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A Synopsis of the Evidence for the Science and Clinical Management of Cardiovascular-Kidney-Metabolic (CKM) Syndrome: A Scientific Statement From the American Heart Association

Originally published 2023;148:1636–1664


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.

Poor cardiovascular-kidney-metabolic (CKM) health is a major determinant of premature morbidity and mortality. Consequently, developing comprehensive strategies to augment CKM health across the life course is a key clinical and public health priority. There is a growing understanding of the science underlying the complex interplay among metabolic risk factors, chronic kidney disease (CKD), and the cardiovascular system. Accordingly, there has been an expansion of therapeutic approaches to prevent or mitigate metabolic risk factors, to delay kidney disease progression, and to reduce associated cardiovascular risk. The increasing number of agents with beneficial metabolic effects, kidney effects, or both that additionally improve cardiovascular disease (CVD) outcomes offers promise for the future of CKM care.

However, several fundamental gaps remain in our scientific insight into the mechanistic underpinnings of CKM health. There are also major gaps, as well as some conflicts, in current clinical guidelines with respect to the approach to screening, prevention, and management of the patient with CKM syndrome. Using a review of the literature and crosswalk of major guidelines, this scientific statement describes the current evidence and gaps in our knowledge in terms of the science, screening, and clinical care of CKM syndrome. The scientific statement concludes with charting a path forward for science and clinical care in relation to CKM health.


As described in the CKM health presidential advisory,1 CKM syndrome is defined as a systemic disorder characterized by pathophysiological interactions among metabolic risk factors, CKD, and the cardiovascular system, leading to multiorgan dysfunction and a high rate of adverse cardiovascular outcomes. CKM syndrome includes both individuals at risk for CVD due to the presence of metabolic risk factors, CKD, or both and individuals with existing CVD that is potentially related to or complicates metabolic risk factors or CKD. The increased likelihood of CKM syndrome and its adverse outcomes is further influenced by unfavorable conditions for lifestyle and self-care resulting from policies, economics, and the environment.

The pathophysiological consequences of CKM syndrome reflect multidirectional relationships among metabolic risk factors, CKD, and the cardiovascular system (Figure 1). CKM syndrome most commonly originates from excess or dysfunctional adipose tissue or both. Dysfunctional adipose tissue, particularly visceral adipose tissue, secretes proinflammatory and prooxidative products that damage arterial, cardiac, and kidney tissues.2–6 Inflammatory processes reduce sensitivity to the action of insulin, resulting in impaired glucose tolerance.3,6 The development of metabolic dysfunction–associated steatotic liver disease7 (previously called nonalcoholic fatty liver disease) further amplifies systemic inflammation and insulin resistance. Beyond these systemic effects, metabolic dysfunction–associated steatotic liver disease has additionally become the leading cause of liver failure and need for liver transplantation.8 When released into the systemic circulation, pro-oxidative and proinflammatory mediators exacerbate pathophysiological processes involved in atherosclerosis and myocardial injury; in glomerulosclerosis, kidney tubular inflammation, and kidney fibrosis; and in the development of metabolic risk factors. In addition to the systemic effects of adipose tissue, ectopic fat may be a local source of mediators and can produce compressive organ damage, especially when deposited in the epicardium and pericardium, promoting arrhythmogenesis, myocardial dysfunction, and coronary atherosclerosis, and within and around the kidney, contributing to hypertension and abnormal blood pressure variability.3,5,6,9

Figure 1.

Figure 1. Conceptual diagram for CKM syndrome. The image displays the pathophysiology underlying cardiovascular-kidney-metabolic (CKM) syndrome. CKM syndrome most commonly originates from excess adipose tissue, dysfunctional adipose tissue, or both. Multiple pathological processes related to dysfunctional adipose tissue result in insulin resistance and eventual hyperglycemia. Inflammation, oxidative stress, insulin resistance, and vascular dysfunction are highlighted as central processes leading to the development of metabolic risk factors, to the progression of kidney disease, to the potentiation of heart-kidney interactions, and to the development of cardiovascular diseases. Metabolic risk factors and chronic kidney disease further predispose to cardiovascular diseases through multiple direct and indirect pathways. MASLD indicates metabolic dysfunction–associated steatotic liver disease.

As one component of CKM syndrome, the constellation of risk factors making up metabolic syndrome (MetS)—abdominal obesity, dysglycemia, atherogenic dyslipidemia, and hypertension—has numerous pathophysiological consequences, including endothelial dysfunction, atherogenesis, thrombosis, myocardial injury, fibrosis, and cardiac remodeling. MetS thereby contributes to the development of all subtypes of CVD, including coronary heart disease, cerebrovascular disease, peripheral artery disease, cardiac arrhythmias, and heart failure (HF). Progression from MetS to type 2 diabetes (T2D) is common as a consequence of beta cell dysfunction in the context of chronic insulin resistance, which markedly amplifies risk for vascular and kidney disease.10

Mechanisms of vascular, heart, and kidney injury associated with these processes can be broadly classified as hemodynamic, metabolic, inflammatory, and fibrotic.11–14 Hyperglycemia induces glomerular hyperfiltration and hypertension, which are hemodynamic mechanisms that have long been recognized to initiate and propagate kidney damage. Along with obesity and systemic hypertension, glomerular hemodynamic and arterial injury is promulgated by sheer stress and damage to the endothelium that contribute to both atherosclerosis and glomerulosclerosis.11,15 Hypertension and obesity are also major etiologic factors underlying the development of left ventricular hypertrophy and HF.16

Hyperglycemia in T2D initiates a series of intracellular processes that promote kidney and vascular damage through inflammation and fibrosis.11,15,17 Altered intracellular glucose metabolism generates advanced glycation end products, reactive oxygen species, and activation of protein kinase C and the Janus kinase–signal transducer and activator of transcription pathways.11,15 These and various related intracellular signals lead to ongoing release of proinflammatory mediators, profibrotic factors, and immune cell recruitment.15,18,19 Intensively controlling hyperglycemia only modestly reduces the risk of microvascular complications or progression in individuals with long-term diabetes.20 Past hyperglycemia leads to long-lasting advanced glycation end products and epigenetic modifications, as well as subsequent upregulation of proinflammatory and profibrotic genes.15,21 Consequently, pathways initially activated by metabolic disturbance may become self-perpetuating.9,15,21

CKD is a major amplifier of cardiovascular risk. The hallmarks of CKD, albuminuria, low glomerular filtration rate (GFR), or both, are associated with progressive increases in the risk of major atherosclerotic vascular and HF events and cardiovascular death.22,23 Consequently, the most common causes of death for people with diabetes and CKD are HF and atherosclerotic CVD (ASCVD),24–26 and only ≈10% of patients with CKD even survive to reach kidney failure.27 As a result, greater numbers of individuals are affected by the constellation of risk factors and disease burden that encompasses CKM syndrome.

In addition to their various impacts on vascular disease, MetS and diabetes are predisposing conditions for CKD, with three-quarters of kidney failure cases attributed to diabetes and hypertension in the United States.28,29 Although the prevalence of other diabetes complications has fallen substantially, the number of people with diabetes who develop kidney failure has progressively risen over time.28,30–32 Moreover, deaths attributed to CKD in diabetes increased by 106% worldwide between 1990 and 2013.32

Although the mechanisms of kidney-heart interactions for reciprocal risk amplification are not fully elucidated, it is clear that many risk factors are shared. CKD, especially when present with diabetes, is a proinflammatory state, with elevated systemic inflammatory markers strongly associated with high cardiovascular risk.33,34 Vascular calcification is a common complication of CKD that is associated with ischemic complications, including myocardial infarction and peripheral artery disease.35 In addition, CKD and diabetes are more likely to precipitate peripheral artery disease below the knee, which is often more difficult to revascularize and is associated with more ischemic injury.36,37 CKD also leads to anemia and bone and mineral metabolism disorders that exacerbate CVD.38 Lower oxygen-carrying capacity increases myocardial demand and may worsen HF.16 Conversely, CVD, particularly HF, is associated with the development of CKD.16 HF may reduce GFR as a result of impaired cardiac output, high venous pressure, and activation of the renin-angiotensin-aldosterone system and sympathetic nervous system.16,39 In turn, low estimated GFR (eGFR) can exacerbate fluid retention, which increases vascular congestion, forming an interlocking cycle of organ failure between the heart and kidney. Last, atherosclerosis can affect the kidney vasculature, which, when associated with critical ischemia, can cause both resistant hypertension and kidney failure.40,41

In summary, CKM syndrome represents a multidirectional pathophysiology leading to increased morbidity and mortality that goes beyond the simple sum of its components.


Although the scientific understanding of the determinants and pathophysiological consequences of CKM syndrome is increasing, several key gaps persist in our knowledge, as detailed in the following sections (Table 1).

