treatment, including nonadherence. Drug development of novel, long-acting treatments requires consideration of specific clinical trial design aspects, including safety collection, benefit: risk assessment, the development and assessment of novel, qualitative surrogate end points, such as time-in-therapeutic range, the use of representative trial settings as well as the definition of standard of care in placebo-controlled trials, which should be of reasonably high-quality allowing for credible evaluation of effectiveness. Here, we provide an overview on barriers to effective treatment and a framework for trials assessing novel treatments for cardiovascular disease risk factors, including early and broad implementation programs.

BACKGROUND: Heart failure (HF) is a heterogeneous syndrome with high mortality. The need for a new taxonomy of HF is recognized; up to now, such phenomapping efforts have primarily used clinical data. Proteomics offers potential for more precise phenotypic identification and mechanistic insights. However, few phenomapping studies have used this approach, and all have focused on targeted cardiovascular proteomics panels and a restricted HF ejection fraction group. METHODS: We measured over 7000 plasma proteins in a population-based cohort of 1351 patients with HF, used k-means clustering to identify distinct phenogroups, and compared their clinical characteristics and all-cause mortality. RESULTS: Three proteomics-defined phenogroups were identified, with substantial differences in survival (phenogroup 1 5-year survival probability, 65% [95% CI, 61%–68%]; phenogroup 2, 45% [40%–51%]; phenogroup 3, 26% [22%–30%]), independent of clinical characteristics. Phenogroups also exhibited differences in several measures suggesting poorer health, including NT-proBNP (N-terminal pro-B-type natriuretic peptide), kidney function, and Meta-Analysis Global Group in Chronic Heart Failure scores, but did not differ by ejection fraction or New York Heart Association class. CONCLUSIONS: Our study demonstrates that molecular phenomapping can stratify patients with HF into distinct subgroups that go beyond predefined clinical classifications.

Background Multimorbidity is common in patients with atrial fibrillation (AF), yet comorbidity patterns are not well documented. Methods The prevalence of 18 chronic conditions (6 cardiometabolic, 7 other somatic, 5 mental health) was obtained in patients with new-onset AF from 2013-2017 from a 27-county region and controls matched 1:1 on age, sex, and county of residence. For AF patients and controls separately, clustering of conditions and co-occurrence beyond chance was estimated (using the asymmetric Somers’ D statistic), overall and for ages <65, 65-74, 75-84, and ≥85 years. Results Among 16,509 patients with AF (median age 76 years, 57% men), few (4%) did not have any of the 18 chronic conditions, whereas nearly one-quarter of controls (23%) did not have any chronic conditions. Clustering of cardiometabolic conditions was common in both AF patients and controls, but clustering of other somatic conditions was more common in AF. Although the prevalence of most condition pairs was higher in AF patients, controls had a larger number of condition pairs occurring together beyond chance. In persons aged <65 years, AF patients more frequently exhibited concordance of condition pairs that included either pairs of somatic conditions or a combination of conditions from different condition groups. In persons aged 65-74 years, AF patients more frequently had pairs of other somatic conditions. Conclusion Patterns of co-existing conditions differed between patients with AF and controls, particularly in younger ages. A better understanding of the clinical consequences of multimorbidity in AF patients, including those diagnosed at younger ages, is needed.

