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In the past 2 decades, health care has witnessed technological and pharmacological advancements leading to innovations in diabetes management. Despite these advances, published guidelines, and treatment algorithms, most people with diabetes remain above glycemic targets. Thus, the authors designed a novel care model aimed at improving several causative factors, including therapeutic inertia, limited access to endocrinology and cardiovascular specialists, time constraints, and complexity in incorporating clinical practice guidelines. The model involves collaboration between the diabetes specialty team and primary care providers (PCPs). The intervention reviewed uncontrolled diabetes data and the patient's electronic medical record (EMR) and sent personalized, evidence-based recommendations to the provider using the task function in the EMR. Other services (eg, diabetes education) were utilized to optimize patient care to achieve optimal glycemic targets and address cardiometabolic risk. The overall mean hemoglobin A1c (HbA1c) decreased pre-post intervention by almost 1%, and 52.1% (347 of 666) of the cohort had ≥−0.5% change in HbA1c post-intervention. All pathways exhibited a decrease in HbA1c. Team-based approaches to managing diabetes patient care were the most effective. The interventions effectively utilized the resources across the health system without placing additional load or burden on primary care or diabetes specialty care teams. In the future, the authors hope to address the limitations of the current gap caused by increasing diabetes numbers, decreasing availability of PCPs and endocrinologists, and fee-for-service models using the innovative specialty consultant–primary care connection and knowledge exchange offered by this novel model, which can only be sustained with payer's support. [ABSTRACT FROM AUTHOR]

Background: Obesity and diabetes are associated with a higher risk of heart failure (HF). The interrelationships between different measures of adiposity-overall obesity, central obesity, fat mass (FM)-and diabetes status for HF risk are not well-established.Methods: Participant-level data from the ARIC study (Atherosclerosis Risk in Communities; visit 5) and the CHS (Cardiovascular Health Study; visit 1) cohorts were obtained from the National Heart, Lung, and Blood Institute Biologic Specimen and Data Repository Information Coordinating Center, harmonized, and pooled for the present analysis, excluding individuals with prevalent HF. FM was estimated in all participants using established anthropometric prediction equations additionally validated using the bioelectrical impedance-based FM in the ARIC subgroup. Incident HF events on follow-up were captured across both cohorts using similar adjudication methods. Multivariable-adjusted Fine-Gray models were created to evaluate the associations of body mass index (BMI), waist circumference (WC), and FM with risk of HF in the overall cohort as well as among those with versus without diabetes at baseline. The population attributable risk of overall obesity (BMI≥30 kg/m2), abdominal obesity (WC>88 and 102 cm in women and men, respectively), and high FM (above sex-specific median) for incident HF was evaluated among participants with and without diabetes.Results: The study included 10 387 participants (52.9% ARIC; 25.1% diabetes; median age, 74 years). The correlation between predicted and bioelectrical impedance-based FM was high (R2=0.90; n=5038). During a 5-year follow-up, 447 participants developed HF (4.3%). Higher levels of each adiposity measure were significantly associated with higher HF risk (hazard ratio [95% CI] per 1 SD higher BMI=1.15 [1.05, 1.27], WC=1.22 [1.10, 1.36]; FM=1.13 [1.02, 1.25]). A significant interaction was noted between diabetes status and measures of BMI (P interaction=0.04) and WC (P interaction=0.004) for the risk of HF. In stratified analysis, higher measures of each adiposity parameter were significantly associated with higher HF risk in individuals with diabetes (hazard ratio [95% CI] per 1 SD higher BMI=1.29 [1.14-1.47]; WC=1.48 [1.29-1.70]; FM=1.25 [1.09-1.43]) but not those without diabetes, including participants with prediabetes and euglycemia. The population attributable risk percentage of overall obesity, abdominal obesity, and high FM for incident HF was higher among participants with diabetes (12.8%, 29.9%, and 13.7%, respectively) versus those without diabetes (≤1% for each).Conclusions: Higher BMI, WC, and FM are strongly associated with greater risk of HF among older adults, particularly among those with prevalent diabetes. [ABSTRACT FROM AUTHOR]