Table 1. Key Gaps in the Scientific Understanding of CKM Syndrome

Topic areaKey gaps
Mechanisms of CVD development in CKMElucidating mechanisms underlying the development of ASCVD
 Demographic differences, particularly by sex, and regional differences in CVD risk related to CKM syndrome
 Genetic underpinnings of CVD and role for genetic testing
 Mechanisms of endothelial dysfunction
Elucidating mechanisms underlying the development of HF and arrhythmias
 Molecular mechanisms of HFpEF development
 Determinants of progression from subclinical to clinical CVD
 Interactions between extracardiac dysfunction and cardiac dysfunction
Understanding the heterogeneity within CKM syndromeElucidating key aspects of CKM heterogeneity
 Heterogeneity in degree and subtypes of metabolic risk factors among individuals with excess weight
 Heterogeneity in progression across CKM stages
 Clarifying biological factors predisposing to CKM risk, social determinants of CKM risk, and their interrelationships
 Understanding the effect of risk-enhancing factors in those susceptible to CKM syndrome
Need for longitudinal studies of competing riskNeed for
 Accurate estimations of risk for CVD and CKD in the context of CKM syndrome considering competing risks
 Strategies for prioritizing clinical outcomes in longitudinal CKM risk modeling
Understanding bidirectional cardiovascular-kidney relationshipsClarifying aspects of cardiovascular-kidney interactions
 Pathways linking CVD to the development of CKD and those potentiating cardiovascular-kidney interactions
 Subtypes of CVD most linked to CKD
 Most appropriate markers for tracking CKD development in CVD

ASCVD indicates atherosclerotic cardiovascular disease; CKD, chronic kidney disease; CKM, cardiovascular-kidney-metabolic; CVD, cardiovascular disease; HF, heart failure; and HFpEF, heart failure with preserved ejection fraction.

Mechanisms of CVD Development in CKM

Although epidemiological studies have described clear associations of CKM components, including hallmark features of visceral adiposity and insulin resistance, with risk of ASCVD, the exact mechanisms remain incompletely understood. When present, CKM syndrome appears to accelerate the pathophysiology of atherosclerosis by augmenting inflammation, dyslipidemia, hypertension, and insulin resistance, each central contributors to the development of atherogenesis.2 With the changing landscape of atherosclerosis that has shifted to developing countries, women, and younger individuals, current knowledge gaps include an incomplete understanding of (1) sex differences in CVD in CKM syndrome, (2) genetic underpinnings of disease that may account for some regional differences and clinical applications of genetic testing, (3) mechanisms of endothelial dysfunction in CKM syndrome (accelerated in the presence of CKD42) as an early harbinger of CVD, and (4) environmental and community-level risk factors in the development of CVD.43

In contrast to atherosclerosis, mechanisms by which CKM syndrome leads to HF and arrhythmias (and, in particular, atrial fibrillation [AFib]) are less well described. Adiposity itself leads to hemodynamic changes. Additionally, adipose depots, including pericardial and myocardial fat accumulation, may exert direct effects on cardiac remodeling through activation of inflammatory and fibrosis pathways, in addition to abnormal myocardial energetics. The role of metabo-inflammation is increasingly recognized as an important mechanism leading to HF with preserved ejection fraction (HFpEF).44 Key knowledge gaps that remain include (1) molecular mechanisms of HFpEF in the setting of substantial phenotypic heterogeneity; (2) determinants of disease progression from subclinical to overt CVD, including HFpEF and AFib; and (3) interactions between extracardiac organ dysfunction, particularly kidney disease,16 and cardiac dysfunction.

Understanding the Heterogeneity Within CKM Syndrome

Another key gap relates to understanding the factors underlying the marked heterogeneity within CKM syndrome. There is significant heterogeneity in metabolic disease within weight categories, with some individuals having few or no metabolic risk factors beyond excess weight and others having multiple metabolic risk factors despite having only modest degrees of excess weight or even being within a normal weight range. It is important to note that the absence of metabolic risk factors among individuals with obesity is still associated with increased CVD risk relative to individuals with normal weight without metabolic risk factors.45 This is due to direct adverse cardiovascular effects of obesity and the fact that many individuals develop metabolic risk factors over time.45 However, there is limited understanding of the reasons for this heterogeneity in metabolic risk factors, with the distribution of ectopic fat and the metabolic activity of adipose tissue thought to play key roles.46

In addition, there are significant racial and ethnic differences in the propensity for metabolic risk factors at a given weight.47 Much of this is related to social determinants of health (SDOH), which primarily drive the higher burden of metabolic risk factors within historically disenfranchised populations.48,49 SDOH can be conceptualized within a socioecological framework in which societal factors, community, and interpersonal relationships affect each other and strongly influence individual health behaviors (Figure 2).

Figure 2.

Figure 2. Socioecological framework for CKM syndrome. Social determinants at multiple levels of influence, including at societal, community, interpersonal and individual behavioral levels, affect the likelihood of cardiovascular-kidney-metabolic (CKM) syndrome and of consequent adverse outcomes. Individual biological predisposition, nested within these multiple levels of social influence, further affects CKM syndrome development and related outcomes.

Individual biological predisposition also plays a key role; as an example, the higher burden of metabolic risk factors among people of South Asian ancestry is likely related to a higher degree of ectopic fat deposition at a given body mass index (BMI).50 However, individual biological predisposition is likely best conceptualized within a social context, with adverse SDOH and unfavorable biological factors being interrelated and leading to worse CKM outcomes when jointly present. Epigenetic changes, resulting from interconnections among genetic, environmental, social, and lifestyle factors, may help to elucidate the biological basis for heterogeneous manifestations of CKM syndrome.51 A better understanding is also needed regarding multiple MetS subtypes (eg, insulin resistance dominant, lipid dominant, vascular dominant) and the variability in the end organ–related manifestations of CKM syndrome.

There is also heterogeneity in the speed and extent of progression across CKM stages. Progression along CKM stages is associated with increased relative and absolute risk for CVD, kidney failure, and mortality. Altering the trajectory of CKM syndrome requires a deeper understanding of metabolic-inflammatory interplay accompanied by an integration of bio-socio-ecological pathways. Factors such as genetics, behavioral and environmental factors, and SDOH may collectively influence the progression of CKM syndrome across its stages. Indeed, in the CKM health presidential advisory, we identified risk-enhancing factors for progression along CKM stages, including sex-specific factors such as early menopausal transition, adverse pregnancy outcomes, and polycystic ovarian disease; mental health and sleep disorders; chronic inflammatory conditions; and family history of diabetes or kidney failure. However, there is limited understanding of the relative importance of these factors and how they interact to influence transitions from excess and dysfunctional adiposity to the emergence of metabolic risk factors and progressive kidney disease to subclinical and eventual clinical CVD. There is a key need for such outcomes data from diverse populations, including groups traditionally underrepresented in clinical studies and trials, to maximize our understanding of CKM syndrome heterogeneity. In addition, the development of animal or cellular models would be beneficial in understanding the molecular mechanisms that mediate the development and progression of CKM syndrome. Obtaining a deeper understanding of the factors linked to the variability in CKM and progression along CKM stages may inform novel strategies for predicting and positively influencing CKM health in the population.

Need for Longitudinal Studies of Competing Risk

Accounting for competing risk in longitudinal analyses not only allows more accurate risk prediction but also adds contextual dimensions and insights, especially when conducted over longer periods of time.52,53 CKM syndrome represents a complex interplay of conditions that are individually associated with high cardiovascular and kidney disease event rates such as myocardial infarction, stroke, HF, kidney failure, and death. However, high-quality studies focused on describing and assessing risks in CKM syndrome are scarce; thus, a longitudinal approach to studying competing risks of the various components of CKM syndrome provides an opportunity for new insights into mechanisms that affect or modify each factor over time. In the context of CKM syndrome, using competing-risk methodology to identify the first adverse outcome resulting from multiple interacting factors can guide the prioritization of preventive therapies, with the goal of averting primary (eg, myocardial infarction) and subsequent secondary (eg, HF or recurrent myocardial infarction) events.

Individually, the components of CKM have been modeled with competing-risk methodologies in multiple studies to avoid biased estimates of the risk for disease outcomes, as described previously.54 In CKD and kidney failure, competing-risk models have demonstrated higher concordance with observed outcomes than standard Cox regression modeling.55–57 Establishing adequate modeling methodologies will be important in consistent risk estimation. Such modeling methodologies will be important in accurately estimating future outcomes for the purposes of trial design and resource allocation in health care settings. The challenge for future analyses with the broad CKM syndrome will be the selection of outcomes to consider. For example, a patient with CKD G4 may be at risk for and experience kidney failure, a cardiovascular event, or death not related to CKM disease. On the other hand, individuals with earlier stages of CKD but with components of MetS may have higher risks of death or cardiovascular events in the short term and progressive kidney disease in the long term. Therefore, there is a great need to prioritize outcomes in risk modeling with CKM and to develop the appropriate modeling strategies to answer important questions related to long-term CKM syndrome consequences.

Understanding Bidirectional Cardiovascular-Kidney Relationships

The importance of considering cardiovascular and kidney disease in a singular framework stems from the frequent co-occurrence of these entities and the bidirectional organ cross talk that perpetuates organ damage. CKD is an important risk factor for CVD. The heightened risk begins at the earliest stages of kidney disease, most easily recognized by the presence of albuminuria.58 This biomarker reflects global vascular endothelial dysfunction and early kidney disease,59 further amplified by traditional metabolic risk factors such as elevated blood pressure and hyperglycemia. In addition, this heightened cardiovascular risk in kidney disease is recognized even in young individuals with congenital kidney diseases and in primary glomerular or tubulointerstitial diseases.60

The causal relationship between CVD and subsequent kidney disease is less understood (type 2 cardiorenal syndrome).16 Although kidney benefits have been shown in data from cardiovascular trials with agents such as angiotensin-converting enzyme (ACE) inhibitors/angiotensin II receptor blockers (ARBs), sodium-glucose cotransporter-2 (SGLT2) inhibitors, and finerenone,61 the global kidney trajectory in CVD has not received as much attention and needs further clarification. Questions that remain include the types of CVD most associated with future kidney disease (ie, ischemia, HF, valvular disease, arrhythmias), appropriate biomarkers for tracking kidney disease development in CVD, and age-specific variations in this risk.