Background: Heart failure (HF) is a heterogeneous syndrome with high mortality. Previous work characterizing HF subgroups primarily relied on clinical data to cluster patients, an approach constrained by the boundaries of documented clinical features. Clustering based on biomarker data, such as proteomics, may provide insights into underlying molecular processes. However, few studies have used this approach, and all used targeted cardiovascular proteomics panels and a restricted HF ejection fraction group. Hypothesis: We used unsupervised clustering analysis to characterize molecular phenogroups in a population-based HF cohort using a large-scale array of circulating plasma proteins. We hypothesized that distinct proteomic-defined phenogroups would exhibit differences in clinical characteristics, mortality, and protein expression. Methods: We measured 7151 SOMAmers (Slow off-rate modified aptamers) targeting human proteins via the SomaLogic 7K SomaScan assay in 1351 HF patients. After feature selection, 831 SOMAmers were used in k-means clustering of patients via R package “ConsensusClusterPlus.” Phenogroups were compared for clinical characteristics, all-cause mortality, and protein expression. Results: Three phenogroups were identified, exhibiting different clinical characteristics ( Table 1 ) and survival probabilities (5-year survival probability in phenogroup 1: 65% [61%, 68%], phenogroup 2: 45% [40%, 51%], and phenogroup 3: 26% [22%, 30%]). In covariate-adjusted Cox models, membership in phenogroups 2 and 3 was significantly associated with increased rate of mortality compared to phenogroup 1. Phenogroups did not differ by ejection fraction or New York Heart Association class. Pathway overrepresentation analysis of differentially expressed SOMAmers identified pathways associated with inflammatory response and immune cell trafficking. Conclusions: Unsupervised clustering analysis using large-scale proteomics data identified three HF phenogroups with different proteomic signatures, clinical characteristics, and outcomes. Future work is necessary to elucidate how molecular differences contribute to heterogeneity in HF to improve risk stratification beyond current recommended clinical guidelines.

Objectives: To assess compliance with chronic coronary artery disease (CAD) secondary prevention guidelines in the USA, to determine time trends, and to identify potential sociodemographic predictors of low compliance. Design, Setting and Participants: We analyzed the National Health and Nutrition Examination Survey (NHANES) data from 1999 to 2010, representative of non-institutionalized civilian population in the USA. We included people with self-reported previous diagnosis of CAD, angina or myocardial infarction (MI). Primary Outcome: Adherence to secondary prevention guidelines including blood pressure control, lipid control, not smoking, normal body mass index, physical activity at goal, and meeting all 5 outcomes (“all-or-none”). Use of antiplatelet therapy was reported and analyzed from 1999-2004. Secondary Outcome: Use of beta-blocker therapy in people with history of MI; in diabetes (DM), use of ACE-inhibitors or angiotensin receptor blocker, and HgbA1C <7%. Age, gender, race, income, education and insurance status were evaluated as covariates. Analyses were weighed according to Center for Disease Control guidelines. Results: There were 62,160 individuals in the cycle data of which 2,615 comprised the study group, representative of 73,574,548 individuals in the USA. Mean age was 65 yr, 58% men, 79% white. Only 2.8% of people with CAD met all 5 main outcomes. Only blood pressure and LDL control showed significant improvement over time, see Figure. Antiplatelet therapy was reported in 58.2%. Of those with history of MI, only 50.5% were on a beta-blocker and of those with history of DM, 59.4% were using either an ACE-I or an ARB; and 54% had a HgbA1C less than 7%. When adjusting for demographics, no significant differences were found regarding compliance with all 5 main outcomes. Conclusions: Adherence to guidelines for secondary prevention of CAD is suboptimal. There is an immense opportunity for improvement in secondary prevention for CAD in the USA.

Background: Epidemiologic studies have demonstrated that the incidence of heart failure varies by race and ethnicity, with the highest incidence occurring in blacks. However, whether these racial and ethnic variations extend to commercially insured populations and whether differences in early outcomes after diagnosis exist requires further exploration. Methods: We utilized administrative claims data from a large U.S. commercial insurance database to retrospectively identify privately insured and Medicare Advantage patients who were diagnosed with heart failure between 2006 and 2014. Published claims-based algorithms were used to identify patients with incident HF and categorize reasons for hospitalization after diagnosis. Results: Among 148,827 patients with incident heart failure (mean age 72.2 years, 51% women), 70% were white, 15% black, 6% Hispanic, 3% Asian and 6% had unknown race/ ethnicity. The incidence of heart failure during the study period was 3.7 per 1000 person-years and was highest among blacks, followed by whites, Hispanics and Asians (9.9, 3.6, 2.5, and 2.0 per 1000 person-years, respectively). In total, 37% of patients were hospitalized at least once in the first year after diagnosis for a total of 93,358 hospitalizations. HF was the most common reason for hospitalization (13% of all hospitalizations), followed by arrhythmia (5%), sepsis (5%), pneumonia (4%), COPD (3%) and acute renal failure (3%). Reasons for hospitalization were similar across racial and ethnic groups. The rate of hospitalizations was highest the first month after diagnosis and then gradually declined. Black patients had the highest rates of hospitalization, while Asians had the lowest (Figure). Conclusions: Even among a commercially insured population that likely have fewer barriers to care, black patients had a higher incidence of HF and higher rates of hospitalization after initial diagnosis compared with other racial and ethnic groups.