Obesity is a recognized public health epidemic with a prevalence that continues to increase dramatically in nearly all populations, impeding progress in reducing incidence rates of cardiovascular disease. Over the past decade, obesity science has evolved to improve knowledge of its multifactorial causes, identifying important biological causes and sociological determinants of obesity. Treatments for obesity have also continued to develop, with more evidence-based programs for lifestyle modification, new pharmacotherapies, and robust data to support bariatric surgery. Despite these advancements, there continues to be a substantial gap between the scientific evidence and the implementation of research into clinical practice for effective obesity management. Addressing barriers to obesity science implementation requires adopting feasible methodologies and targeting multiple levels (eg, clinician, community, system, policy) to facilitate the delivery of obesity-targeted therapies and maximize the effectiveness of guideline-driven care to at-need patient populations. This scientific statement (1) describes strategies shown to be effective or promising for enhancing translation and clinical application of obesity-based research; (2) identifies key gaps in the implementation of obesity science into clinical practice; and (3) provides guidance and resources for health care professionals, health care systems, and other stakeholders to promote broader implementation and uptake of obesity science for improved population-level obesity management. In addition, advances in implementation science that hold promise to bridge the know-do gap in obesity prevention and treatment are discussed. Last, this scientific statement highlights implications for health research policy and future research to improve patient care models and optimize the delivery and sustainability of equitable obesity-related care.

Cardiovascular-kidney-metabolic (CKM) syndrome is a novel construct recently defined by the American Heart Association in response to the high prevalence of metabolic and kidney disease. Epidemiological data demonstrate higher absolute risk of both atherosclerotic cardiovascular disease (CVD) and heart failure as an individual progresses from CKM stage 0 to stage 3, but optimal strategies for risk assessment need to be refined. Absolute risk assessment with the goal to match type and intensity of interventions with predicted risk and expected treatment benefit remains the cornerstone of primary prevention. Given the growing number of therapies in our armamentarium that simultaneously address all 3 CKM axes, novel risk prediction equations are needed that incorporate predictors and outcomes relevant to the CKM context. This should also include social determinants of health, which are key upstream drivers of CVD, to more equitably estimate and address risk. This scientific statement summarizes the background, rationale, and clinical implications for the newly developed sex-specific, race-free risk equations: PREVENT (AHA Predicting Risk of CVD Events). The PREVENT equations enable 10- and 30-year risk estimates for total CVD (composite of atherosclerotic CVD and heart failure), include estimated glomerular filtration rate as a predictor, and adjust for competing risk of non-CVD death among adults 30 to 79 years of age. Additional models accommodate enhanced predictive utility with the addition of CKM factors when clinically indicated for measurement (urine albumin-to-creatinine ratio and hemoglobin A1c) or social determinants of health (social deprivation index) when available. Approaches to implement risk-based prevention using PREVENT across various settings are discussed.

Cardiovascular-kidney-metabolic health reflects the interplay among metabolic risk factors, chronic kidney disease, and the cardiovascular system and has profound impacts on morbidity and mortality. There are multisystem consequences of poor cardiovascular-kidney-metabolic health, with the most significant clinical impact being the high associated incidence of cardiovascular disease events and cardiovascular mortality. There is a high prevalence of poor cardiovascular-kidney-metabolic health in the population, with a disproportionate burden seen among those with adverse social determinants of health. However, there is also a growing number of therapeutic options that favorably affect metabolic risk factors, kidney function, or both that also have cardioprotective effects. To improve cardiovascular-kidney-metabolic health and related outcomes in the population, there is a critical need for (1) more clarity on the definition of cardiovascular-kidney-metabolic syndrome; (2) an approach to cardiovascular-kidney-metabolic staging that promotes prevention across the life course; (3) prediction algorithms that include the exposures and outcomes most relevant to cardiovascular-kidney-metabolic health; and (4) strategies for the prevention and management of cardiovascular disease in relation to cardiovascular-kidney-metabolic health that reflect harmonization across major subspecialty guidelines and emerging scientific evidence. It is also critical to incorporate considerations of social determinants of health into care models for cardiovascular-kidney-metabolic syndrome and to reduce care fragmentation by facilitating approaches for patient-centered interdisciplinary care. This presidential advisory provides guidance on the definition, staging, prediction paradigms, and holistic approaches to care for patients with cardiovascular-kidney-metabolic syndrome and details a multicomponent vision for effectively and equitably enhancing cardiovascular-kidney-metabolic health in the population.