To review the evidence related to the clinical management of CKM syndrome, the American Heart Association convened a science advisory group with broad transdisciplinary expertise. The science advisory group included representation from pediatrics, primary care, nephrology, endocrinology, cardiology, neurology, nursing, and pharmacology, with additional expertise in basic, clinical, epidemiologic, and interventional research. Regular meetings were held among the science advisory group and among a complementary CKM health patient advisory group to provide a lay perspective.

The science advisory group conducted a comprehensive review of the latest guidelines related to screening for CKM risk factors and the prevention and management of ASCVD, HF, and AFib in patients with CKD, T2D, obesity, and other cardiometabolic conditions (Table 2). We compared recommendations across guidelines using a systematic approach and identified the discrepancies in recommendations, the areas that were not adequately addressed in current clinical guidelines, and the gaps in the literature requiring further investigation. In our evaluation of the major guidelines, we classified the recommendations into 3 main categories: lifestyle, pharmacotherapy, and other considerations, including SDOH, interdisciplinary care, and patient-centered approaches. Prevention guidelines provided additional recommendations on screening individuals at risk of developing CVD or progressive kidney disease related to CKM risk factors.

Table 2. Major Guidelines and Scientific Statements Used in the CKM Health Crosswalk

Prevention and Management of ASCVD
2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease62
2021 ESC Guidelines on Cardiovascular Disease Prevention in Clinical Practice63
2023 Standards of Medical Care in Diabetes64
2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults65
2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol66
2013 AHA/ACC/TOS Guideline for the Management of Overweight and Obesity in Adults67
2022 AHA Scientific Statement: Comprehensive Management of Cardiovascular Risk Factors for Adults With Type 2 Diabetes61
2021 AHA Scientific Statement on Weight-Loss Strategies for Prevention and Treatment of Hypertension68
2022 KDIGO Clinical Practice Guideline for Diabetes Management in Chronic Kidney Disease69
2013 KDIGO Clinical Practice Guideline for Lipid Management in Chronic Kidney Disease70
Prevention and Management of HF
2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure71
2021 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure72
2023 Standards of Medical Care in Diabetes64
2022 AHA Scientific Statement: Comprehensive Management of Cardiovascular Risk Factors for Adults With Type 2 Diabetes61
2022 KDIGO Clinical Practice Guideline for Diabetes Management in Chronic Kidney Disease69
Prevention and Management of AFib
2020 ESC Guidelines for the Diagnosis and Management of Atrial Fibrillation Developed in Collaboration With the EACTS73
2019 AHA/ACC/HRS Focused Update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation74
2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure71
2021 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure72
Management of CKM Health in CKD
2022 KDIGO Clinical Practice Guideline for Diabetes Management in Chronic Kidney Disease69
2023 Standards of Medical Care in Diabetes64
2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure71
2021 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure72

AACVPR indicates American Association of Cardiovascular and Pulmonary Rehabilitation; AAPA, American Academy of Physician Assistants; ABC, Association of Black Cardiologists; ACC, American College of Cardiology; ACPM, American College of Preventive Medicine; ADA, American Diabetes Association; AFib, atrial fibrillation; AGS, American Geriatrics Society; AHA, American Heart Association; APhA, American Pharmacists Association; ASH, American Society of Hypertension; ASPC, American Society for Preventive Cardiology; ASCVD, atherosclerotic cardiovascular disease; CKD, chronic kidney disease; CKM, cardiovascular-kidney-metabolic; EACTS, European Association for Cardio-Thoracic Surgery; ESC, European Society of Cardiology; HF, heart failure; HFSA, Heart Failure Society of America; HRS, Heart Rhythm Society; KDIGO, Kidney Disease Improving Global Outcomes; NLA, National Lipids Association; NMA, National Medical Association; PCNA, Preventive Cardiovascular Nurses Association; and TOS, The Obesity Society.

The most recent guidelines from American (led primarily by American Heart Association/American College of Cardiology, with involvement of other subspecialty organizations) and European (primarily led by the European Society of Cardiology) cardiology societies for the management and prevention of ASCVD and HF served as the backbone for our crosswalk. Because ASCVD and HF guidelines from American societies referenced the hypertension65 and cholesterol66 guidelines for specific population subgroups and comorbidities such as recommendations for individuals with diabetes or CKD, hypertension and cholesterol guidelines were used as the primary reference for these specific patient populations. It is notable that the major guideline for the management of overweight and obesity in adults was published in 2013.67 Therefore, we incorporated recommendations related to weight management using more up-to-date guidelines and scientific statements within the CKM framework. The American Diabetes Association’s Standards of Care 2023 served as the primary source for CKM-related recommendations in patients with diabetes, and the Kidney Disease Improving Global Outcomes guidelines were used for therapeutic considerations related to CKD and diabetic kidney disease.75

To identify gaps in the recommendations, we additionally used information provided in scientific statements. This allowed us to incorporate the current evidence base and expert opinion into our advisory while also highlighting areas that necessitate further research. The guideline crosswalk was further supported by an extensive review of the scientific literature by members of the writing group. The complete list of guidelines used for the crosswalk exercise can be found in Table 2.


The ability to detect, at an early stage, conditions with significant negative clinical consequences remains an urgent preventive public health opportunity, especially when multiple effective therapeutics are available. The CKM staging construct provides a framework for identifying individuals at early stages of CKM syndrome to prevent progression to CVD (Table 3). Assessment and early management of modifiable risk factors is a cornerstone of cardiovascular prevention, with the recommended intensity of preventive interventions typically linked to the absolute risk of the individual and expected net benefit of the intervention. Major organizations support screening for hypertension, diabetes, and dyslipidemias, all key CKM risk factors, with early management of these conditions recommended to potentially improve clinical outcomes.62,63,69,76,77 Obesity confers greater risk with longer severity and duration, supporting the concept of addressing excess weight at early points in the life course.78 Traditionally, the components of CKM syndrome have been evaluated and measured separately, but there is a need to consider collective assessments for closely interrelated risk factors to facilitate holistic approaches to prevention.

Table 3. Definitions of CKM Health Stages

CKM health stagesDefinition
Stage 0: No CKM health risk factorsIndividuals without overweight/obesity, metabolic risk factors (hypertension, hypertriglyceridemia, MetS, diabetes), CKD, or subclinical/clinical CVD
Stage 1: Excess and/or dysfunctional adiposityIndividuals with overweight/obesity, abdominal obesity, or dysfunctional adipose tissue, without the presence of other metabolic risk factors or CKD
 BMI ≥25 kg/m2 (or ≥23 kg/m2 if Asian ancestry)
 Waist circumference ≥88/102 cm in women/men (or if Asian ancestry, ≥80/90 cm in women/men) and/or
 Fasting blood glucose ≥100–124 mg/dL or HbA1c between 5.7% and 6.4%*
Stage 2: Metabolic risk factors and CKDIndividuals with metabolic risk factors (hypertriglyceridemia (≥135 mg/dL), hypertension, MetS, diabetes) or CKD
Stage 3: Subclinical CVD in CKMSubclinical ASCVD or subclinical HF among individuals with excess/dysfunctional adiposity, other metabolic risk factors, or CKD
 Subclinical ASCVD to be principally diagnosed by coronary artery calcification (subclinical atherosclerosis by coronary catheterization/CT angiography also meets criteria)
 Subclinical HF diagnosed by elevated cardiac biomarkers (NT-proBNP ≥125 pg/mL, high-sensitivity troponin T ≥14 ng/L for women and ≥22 ng/L for men, high-sensitivity troponin I ≥10 ng/L for women and ≥12 ng/L for men) or by echocardiographic parameters, with combination indicating highest HF risk.
Risk equivalents of subclinical CVD
 Very high-risk CKD (G4 or G5 CKD or very high risk per KDIGO classification)
 High predicted 10-y CVD risk
Stage 4: Clinical CVD in CKMClinical CVD (coronary heart disease, heart failure, stroke, peripheral artery disease, AFib) among individuals with excess/dysfunctional adiposity, other metabolic risk factors, or CKD
 Stage 4a: no kidney failure
 Stage 4b: kidney failure present

AFib indicates atrial fibrillation; ASCVD, atherosclerotic cardiovascular disease; BMI, body mass index; CKD, chronic kidney disease; CKM, cardiovascular-kidney-metabolic; CT, computed tomography; CVD, cardiovascular disease; HbA1c, hemoglobin A1c; HF, heart failure; KDIGO, Kidney Disease Improving Global Outcomes; MetS, metabolic syndrome; and NT-proBNP, N-terminal pro-B-type natriuretic peptide.

* Individuals with gestational diabetes should receive intensified screening for impaired glucose tolerance after pregnancy.

† MetS is defined by the presence of ≥3 of the following: (1) waist circumference ≥88 cm for women and ≥102 cm for men (if Asian ancestry, ≥80 cm for women and ≥90 cm for men), (2) high-density cholesterol <40 mg/dL for men and <50 mg/dL for women; (3) triglycerides ≥150 mg/dL; (4) elevated blood pressure (systolic blood pressure ≥130 mm Hg and/or diastolic blood pressure ≥80 mm Hg and/or use of antihypertensive medications); and (5) fasting blood glucose ≥100 mg/dL.