Introduction: Soluble ST2 (sST2) is a serum marker of cardiomyocyte stress associated with a large risk of death and heart failure after myocardial infarction (MI). The relationship between sST2 and cardiac structure and function after MI however remains incompletely defined, and greater characterization is required prior to clinical application. Methods: Olmsted County, Minnesota residents who experienced their first MI between 2007 and 2012 were prospectively recruited. MIs were validated using standardized criteria and patients underwent simultaneous comprehensive Doppler echocardiography and sST2 measurement. The association between cardiac morphology and hemodynamics and sST2 were examined. Published normal values were used as referent ranges for sST2 levels. Results: Among 316 patients (mean age 65 [SD 14] years, 67% men, 32% ST-elevation MI), sST2 was measured 2.5 [SD 1.6] days after MI and within 0.7 [SD 2.3] days of echocardiography. Soluble ST2 was elevated in 33% of patients and univariately associated with decreased LV ejection fraction (LVEF), increased LV mass, impaired LV diastolic function and increased pulmonary artery pressure (ePAP) (Table). After adjustment for age, sex, LVEF and key measures of LV filling pressures, elevated sST2 was independently associated with reduced LVEF (p=0.01) mitral valve deceleration time (p=0.03), greater left atrial volume (p=0.03) and mitral regurgitation (≥mild; p=0.09). LVEF and ePAP exhibited the strongest associations with elevated sST2 (both p<0.001). Conclusions: Soluble ST2 is frequently elevated following MI and is strongly associated with the morphologic and hemodynamic determinants of adverse LV remodeling that infer poor long-term outcome after MI.

Background: Depression is prevalent in adults with cardiovascular disease; however, the association between depression and death in older adults treated with percutaneous coronary intervention (PCI) is not known. Method: We prospectively studied 596 patients 65 years of age or older undergoing PCI at Mayo Clinic (Rochester, MN and Franciscan Skemp Hospital in La Crosse, WI) from October 2005 through September 2008. Depression was assessed using the validated and reliable Center for Epidemiological Studies Depression (CES-D) scale. Patients were categorized into groups by depression symptom severity: none/mild (CES-D <16; referent), moderate (CES-D 16-21), or moderate/severe (CES-D>21). Patients were followed annually for death. Results: Mean age of patients was 75.0±6.4 years; 31% were women, 98.0% were white. There were 461 patients (77.3%) that were not depressed and 135 patients (22.7%) that were depressed; 67 patients (11.3%) had moderate depressive scores (CES-D 16-21) and 68 patients (11.4%) had moderate/severe scores (CES-D >21). Groups were similar with respect to baseline characteristics. After a median follow-up of 36 months, there were 74 deaths, and patients with moderate/severe depressive symptom scores had a higher cumulative incidence of mortality (p = 0.036 by log-rank) (Figure). In multivariable analysis, CES-D score >21 was independently predictive of all-cause mortality (HR 1.90; 95% CI 1.02-3.53; p = 0.043), along with other covariates, including age (HR 1.88; 95% CI 1.31-2.68), comorbidity (Charlson Index) (HR 1.08; 95% CI 1.02-1.15), and diabetes mellitus (HR 2.04; 95% CI 1.26-3.30). Conclusion: Over one-fifth of older adults undergoing PCI met criteria for depression and those with high depressive scores reflecting greater self-perceived depressive symptoms had worse survival. Recognition of depressive symptoms in older adults treated with PCI identifies a cohort at higher risk of adverse outcomes.