A growing appreciation of the pathophysiological interrelatedness of metabolic risk factors such as obesity and diabetes, chronic kidney disease, and cardiovascular disease has led to the conceptualization of cardiovascular-kidney-metabolic syndrome. The confluence of metabolic risk factors and chronic kidney disease within cardiovascular-kidney-metabolic syndrome is strongly linked to risk for adverse cardiovascular and kidney outcomes. In addition, there are unique management considerations for individuals with established cardiovascular disease and coexisting metabolic risk factors, chronic kidney disease, or both. An extensive body of literature supports our scientific understanding of, and approach to, prevention and management for individuals with cardiovascular-kidney-metabolic syndrome. However, there are critical gaps in knowledge related to cardiovascular-kidney-metabolic syndrome in terms of mechanisms of disease development, heterogeneity within clinical phenotypes, interplay between social determinants of health and biological risk factors, and accurate assessments of disease incidence in the context of competing risks. There are also key limitations in the data supporting the clinical care for cardiovascular-kidney-metabolic syndrome, particularly in terms of early-life prevention, screening for risk factors, interdisciplinary care models, optimal strategies for supporting lifestyle modification and weight loss, targeting of emerging cardioprotective and kidney-protective therapies, management of patients with both cardiovascular disease and chronic kidney disease, and the impact of systematically assessing and addressing social determinants of health. This scientific statement uses a crosswalk of major guidelines, in addition to a review of the scientific literature, to summarize the evidence and fundamental gaps related to the science, screening, prevention, and management of cardiovascular-kidney-metabolic syndrome.

Background Nonalcoholic fatty liver disease (NAFLD) and heart failure (HF) are increasing in prevalence. The independent association between NAFLD and downstream risk of HF and HF subtypes (HF with preserved ejection fraction and HF with reduced ejection fraction) is not well established. Methods and Results This was a retrospective, cohort study among Medicare beneficiaries. We selected Medicare beneficiaries without known prior diagnosis of HF. NAFLD was defined using presence of 1 inpatient or 2 outpatient claims using International Classification of Diseases, Ninth Revision, Clinical Modification ( ICD-9-CM ), claims codes. Incident HF was defined using at least 1 inpatient or at least 2 outpatient HF claims during the follow-up period (October 2015-December 2016). Among 870 535 Medicare patients, 3.2% (N=27 919) had a clinical diagnosis of NAFLD. Patients with NAFLD were more commonly women, were less commonly Black patients, and had a higher burden of comorbidities, such as diabetes, obesity, and kidney disease. Over a mean 14.3 months of follow-up, patients with (versus without) baseline NAFLD had a significantly higher risk of new-onset HF in unadjusted (6.4% versus 5.0%; P <0.001) and adjusted (adjusted hazard ratio [HR] [95% CI], 1.23 [1.18-1.29]) analyses. Among HF subtypes, the association of NAFLD with downstream risk of HF was stronger for HF with preserved ejection fraction (adjusted HR [95% CI], 1.24 [1.14-1.34]) compared with HF with reduced ejection fraction (adjusted HR [95% CI], 1.09 [0.98-1.2]). Conclusions Patients with NAFLD are at an increased risk of incident HF, with a higher risk of developing HF with preserved ejection fraction versus HF with reduced ejection fraction. The persistence of an increased risk after adjustment for clinical and demographic factors suggests an epidemiological link between NAFLD and HF beyond the basis of shared risk factors that requires further investigation.