MetS is strongly linked to the development of diabetes and CVD, and the MetS construct underscores the connectivity of several metabolic risk factors. Both the diagnostic components of MetS and additional pathophysiological features such as inflammation, endothelial dysfunction, a prothrombotic milieu, and a higher low-density lipoprotein (LDL) particle concentration confer CVD risk. Therefore, addressing the root causes of MetS through lifestyle modification, in addition to pharmacological risk factor control, is key to fully address both diagnostic and typically unmeasured MetS components and their associated CVD risk.

CVD and kidney diseases are currently treated as separate health conditions. However, the increasing recognition that these 2 conditions are closely linked through shared biological and social risk factors warrants updated considerations in the context of CKM syndrome. Historically, screening for kidney diseases has had variable support from the medical community. In the strongest argument against screening, the US Preventive Services Task Force issued a statement that routine screening for CKD among the general adult population lacked sufficient evidence for benefit.79 However, this guidance must be revisited with the advent of several classes of medications now demonstrating benefit in slowing the progression of CKD (eg, ACE inhibitors/ARBs, SGLT2 inhibitors, and nonsteroidal mineralocorticoid receptor antagonists), preventing CVD events, and reducing cardiovascular mortality. Most specialty organizations have now embraced the importance of identifying CKD, especially in high-risk adult populations such as those with diabetes.58,61 Screening for CKD has historically been centered around the eGFR. The challenges with relying solely on the eGFR are numerous, including inconsistent reporting with some systems not reporting granular values >60 mL·min−1·1.73 m−2 and imprecision related to higher eGFR estimations. There are alternative categorizations to define kidney disease, including a rubric that relies on albuminuria (>30 mg/g creatinine in a spot urine specimen). Albuminuria is an independent risk marker for future CVD events below the standard threshold for CKD criteria and is an important screening tool for patients with diabetes.58,69,80 The Kidney Disease Improving Global Outcomes CKD staging system combines eGFR and albuminuria to provide a broad risk estimate for CKD progression, CVD events, and overall mortality.81 Including kidney parameters as part of comprehensive CKM screening will enhance the potential to predict and prevent clinically relevant and patient-reported outcomes.


Review of the literature and major guidelines revealed key gaps and conflicts with regard to screening for children, metabolic risk factors and CKD in adulthood, subclinical CVD, and SDOH closely linked to CKM health (Table 4).

Table 4. Key Gaps in the Screening Approaches for CKM Syndrome

Topic areaKey gaps
Early-life screeningNeed for clarity on early life screening for CKM factors
 Not currently recommended by USPSTF because of limited evidence on outcome, but recommended by other pediatric organizations
Screening for metabolic risk factors and CKD in adulthoodObesity: limited focus on waist circumference measurements and race- and ethnicity-specific cut points in current guidelines
MetS components: suboptimal identification of MetS in clinical practice, which should trigger lifestyle change and multifactorial risk factor control
 Optimal frequency for MetS screening undefined
CKD: significant underuse of urine albumin-creatinine ratio measurement in concert with eGFR to fully characterize CKD-associated risk
Subclinical CVD diagnosisSubclinical HF: optimal strategy for identifying in the population not fully defined
 Possible targeted cardiac biomarker measurements based on combination of age/CKM risk factors/risk algorithms
 Next diagnostic/therapeutic steps after the finding of elevated cardiac biomarkers not yet defined
 CKD systematically underemphasized in current HF staging despite high HF risk with CKD
  CKD not among risk conditions in HF guidelines; CKD excluded from biomarker definition for subclinical HF because of elevated biomarker levels with kidney dysfunction; alternative approach for defining and addressing risk in CKD remains undefined
SDOH screeningApproach to and utility of systematic screening for SDOH
 Optimal tools for SDOH screening (may differ by setting)
 Strategies for incorporating SDOH screening into EHR and clinical workflows
 Impact of addressing SDOH identified by screening on clinical outcomes

CKD indicates chronic kidney disease; CKM, cardiovascular-kidney-metabolic; CVD, cardiovascular disease; eGFR, estimated glomerular filtration rate; EHR, electronic health record; HF, heart failure; MetS, metabolic syndrome; SDOH, social determinants of health; and USPSTF, US Preventive Services Task Force.

Gaps in Early Life Screening

Indicators of cardiovascular health such as those in Life’s Essential 882 present an important paradigm for prevention of disease, but the age at which to begin screening and prevention efforts has been controversial. The vascular and myocardial pathology underlying CVD begins early in life and progresses through childhood and adolescence into adulthood. The most direct evidence for prevention would come from studies linking screening and prevention efforts initiated during childhood to a clear reduction of cardiac outcomes in adulthood. Unfortunately, such studies are impractical because of the necessary duration and cost. From this lack of direct evidence, the US Preventive Services Task Force has concluded that there is insufficient evidence to assess the benefits and harms of screening for most cardiovascular risk factors in children and adolescents.83–86 However, some pediatric organizations, including the American Academy of Pediatrics, have recommended early-life screening on the basis of multiple lines of indirect evidence suggesting an association among childhood cardiovascular risk factor onset, preservation of ideal cardiovascular health, tracking of risk factors into adulthood, and the likelihood of long-term CVD events.87–91 Pediatric obesity and pediatric CKD precede the development of other CKM risk factors.92,93 Pediatric CKD is associated with increased CVD mortality risk that is often arrhythmic in pathogenesis.60,94 In addition, blood pressure control in pediatric patients with CKD reduces CKD progression.95 Additional evidence of the benefits of screening early in life and the impact of early identification of modifiable risk factors is needed.

Gaps in Screening for Metabolic Risk Factors and CKD in Adulthood

The foundations of metabolic risk factor screening include measurements of blood pressure, lipids, blood glucose, and the anthropometric measures of BMI and waist circumference. Assessments of kidney function provide complementary prognostic information and guide therapeutic approaches. However, there is limited and conflicting guidance on the recommended frequency, age of inception, and modalities for screening for CKM risk factors, which need to be addressed within the paradigm for CKM screening.

Screening for traditional risk factors is recommended in healthy young adults every 4 to 6 years. Obesity is at the core of CKM syndrome, and annual assessments of BMI are widely recommended.62,63 Because BMI does not reflect body composition, the addition of waist circumference measurements enhances the identification of increased cardiometabolic risk, particularly in overweight and grade I obesity, but the utility of widespread waist circumference assessments is debated. Assessments for prediabetes and diabetes may inform dietary and physical activity counseling and are recommended by American Diabetes Association and US Preventive Services Task Force every 3 years in adults with overweight or obesity on the basis of modeling of diabetes incidence. Those with gestational diabetes are at high risk for diabetes, and timely interventions prevent diabetes development.96 Evidence further suggests that glycemic assessments in the overall population, regardless of BMI, increase equity in prediabetes and diabetes diagnosis.97 Blood pressure screening is recommended every 3 to 5 years in those 18 to 39 years of age and annually in those >40 years of age.98 Approximately half of individuals with obesity but without metabolic risk factors develop metabolic risk factors over 6 to 7 years of follow-up.99 The Endocrine Society recommends assessment for MetS every 3 years for individuals with risk factors and yearly diabetes assessments in those with prediabetes.100 Because of the close relationship between metabolic risk factors and metabolic dysfunction–associated steatotic liver disease, the American Association for the Study of Liver Diseases recommends screening for liver fibrosis every 1 to 2 years among individuals with established metabolic risk factors. The Kidney Disease Improving Global Outcomes recommends CKD assessments, including eGFR and albuminuria, to provide the most prognostic information for kidney and cardiovascular risk,75 with the greatest utility in those with CKD and established metabolic risk factors such as diabetes and hypertension.80 Overall, current evidence, although limited, supports the most frequent assessments of CKM risk profiles for those with established metabolic risk factors, moderate-frequency CKM risk factor screening in those with excess weight or prior gestational diabetes, and less frequent but systematic screening in healthy adults to support equitable identification of CKM risk factors.97 However, there is need for prospective clinical data to validate the utility of this approach.

Gaps in Subclinical CVD Diagnosis

Subclinical CVD is associated with increased absolute risk for CVD events. However, in the general primary prevention population, routine testing for the diagnosis of subclinical CVD in asymptomatic individuals is not recommended.62 The presence of coronary artery calcium (CAC), a marker of subclinical atherosclerosis, identifies individuals likely to have the greatest net clinical benefit from statin therapy.101 Although carotid intima-media thickness is also associated with ASCVD, the magnitude of association is diminished compared with CAC, and the relationship of carotid intima-media thickness to treatment remains controversial.102 Therefore, American Heart Association guidelines endorse selective use of CAC scoring to help guide decisions on statin therapy for those in the borderline to intermediate range as quantified by the Pooled Cohort Equations. Emerging data further suggest that CAC testing may help with targeting the intensification of preventive therapies beyond statins.103,104

The optimal approach for identifying subclinical HF in the population is less clear. Elevated cardiac biomarkers (BNP [brain natriuretic peptide] or high-sensitivity cardiac troponins) and abnormal cardiac function or structure by cardiac imaging now make up the diagnostic criteria for subclinical HF, with the presence of both associated with greatest HF risk.71,105 The 2022 American College of Cardiology/American Heart Association/Heart Failure Society of America guidelines for HF management support BNP-based measurements71 on the basis of data from STOP-HF (St. Vincent’s Screening to Prevent Heart Failure Study)106 and PONTIAC (NT-proBNP Guided Primary Prevention of CV Events in Diabetic Patients),107 which were randomized controlled trials that demonstrated benefit and cost-effectiveness of BNP-based assessments for the prevention of HF.108 An American Diabetes Association consensus statement supports BNP measurements in older adults with diabetes. However, there is limited clarity on how best to target cardiac biomarker measurements in the population, the frequency of such testing, and appropriate next diagnostic steps (eg, echocardiograms) when elevated cardiac biomarkers are identified. Potential strategies may include measurement strategies based on risk factors (eg, diabetes109,110), age (eg, ≥65 years111,112), or an intermediate risk threshold based on 10-year risk of HF.

Individuals with CKD are systematically underemphasized in current HF staging approaches. Despite being strongly linked to HF risk, CKD is not among the HF risk factors in stage A HF.71 In addition, because of elevated cardiac biomarker levels with kidney dysfunction, individuals with CKD are excluded from the biomarker-based definition for subclinical HF (stage B HF). Alternative strategies are needed to quantify and address HF risk in CKD.

Gaps in SDOH Screening

SDOH play a critical role in CKM health; however, several evidence gaps exist about screening for social needs among patients with CKM syndrome.113,114 The effectiveness of routine social needs screening and referral to resources for improving CKM health behaviors such as nutrition and physical activity and outcomes must be further elucidated. Interventions for social needs screening and referral must account for CKM-related health behavior and outcome disparities and promote health equity. Effective interventions should be identified for geographic areas where structural racism and other adverse SDOH serve as barriers to health care and healthy behaviors (ie, food deserts115), without stigmatizing patients or adding undue clinician burden. Moreover, SDOH are intrinsically linked to access to CKM therapies, particularly cardioprotective glucose-lowering therapies. Therefore, we must better understand the effects of addressing social needs on CKM therapeutic access and use. Social needs screening tools must also be harmonized across electronic health record platforms to reach diverse patient populations. In addition, workflow pathways should be developed in health care systems to address social needs among patients with CKM syndrome by identifying, evaluating, using, and referring to existing community resources. Last, multilevel support across health care systems is critical for the implementation of care models that reflect a SDOH focus. The composition of interdisciplinary care teams should include care navigators, social workers, or community health workers who can connect patients to necessary social need resources that protect against the effects of adverse social conditions.


A growing body of evidence supports the overarching considerations of facilitating interdisciplinary care and assessing or addressing SDOH in CKM care. There is also substantial evidence supporting approaches for individual CKM stages, including those without CKM risk factors or subclinical or clinical CVD (stage 0); with excess/dysfunctional adiposity (stage 1); with metabolic risk factors, moderate- to high-risk CKD, or both (stage 2); with subclinical CVD overlapping with CKM risk factors or risk equivalents (stage 3); and with clinical CVD overlapping with CKM risk factors (stage 4). A summary of the evidence supporting the approach to management for each stage of CKM syndrome is provided in Figure 3.

Figure 3.

Figure 3. Summary of the evidence for recommended approaches and treatments at each stage of CKM syndrome. ACEi indicates angiotensin-converting-enzyme inhibitors; ARB, angiotensin II receptor blockers; ARNi, angiotensin receptor/neprilysin inhibitors; ASCVD, atherosclerotic cardiovascular disease; BP, blood pressure; CAC, coronary artery calcium; CKD, chronic kidney disease; CKM, cardiovascular-kidney-metabolic; CVD, cardiovascular disease; CVH, cardiovascular health; eGFR, estimated glomerular filtration rate; GDMT, guideline-directed medical therapy; GLP-1RA, glucagon-like peptide 1 receptor agonist; HbA1c, hemoglobin A1c; HF, heart failure; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; LDL-C, low-density cholesterol; LV, left ventricle; MACE, major adverse cardiac event; MetS, metabolic syndrome; MRA, mineralocorticoid receptor antagonist; P2Y12i, P2Y12 inhibitor; QOL, quality of life; and SGLT2i, sodium-glucose cotransporter-2 inhibitor. *Incretin analog indicates GLP1-RA, GLP1/GIP-RA, and GLP1/GIP/glucagon-RA.

Interdisciplinary Care

Individuals navigating multiple comorbid conditions face unique challenges related to fragmented care across several health care professionals. Models supporting interdisciplinary care demonstrate promise for providing harmonized and holistic care and supporting adherence to recommended therapies.116–118 Patients attending cardiometabolic clinics that include representation from cardiology, endocrinology, pharmacy, and nutrition, aided by nurse navigators, have increased use of cardiometabolic therapies and achieve more favorable metabolic risk profiles.119 A recent randomized trial demonstrated increased use of cardiometabolic therapies with the engagement of a multidisciplinary team and an implementation specialist.120 A combination of value- and volume-based interdisciplinary care models has the potential to increase feasibility and scalability across diverse clinical settings with disparate health care resources.

Incorporation of SDOH

Interventions that incorporate social need screening and connect patients to services have demonstrated reductions in social need prevalence.114 A limited number of interventions have examined health outcomes in the setting of addressing social needs, and few studies have shown improvement in CKM health–related factors. For instance, obtaining resources for social needs related to food, housing, medication, and transportation after screening was associated with reductions in blood pressure and LDL cholesterol (LDL-C) but not hemoglobin A1c (HbA1c).71 Screening for and addressing social needs has also been linked to a reduction in emergency room visits. Other interventions have shown higher smoking cessation rates or greater fruit and vegetable consumption for those who gained resources to address social needs.121 More data are needed that examine the impact of interventions that address social needs on CKM health risk factors and outcomes.

Screening to Support CKM Staging

A critical element of the CKM framework is active screening in the population and clinical settings to identify individuals at different stages of CKM syndrome. Screening involves assessing for biological factors and screening for SDOH, which can powerfully affect the development of CKM syndrome and influence its outcomes and management. The goal is to identify CKM syndrome in its earliest phases to avert the development of clinical CVD and kidney failure. Currently, for both children and adults, there is a lack of consensus on timing, frequency, and components for screening approaches to CKM syndrome (Table 4). A detailed discussion of recommendations for CKM screening can be found in the CKM health presidential advisory.1

Evidence for Stage 0 CKM Approach

The stage 0 approach is focused on primordial prevention in those with optimal cardiovascular health, including the absence of CKM risk factors and subclinical or clinical CVD. CKM risk factors in childhood such as obesity, hypertension, and diabetes frequently persist into adulthood and are linked to long-term vascular disease.90,122,123 The Life’s Essential 8 framework provides a holistic approach for attaining and preserving cardiovascular health,82 with Life’s Essential 8 health metrics of weight, blood pressure, glycemia, and lipids also being components of CKM syndrome. Studies indicate that sustaining healthy lifestyle practices from childhood through young adulthood is critical for maintaining ideal cardiovascular health through middle age.82 Among children, school-based programs promoting healthy eating and physical activity by targeting students, staff, and families or enhancing the school environment are shown to reduce weight and increase the likelihood of achieving ideal cardiovascular health.124,125 Among young adults, the avoidance of weight gain with aging reduces the likelihood of developing CKM risk factors such as MetS and prediabetes/diabetes over time.126

Evidence for Stage 1 CKM Approach

The stage 1 approach is focused on the prevention of metabolic risk factor development in those with excess or dysfunctional adiposity. Although weight loss is highly desirable at this CKM stage for cardiometabolic benefits, adopting a heart-healthy diet and increasing levels of physical activity and fitness confer several clinical benefits that are independent of weight loss and should be encouraged. Although providing weight loss counseling is strongly linked to patients’ likelihood of attempting weight loss, patients are more likely to achieve clinically significant weight loss if they do not perceive judgment during the weight loss discussion.127 Therefore, it is important to use patient-centered approaches such as those outlined in toolkits from the STOP Obesity Alliance when engaging in weight loss discussions.128 For patients with excess weight, intentional weight loss reduces the likelihood of developing metabolic risk factors in a dose-response fashion, with clinically significant benefits seen at ≥5% weight loss.129 More marked weight loss may be associated with lower risk for incident CVD. Intentional weight loss through lifestyle modification is best achieved through a comprehensive lifestyle intervention of ≥6 months’ duration. Obesity pharmacotherapies and bariatric surgery are effective adjunctive approaches to lifestyle change, with bariatric surgery linked to lower CVD and mortality rates in matched observational studies.130,131 In navigating the various therapeutic options for supporting weight loss, integrated multidisciplinary weight loss teams can facilitate patient-centered approaches to achieving weight reduction goals. In assessing metabolic risk and the need for lifestyle change, it is important to consider both anthropometric and glycemic measures to capture individuals with dysfunctional adiposity despite nonelevated anthropometric measures.132,133 Notably, non-White adults develop prediabetes or diabetes in normal weight categories more commonly than White adults,47 illustrating the importance of such an approach for identifying metabolic risk equitably. Among individuals with impaired glucose tolerance, including those with prior gestational diabetes, both lifestyle modification and metformin reduce progression to diabetes.95,134

Evidence for Stage 2 CKM Approach

The stage 2 approach is focused on CVD prevention in those with at least 1 established metabolic risk factor or moderate- to high-risk CKD.