The global obesity epidemic is well established, with increases in obesity prevalence for most countries since the 1980s. Obesity contributes directly to incident cardiovascular risk factors, including dyslipidemia, type 2 diabetes, hypertension, and sleep disorders. Obesity also leads to the development of cardiovascular disease and cardiovascular disease mortality independently of other cardiovascular risk factors. More recent data highlight abdominal obesity, as determined by waist circumference, as a cardiovascular disease risk marker that is independent of body mass index. There have also been significant advances in imaging modalities for characterizing body composition, including visceral adiposity. Studies that quantify fat depots, including ectopic fat, support excess visceral adiposity as an independent indicator of poor cardiovascular outcomes. Lifestyle modification and subsequent weight loss improve both metabolic syndrome and associated systemic inflammation and endothelial dysfunction. However, clinical trials of medical weight loss have not demonstrated a reduction in coronary artery disease rates. In contrast, prospective studies comparing patients undergoing bariatric surgery with nonsurgical patients with obesity have shown reduced coronary artery disease risk with surgery. In this statement, we summarize the impact of obesity on the diagnosis, clinical management, and outcomes of atherosclerotic cardiovascular disease, heart failure, and arrhythmias, especially sudden cardiac death and atrial fibrillation. In particular, we examine the influence of obesity on noninvasive and invasive diagnostic procedures for coronary artery disease. Moreover, we review the impact of obesity on cardiac function and outcomes related to heart failure with reduced and preserved ejection fraction. Finally, we describe the effects of lifestyle and surgical weight loss interventions on outcomes related to coronary artery disease, heart failure, and atrial fibrillation.

Background: Obesity may contribute to adverse outcomes in coronavirus disease 2019 (COVID-19). However, studies of large, broadly generalizable patient populations are lacking, and the effect of body mass index (BMI) on COVID-19 outcomes- particularly in younger adults-remains uncertain., Methods: We analyzed data from patients hospitalized with COVID-19 at 88 US hospitals enrolled in the American Heart Association's COVID-19 Cardiovascular Disease Registry with data collection through July 22, 2020. BMI was stratified by World Health Organization obesity class, with normal weight prespecified as the reference group., Results: Obesity, and, in particular, class III obesity, was overrepresented in the registry in comparison with the US population, with the largest differences among adults ≤50 years. Among 7606 patients, in-hospital death or mechanical ventilation occurred in 2109 (27.7%), in-hospital death in 1302 (17.1%), and mechanical ventilation in 1602 (21.1%). After multivariable adjustment, classes I to III obesity were associated with higher risks of in-hospital death or mechanical ventilation (odds ratio, 1.28 [95% CI, 1.09-1.51], 1.57 [1.29-1.91], 1.80 [1.47-2.20], respectively), and class III obesity was associated with a higher risk of in-hospital death (hazard ratio, 1.26 [95% CI, 1.00-1.58]). Overweight and class I to III obese individuals were at higher risk for mechanical ventilation (odds ratio, 1.28 [95% CI, 1.09-1.51], 1.54 [1.29-1.84], 1.88 [1.52-2.32], and 2.08 [1.68-2.58], respectively). Significant BMI by age interactions were seen for all primary end points ( P -interaction<0.05 for each), such that the association of BMI with death or mechanical ventilation was strongest in adults ≤50 years, intermediate in adults 51 to 70 years, and weakest in adults >70 years. Severe obesity (BMI ≥40 kg/m 2 ) was associated with an increased risk of in-hospital death only in those ≤50 years (hazard ratio, 1.36 [1.01-1.84]). In adjusted analyses, higher BMI was associated with dialysis initiation and with venous thromboembolism but not with major adverse cardiac events., Conclusions: Obese patients are more likely to be hospitalized with COVID-19, and are at higher risk of in-hospital death or mechanical ventilation, in particular, if young (age ≤50 years). Obese patients are also at higher risk for venous thromboembolism and dialysis. These observations support clear public health messaging and rigorous adherence to COVID-19 prevention strategies in all obese individuals regardless of age.