Hypertension, Hypertriglyceridemia, and MetS

Improving blood pressure control markedly reduces risk for multiple CVD outcomes in a dose-response fashion. Guidelines support a blood pressure goal of <130/80 mm Hg for all, with the addition of pharmacological therapy to lifestyle change recommended for those with diabetes, CKD, age ≥65 years, or a predicted 10-year ASCVD risk of ≥10%. Although thiazide-type diuretics and calcium channel blockers are similarly effective, ACE inhibitors/ARBs should be prioritized in those with diabetes and albuminuria or those with other CKD given their impact on preventing worsening kidney function.65,135,136

Hypertriglyceridemia is causally related to ASCVD. Guidelines support addressing lifestyle factors and medications often linked to hypertriglyceridemia as the initial approach for lowering triglycerides.66 In those at intermediate ASCVD risk or greater, statin therapy modestly reduces triglycerides and lowers ASCVD risk. In those with modest hypertriglyceridemia (135–499 mg/dL), diabetes, and concomitant risk factors, icosapent ethyl lowers risk for CVD events.137 Marked hypertriglyceridemia (≥500 mg/dL) is associated with increased pancreatitis risk. Guidelines support fibrate therapy to reduce pancreatitis risk if triglycerides remain markedly elevated after lifestyle change and addressing secondary causes, with fenofibrate associated with least side effects with concomitant statin therapy.66

The MetS construct includes the interrelated metabolic risk factors of hypertension, atherogenic dyslipidemia, abdominal obesity, and impaired glucose tolerance. MetS is found among the majority of individuals with diabetes, and collective metabolic risk factor control is strongly linked to CVD risk in diabetes.138 An approach of lifestyle modification with additional pharmacological therapy as needed to achieve multifactorial risk factor control is associated with reduced CVD event rates.139


Among individuals with T2D with overweight or obesity, weight loss through intensive lifestyle intervention improves risk factor control and functional status.140 Several randomized controlled trials support the utility of moderate- to high-intensity statin therapy for preventing ASCVD events in individuals with diabetes, with more intensive statin therapy indicated for those with higher baseline risk. For individuals with diabetes and high estimated ASCVD risk, the addition of ezetimibe can help achieve the desired goal of ≥50% LDL-C reduction.141,142

The use of cardioprotective antihyperglycemic therapies such as SGLT2 inhibitors and glucagon-like peptide 1 receptor agonists (GLP-1RAs) reduces CVD events and mortality and is indicated for patients with diabetes and significant comorbidities on the basis of inclusion criteria from randomized clinical trials. Because of the differential physiological effects of SGLT2 inhibitors and GLP-1RAs, data support a comorbidity-based approach for selecting agents.143 SGLT2 inhibitors reduce the risk of worsening kidney function and are likely preferred for those with CKD.69,80,144 Because American Diabetes Association guidelines support achieving an HbA1c <7% in diabetes, GLP-1RAs may be preferred in those with marked hyperglycemia (HbA1c ≥9%) or on high insulin doses because of a stronger impact on glycemia than SGLT2 inhibitors.145 In addition, GLP-1RAs may be preferred for those with severe obesity (BMI ≥35 kg/m2) given their potent impact on weight loss. Data suggest that risk estimation may help guide the targeting of cardioprotective antihyperglycemic therapies.146 SGLT2 inhibitors may have greatest utility in those with high HF risk given their beneficial impact on reducing HF hospitalizations. GLP-1RAs may be particularly useful in those with high ASCVD risk. Metformin improves glycemic control and is associated with significantly less financial burden than newer cardioprotective antihyperglycemic therapies. For individuals with uncontrolled hyperglycemia (eg, HbA1c, ≥7.5%), co-utilization of metformin with cardioprotective antihyperglycemic therapies (particularly with SGLT2 inhibitors) can help to achieve glycemic targets with less financial burden for patients.

Chronic Kidney Disease

ACE inhibitor/ARB use in proteinuric CKD regardless of diabetes status is linked to decreased kidney disease progression and rates of adverse cardiovascular events.77 Better blood pressure control leads to CVD risk reduction in CKD regardless of diabetes status.65,77,147 Consistent benefits have been demonstrated with SGLT2 inhibitors with respect to reduction in CKD progression or need for kidney replacement therapies and incident CVD, with the largest impact on rates of incident HF.39 GLP-1RAs also have established CVD benefits,39 with ongoing studies examining kidney outcomes.148 In the FIDELITY (Finerenone in Chronic Kidney Disease and Type 2 Diabetes: Combined FIDELIO-DKD and FIGARO-DKD Trial Programme Analysis) pooled analysis, among patients with T2D and CKD on maximally tolerated ACEI/ARB use, finerenone led to reduced risk of kidney disease progression and CVD events, with a particularly potent impact on HF hospitalizations.149 In the SHARP trial (Study of Heart and Renal Protection), among patients with CKD (almost half of whom were on dialysis) with no known history of ASCVD, patients randomized to simvastatin plus ezetimibe compared with placebo had a significant reduction in first major atherosclerotic events.150

Evidence for Stage 3 CKM Approach

The Stage 3 approach is focused on intensified lifestyle change and preventive therapies for those individuals with evidence of subclinical ASCVD or HF overlapping with CKM risk factors or with the risk equivalents of very high-risk CKD or high predicted CVD risk.

Subclinical HF

Elevations of cardiac biomarkers (NT-proBNP [N-terminal pro-B-type natriuretic peptide] or high-sensitivity troponin) and the presence of myocardial structural or functional abnormalities on cardiac imaging identify individuals with subclinical cardiac dysfunction who are at greatest risk for clinical HF. Among patients with asymptomatic systolic dysfunction, ACE inhibitors have been shown to reduce progression to clinical HF or CVD mortality.151 In post hoc analyses of clinical trials, the addition of β-blocker therapy to ACE inhibitors for those with asymptomatic left ventricular dysfunction was associated with lower rates of the combined outcome of death or HF hospitalization.152 As a result, ACE inhibitors and β-blockers are recommended in guidelines for individuals with subclinical systolic dysfunction.71 Among individuals with diabetes, SGLT2 inhibitors reduce the likelihood of incident hospitalized HF or cardiovascular mortality.153 SGLT2 inhibitors are expected to have the greatest absolute reduction in HF events in those with diabetes and subclinical cardiac dysfunction given their high baseline HF risk.154 Trials of HF prevention efforts guided by natriuretic peptide screening demonstrate some promise for reducing progression to clinical HF.

Subclinical ASCVD

Extensive data validate CAC scores as a powerful discriminator of ASCVD risk. In the MESA study (Multi-Ethnic Study of Atherosclerosis), a CAC score of 0 was associated with 10-year ASCVD rates <5% among individuals at less than high predicted ASCVD risk, whereas CAC scores ≥100 are linked to 10-year ASCVD rates ≥7.5% (intermediate risk or higher).155 CAC scores provide the most prognostic information in those estimated to be at intermediate risk, with significant reclassification, improvement in discrimination, and greater estimated absolute risk reduction from statins in those with elevated CAC.156,157 Current guidelines therefore support selective CAC scoring to guide decisions about statin use in those estimated to be at borderline to intermediate risk for ASCVD events.62 A growing body of data support the use of CAC, as an indicator of absolute ASCVD risk, for identifying individuals likely to have greatest net benefit from the use of aspirin, as well as from proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, GLP-1RAs, icosapent ethyl for hypertriglyceridemia, and antihypertensive therapy.158 However, clinicians should be mindful that these studies represent simulated data from randomized controlled trials applied to epidemiological cohorts with significant drop-in of preventive therapies over time, making assessment of absolute event rates difficult.

Risk Equivalents and Overarching Considerations in Stage 3 CKM

Individuals with very high-risk CKD by the Kidney Disease Improving Global Outcomes risk classification or with high predicted CVD risk also represent subgroups of individuals with high absolute risk for whom preventive therapies may have the greatest net benefit, if contraindications to therapy are not present and after competing risk is considered. Several of the preventive therapies described previously might have the largest effect on event rates in this population, and additional preventive approaches may be considered. For example, observational data suggest that combination therapy with SGLT2 inhibitors and GLP-1RAs may have a greater impact on major adverse cardiac events and HF events than one of the agents alone.159 Optimal targeting for such an approach is undefined but could be considered in the stage 3 CKM population at higher absolute CVD risk.

Evidence for Stage 4 CKM Approach

The stage 4 approach is focused on the management of patients with CVD overlapping with CKM risk factors. In addition to a general emphasis on healthy lifestyle practices, guidelines are largely aligned on approaches to guideline-directed medical therapy (GDMT) for patients with HF, with a focus on the 4 pillars of management: β-blockers, angiotensin receptor/neprilysin inhibition, mineralocorticoid receptor antagonists, and SGLT2 inhibitors in HF with reduced ejection fraction (HFrEF).71,72 Similarly, guidelines generally agree on the use of aspirin or P2Y12 inhibitor and high-intensity statins for patients with ASCVD, with additional LDL-lowering therapy as needed according to LDL-C levels, LDL-C reduction goals, and the presence of accompanying high-risk features.62,63 Additional evidence supporting therapeutic approaches for those with overlapping CKM risk factors is described in the next section.

Obesity, MetS Components, and CVD

Despite the finding of an obesity paradox among individuals with CVD in which individuals with overweight and grade I obesity have slightly longer survival than those with normal weight, intentional weight loss is linked to clinical benefit among patients with obesity and CVD. A patient-centered and nonjudgmental approach to initiating the weight loss discussion is most effective,127 with the STOP Obesity Alliance toolkit serving as a useful framework for clinicians.128 Weight loss through lifestyle modification is linked to improved risk factor control among patients with obesity and ASCVD.129 In patients with obesity and HFpEF, lifestyle modification, including exercise training, improves functional status.160 In terms of adjunctive obesity pharmacotherapies, high-dose glucagon-like peptide 1 receptor agonists (GLP-1RAs) and glucose-dependent insulinotropic polypeptide-receptor agonists (GLP-1/GIP-RAs) induce marked weight loss (12%–18% compared with placebo) and improve cardiometabolic risk factors, functional status, and quality of life in individuals with obesity and CVD. GLP-1RAs reduce myocardial infarction, stroke, and cardiovascular mortality in individuals with diabetes.161 Initial results from the SELECT trial (Semaglutide Effects on Cardiovascular Outcomes in People With Overweight or Obesity) indicate that high-dose GLP-1RA causes a reduction in major adverse cardiovascular events in those with obesity and CVD, and the STEP-HFpEF trial (Research Study to Investigate How Well Semaglutide Works in People Living With Heart Failure and Obesity) will evaluate their effects in HFpEF.162 Bariatric surgery reduces major adverse cardiac events and mortality rate by >50% in individuals with prior ASCVD and HF.163 Integrated weight loss teams best facilitate patient-centered approaches to weight loss and may improve clinical outcomes.

The presence of MetS should trigger intensified lifestyle modification, with pharmacological therapy as needed to achieve risk factor control and improve cardiovascular outcomes. In those with hypertriglyceridemia and CVD, icosapent ethyl reduces CVD events and mortality and may be considered after statin therapy.66 In hypertension, a therapeutic goal for all patients is <130/80 mm Hg. ACE inhibitors/ARBs should be prioritized in patients with CVD and CKD or diabetes for cardiovascular and renal benefits.62 In HFrEF, calcium channel blockers for hypertension should be avoided. If residual elevated blood pressure persists in Black patients with HFrEF after the 4 pillars of GDMT, hydralazine/isosorbide should be considered for both hypertension control and improved HF morbidity and mortality.71

Diabetes and CVD

In patients with T2D and CVD, lifestyle modification improves risk factor control and quality of life. For all patients with HF, SGLT2 inhibitors are a fundamental component of GDMT. Across several randomized clinical trials of HF patients, SGLT2 inhibitor therapy improved quality of life and lowered the risk of hospitalized HF, cardiovascular mortality, and all-cause mortality.164–166 Despite SGLT2 inhibitor therapy being an antihyperglycemic therapy, similar results are seen in those with and without diabetes. Benefits are also seen in both HFpEF and HFrEF.167 GLP-1RA data in HF currently are relatively limited. In addition to favorable effects on weight and glycemia, mechanistic studies suggest potential benefits of GLP-1RAs in HFpEF on cardiac function and quality of life, but definitive trial data are pending.168 There are some concerns about potential deleterious effects of GLP-1RAs in HFrEF due to increases in heart rate and cAMP levels in cardiac myocytes, but data are inconclusive.169 Agents within the dipeptidyl peptidase 4 inhibitor and thiazolidinedione classes of antihyperglycemic agents have been linked to adverse effects in patients with HR; therefore, these medications are contraindicated in HF patients.

In patients with ASCVD, adding LDL-lowering therapies beyond maximally tolerated statin therapy may have a more powerful clinical effect in those with than those without T2D.141 Multiple clinical trials demonstrate that both GLP-1RA and SGLT2 inhibitors reduce risk for major adverse cardiovascular outcomes in patients with T2D and ASCVD.153,161 SGLT2 inhibitors additionally reduce the risk for HF hospitalization and worsening kidney function in patients with ASCVD, whereas GLP-1RAs have more potent effects than SGLT2 inhibitors on weight and HbA1c.170 These data support a comorbidity-based approach for selecting a cardioprotective antihyperglycemic therapy in those with diabetes and ASCVD, favoring GLP-1RA in those with severe obesity or marked hyperglycemia and SGLT2 inhibitors in those with CKD or coexisting HF.

Metformin is helpful for achieving glycemic targets but should be avoided in decompensated/unstable HF or for eGFR <30 mL·min−1·1.73 m−2 because of increased risk for lactic acidosis. Combination therapy with SGLT2 inhibitors and GLP-1RA, associated with lower CVD risk in observational studies, could be considered for combined HF and ASCVD or CVD with multiple or severely uncontrolled CKM risk factors.159


In patients with HF, SGLT2 inhibitors causes reductions in kidney disease progression, as well as HF hospitalizations and cardiovascular death.39,171,172 These outcomes are consistent regardless of diabetes status and ejection fraction.171,172 ACE inhibitors/ARBs are well known to reduce morbidity and mortality in HFrEF71; concomitantly, various trials have shown efficacy for preventing worsening renal function.173–175 Use of ACE inhibitors/ARBs and mineralocorticoid receptor antagonists may be complicated in CKD because of concerns about hypotension, hyperkalemia, and worsening renal function.176 An analysis of 6 randomized trials revealed that concomitant SGLT2 inhibitor use reduced the risk of serious hyperkalemia.177 Studies of angiotensin receptor/neprilysin inhibitor use revealed significantly decreased risk of death resulting from cardiovascular causes and hospitalization for HF, especially in HFrEF,178,179 while lowering the risk of worsening renal function and serious hyperkalemia.179,180 Additional data demonstrate that the renal benefits of angiotensin receptor/neprilysin inhibitor use are extended to HFpEF.181 The addition of potassium binders to combined use of SGLT2 inhibitor and angiotensin receptor/neprilysin inhibitor may be considered to optimize GDMT use in CKD, although evidence on clinical outcomes is uncertain.176,179 On the basis of hemodynamic responses to renin-angiotensin-aldosterone system inhibitors and SGLT2 inhibitors, there can be an expected 10% to 30% drop in eGFR when these medications are started, and reflexive discontinuation of these agents based on minor fluctuations of serum creatinine should be avoided.182,183

In patients with ASCVD, CKD is linked to higher risk. There is no evidence of significant adverse effects with higher doses of statins in CKD,184 and continuation of statins for ASCVD is recommended for cardiovascular risk reduction. ACE inhibitors/ARBs reduce morbidity and mortality in patients after acute coronary syndrome with left ventricular dysfunction185 and prevent worsening kidney function.173–175 Various trials have also shown cardiovascular and renal benefits for SGLT2 inhibitors with predominantly cardiovascular benefits for GLP-1RA reported at this time.39 Among patients with diabetic kidney disease optimized on renin-angiotensin system inhibition, finerenone has been shown to reduce both adverse cardiovascular and kidney events.149

AFib in CKM Syndrome

Extensive data link the CKM risk factors of obesity, hypertension, dyslipidemia, MetS, diabetes, and CKD to a greater risk for AFib and higher AFib burden. Consequently, guidelines generally recommend comprehensive control of these risk factors as part of AFib management. Because the CKM risk factors of hypertension and diabetes increase stroke risk in AFib, their presence favors the use of anticoagulation for stroke prophylaxis. Growing data and guidance support the use of dual oral anticoagulants in nonvalvular AFib, even in those with severe obesity or CKD, although dose reductions are typically needed in the latter because of decreased drug clearance. Lifestyle modification, particularly weight loss, and regular physical activity are associated with decreased AFib burden. In addition, preprocedural weight loss and treatment for obstructive sleep apnea may be linked to a lower risk for recurrent AFib after catheter ablation.186,187

Kidney Failure

Despite markedly elevated risk for CVD for patients with kidney failure on maintenance dialysis, evidence for CVD management in this population is scarce because of their limited inclusion in clinical trials. Given the high burden of HF in patients on maintenance dialysis, consideration should be given to more frequent dialysis (hemodialysis or peritoneal dialysis) as a result of beneficial effects demonstrated with respect to left ventricular mass, blood pressure control, and pill burden for antihypertensive medications. Peritoneal dialysis may be preferable in patients with HF, especially in those with lower blood pressure, given the ability to achieve volume control without significant intradialytic hypotension.188,189 In patients on hemodialysis, factoring in the dialyzability of GDMT therapies such as ACE inhibitors, β-blockers, and other antihypertensives is essential for optimal medical management.190 For patients on dialysis, statin initiation does not reduce the risk of future ASCVD events.191,192 However, in a post hoc analysis of patients with diabetes on dialysis, rosuvastatin use was associated with lower risk of adverse cardiovascular outcomes.193 Moreover, among individuals who are already on statins, statin continuation when transitioning to dialysis is associated with reduced risk of cardiovascular and all-cause mortality,194 with greater risk reduction seen when statins are combined with ezetimibe.195


A large body of evidence supports prevention and management approaches for individuals with CKM syndrome, as described previously. Nonetheless, several key gaps persist in the evidence for caring for the patient with CKM (Table 5).