Background and Aims: Inflammatory biomarkers and adipocytokines (IBA) may contribute to atherosclerosis by promoting vascular inflammation. The association between IBA and coronary artery calcium (CAC), a marker of subclinical atherosclerosis, is not well defined in South Asians (SA). We hypothesized that IBA (high sensitivity C-reactive protein [hsCRP], tumor necrosis factor alpha [TNF-α], adiponectin, and leptin) were independently associated with and improved discrimination of CAC among SA., Methods: We analyzed IBA and CAC among participants in the prospective Mediators of Atherosclerosis in South Asians Living in America (MASALA) study. We used logistic regression models to examine cross-sectional associations of IBA with CAC presence (CAC >0) and severity (CAC >100), and C-statistics to assess the incremental contribution of each IBA to traditional risk factors (TRF) from the AHA/ACC Pooled Cohort Equations (PCE) for discrimination of CAC., Results: Among 906 participants in the MASALA study, women (n = 420) had significantly higher levels of hsCRP, adiponectin, and leptin but lower levels of TNF-α than men (p < .01 for all). There was no significant association between any of the four IBA and either CAC category in multivariable-adjusted models, respectively. Lastly, none of the four IBA improved discrimination of CAC presence or severity when added to elements of the PCE., Conclusions: IBA were not associated with CAC presence or severity in the MASALA population. IBA did not help identify SA at risk of subclinical atherosclerosis, although associations with ASCVD events remain unclear. In SA, CAC may have a distinct pathophysiology independent of inflammation as measured by IBA., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Background: As heart failure (HF)-associated morbidity and mortality continue to escalate, enhanced focus on prevention is increasingly important. "Malignant" left ventricular (LV) hypertrophy (LVH): LVH combined with an elevated cardiac biomarker reflecting either injury (high-sensitivity cardiac troponin T), or strain (amino-terminal pro-B-type natriuretic peptide) has predicted accelerated progression to HF. We sought to determine whether malignant LVH identified community-dwelling adults initially free of cardiovascular disease at high risk of asymptomatic decline in LV ejection fraction or a clinical cardiovascular event., Methods and Results: A total of 4985 of 6814 individuals without prevalent cardiovascular disease underwent baseline cardiac magnetic resonance for LVH in combination with measurement of plasma high-sensitivity cardiac troponin T and amino-terminal pro-B-type natriuretic peptide as part of MESA (Multi-Ethnic Study of Atherosclerosis) and were subsequently divided into 4 groups: (1) No LVH, no elevated biomarkers (n=2206; 44.3%); (2) No LVH, ≥1 elevated biomarkers (n=2275; 45.7%); (3) LVH, no elevated biomarkers (n=153; 3.0%); and (4) LVH, ≥1 elevated biomarkers (malignant LVH; n=351; 7.0%). Cardiac magnetic resonance was repeated 10 years later (n=2831) for assessment of LV ejection fraction <50%. Median follow-up was 12.2 years. Malignant LVH was associated with 7.0-, 3.5-, and 2.6-fold adjusted increases in incidence of HF, cardiovascular death, and asymptomatic LV dysfunction, respectively, versus group 1. New-onset HF was predominately HF with reduced ejection fraction (9.5-fold increase)., Conclusions: Malignant LVH is predictive of progression to asymptomatic LV dysfunction, HF (particularly HF with reduced ejection fraction), and cardiovascular death. Consequently, malignant LVH represents a high-risk phenotype among individuals without known cardiovascular disease, which should be targeted for increased surveillance and more-aggressive therapies., (© 2018 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.)

Aims: Metabolic syndrome (MetS) increases atherosclerotic cardiovascular disease (ASCVD) risk. Low HDL cholesterol (HDL-C) is a diagnostic criterion of MetS and a major ASCVD risk factor. HDL particle concentration (HDL-P) associates with incident ASCVD independent of HDL-C, but its association with incident MetS has not been studied. We hypothesized that HDL-P would be inversely associated with incident metabolic syndrome independent of HDL-C and markers of adiposity and insulin resistance., Materials and Methods: HDL-P was measured by NMR and visceral fat by MRI in participants of the Dallas Heart Study, a probability-based population sample of adults age 30-65. Participants with prevalent MetS, DM, CVD, and any systemic illlness were excluded. Incident MetS as defined by NCEP ATPIII criteria was determined in all participants after median follow-up period of 7.0 years., Results: Among 1120 participants without DM or MetS at baseline (57% women, 45% Black, mean age 43), 22.8% had incident MetS at follow-up. HDL-P and HDL-C were modestly correlated (r=0.54, p<0.0001). In models adjusted for traditional risk factors and MetS risk factors including visceral fat, HS-CRP, triglyceride to HDL-C ratio, and HOMA-IR, the lowest quartile of HDL-P was associated with a 2-fold increased risk of incident MetS (OR 2.1, 95%CI 1.4-3.1; p=0.0003)., Conclusions: Low HDL-P is independently associated with incident MetS after adjustment for traditional risk factors, lipid parameters, adiposity, inflammation, and markers of insulin resistance. Further studies are warranted to validate these findings and elucidate the mechanisms underpinning this association., (Copyright © 2016. Published by Elsevier Ltd.)