Table 5. Gaps in the Prevention and Management Approaches for CKM Syndrome

Topic areaGaps
Interdisciplinary care approachDefining optimal approaches for collaborative and harmonized CKM care
 Optimal structure of the interdisciplinary team and roles of CKM coordinators in interprovider communication and patient navigation
 Optimal strategies for enhancing collaboration between primary providers and subspecialists
 Benefits of complementary value- and volume-based interdisciplinary care models
 Approaches to supporting interdisciplinary care across diverse clinical/geographic settings
 Impact of collaborative care approaches on CKM-related outcomes
Early-life preventionOptimal approaches for early life prevention
 Impact of maternal health interventions
 Impact of multilevel and family interventions
 Thresholds for starting advanced therapies (including obesity pharmacotherapies and metabolic surgery)
 Long-term clinical outcomes related to screening and prevention efforts in early life
Strategies to support weight lossOptimal strategies to support weight loss in clinical settings
 Targeting of obesity pharmacotherapies and associated impact on CVD outcomes
 Long-term approaches for obesity pharmacotherapies, including strategies for successful discontinuation
 Need for clinical trials of bariatric surgery in patients with CVD
 Utility and optimal deployment of integrated weight loss teams for supporting patient-centered approach to achieving weight reduction goals
Use of cardioprotective antihyperglycemic therapies in those with diabetes at risk for CVDClarifying approach to using SGLT2 inhibitors and GLP-1RAs in those with diabetes and without CVD
 Defining thresholds for use of cardioprotective antihyperglycemic therapy
 Prioritizing SGLT2 inhibitors vs GLP-1RA; need to validate the utility of a comorbidity-based approach for agent selection
 Establishing the utility and indications for co-utilization of SGLT2 inhibitors and GLP-1RA in the population at risk for CVD
Use of cardioprotective antihyperglycemic therapies in those with diabetes and existing CVDPrevalent ASCVD: both GLP-1RA and SGLT2 inhibitors recommended in guidelines; understanding which to prioritize and how
 Impact of using comorbidities (CKD, severe obesity, marked hyperglycemia) and concomitant HF to guide prioritization
Prevalent HF: when to consider adding GLP-1RA to SGLT2 inhibitors
 Impact of using comorbidities and coexisting ASCVD
 Defining efficacy and safety of GLP-1RA in HFpEF and HFrEF
Co-utilization of GLP-1RA and SGLT2 inhibitors: effectiveness and optimal targeting of co-utilization approach
Lipid-lowering therapies beyond statins in diabetes and high CKM riskWhen and how to use nonstatin therapies
 Statin+ezetimibe agreed on in high-risk primary prevention population; are there high-risk primary prevention subgroups in whom additional LDL-C lowering therapy is indicated?
 Use of icosapent ethyl may be considered for hypertriglyceridemia; need to define effective approaches for addressing residual ASCVD risk linked to elevated triglycerides
Management of CVD in patients with CKDLimited evidence regarding several aspects of GDMT in HF with eGFR <30 mL·min−1·1.73 m−2 due to limited inclusion in clinical trials
 Use of SGLT2 inhibitors and ARN inhibitors
 Interpretation of fluctuations in kidney function with GDMT
 Approach to GDMT titration and use of concurrent agents
 Criteria for multidisciplinary involvement for HF and high-risk CKD and impact on outcomes

ASCVD indicates atherosclerotic cardiovascular disease; ARN, angiotensin receptor/neprilysin; CKD, chronic kidney disease; CKM, cardiovascular-kidney-metabolic; CVD, cardiovascular disease; GDMT, guideline-directed medical therapy; GLP-1RA, glucagon-like peptide 1 receptor agonist; HF, heart failure; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; LDL-C, low-density lipoprotein cholesterol; and SGLT2, sodium-glucose cotransporter-2.

Interdisciplinary Care

Although there is a clear need for care models that support interdisciplinary collaboration in order to reduce care fragmentation for patients navigating a confluence of health conditions, the evidence for the impact of such approaches on clinical outcomes is just beginning to emerge. In addition, it is important to better understand how such models can be applied across diverse clinical and geographic settings with differing availability of health care resources, including subspecialists to accommodate patient referrals. Optimal strategies for supporting partnerships with primary care clinicians and patient-centered approaches to coordinating care also need to be better defined.

Early-Life Prevention

Prenatal exposures are known to influence offspring CKM health.196 However, the impact of interventions to improve maternal health on CKM profiles among children is not yet fully defined. Once CKM risk factors are present, management during childhood and adolescence can be challenging because the child, their community, and their environment need to be considered for optimally effective therapeutic interventions.197 This suggests that multimodal approaches to prevention and treatment should be considered.198 Family-based approaches may be protective against the development of obesity in young adulthood. Other multilevel interventions targeting the food and physical activity environments in addition to children and their support networks may enhance effectiveness, but further data are needed. Developing prevention and management strategies in childhood that are effective across diverse settings remains a key need. Although recent guidelines endorse the adjunctive use of obesity pharmacotherapies and bariatric surgery for children with obesity,91 the optimal targeting of such therapies in childhood remains unclear. It is also critical to acquire data on the long-term clinical outcomes related to CKM screening, staging, and therapeutic approaches in childhood, adolescence, and young adulthood.

Strategies to Support Lifestyle Changes and Weight Loss

Although options to support successful weight loss are expanding, many gaps remain. Newer obesity pharmacotherapies, particularly high-dose GLP-1RA and GLP1/GIP-RA agents, induce marked weight loss and improve metabolic risk factors,199,200 but the optimal targeting of these agents as adjuncts to lifestyle modification in the broad population with obesity is unclear. The impact of these obesity pharmacotherapies for reducing major adverse cardiac events in patients with obesity and CVD, but without diabetes, is being evaluated.162 Studies are also evaluating the impact of GLP-1RAs on symptoms, physical limitations, and exercise function in HFpEF.168 If these trials have positive results, patients with obesity and prevalent CVD might be prioritized for these agents. The long-term impact of these pharmacotherapies is unclear. In addition, the discontinuation of these agents is associated with weight regain,201 and strategies for successful weight maintenance with reductions or discontinuation of newer obesity pharmacotherapies are undefined. In controlled prospective studies, bariatric surgery markedly reduced major adverse cardiac events and mortality in those with and without CVD,163,202 but interventional trials are needed among those with CVD to confirm efficacy and to assess safety. Integrated multidisciplinary teams improve patient-centered approaches to lifestyle change and weight loss support, but more data are needed on the optimal structure and deployment of these teams and their impact on clinical outcomes. As part of this integrated approach, more effective engagement with stakeholders such as insurance companies and employers is needed to expand incentives for supporting positive lifestyle changes to positively affect clinical outcomes.

Cardioprotective Antihyperglycemic Therapies in Those at Risk for CVD

The cardioprotective therapies SGLT2 inhibitors and GLP-1RAs have revolutionized preventive care for individuals with diabetes. However, more clarity is needed on the targeting and prioritization of these antihyperglycemic agents in individuals with diabetes at risk for CVD. Although guidelines generally agree that these agents are indicated for those at high risk for CVD, the criteria for meeting this threshold are unclear. Approaches across guidelines are inconsistent and include the presence of comorbidities,145 the presence of diabetes-related complications or long diabetes duration,62,63,145 and the use of CVD risk calculators to define high risk62,63,71; further clarity and validation are needed. Furthermore, strategies for prioritizing the selection of SGLT2 inhibitors or GLP-1RAs in the at-risk population are not well defined. Prioritization based on comorbidities such as obesity for GLP-1RA or CKD for SGLT2 inhibitors is reasonable on the basis of the physiological effects of these agents, but this also requires validation. Risk calculators hold promise to further refine the selection, with high HF risk, for example, potentially favoring use of SGLT2 inhibitors.203 Subclinical ASCVD and HF could similarly guide selection of therapies. As the science related to pharmacogenomics matures further, it is possible that in the future knowledge of genetic variants may help refine the selection of antihyperglycemic therapies.

Co-utilization of SGLT2 inhibitors and GLP-1RA is recommended to decrease risk in high-risk patients,145 but the approach to delineating this subset of patients is unclear, and interventional trials demonstrating the cardiovascular benefits of combined SGLT2 inhibitors and GLP-1RAs in those at risk for CVD are lacking.204 Further data are urgently needed to guide prioritization of antihyperglycemic agents in individuals with diabetes at risk for CVD.

Cardioprotective Antihyperglycemic Therapies in Those With CVD

Cardiovascular outcome trials of SGLT2 inhibitors and GLP-1RAs demonstrate that individuals with existing CVD derive the greatest clinical benefit from these therapies.165,205 In individuals with diabetes and ASCVD, the approach to prioritizing selection of SGLT2 inhibitors versus GLP-1RAs is unclear because these therapies have not been directly compared in clinical trials. It is possible that individuals with coexisting severe obesity or uncontrolled hyperglycemia may benefit most from GLP-1RAs, whereas those with CKD or concomitant HF will benefit most from SGLT2 inhibitors, but the clinical utility of such an approach needs to be verified. Furthermore, the approach to selecting the best antihyperglycemic agent in patients with diabetes and ASCVD but without such comorbidities is unclear. Although co-utilization of SGLT2 inhibitors and GLP-1RA has been associated with improved clinical outcomes in observational studies and is suggested in clinical guidelines,62,63,76 interventional data are lacking, and the group who benefits most from such an approach is undefined. Among individuals with HF, for whom SGLT2 inhibitors are standard therapy, the optimal criteria for adding GLP-1RAs such as coexisting ASCVD, multiple comorbidities, or high levels of excess weight/glycemia should be further investigated and clarified. Further data are also needed on whether GLP-1RA use is similarly safe and effective in patients with HFpEF and HFrEF.

Lipid-Lowering Therapies Beyond Statins in Diabetes and High CKM Risk

Management of dyslipidemia is at the heart of ASCVD reduction for people with CVD and diabetes, who frequently fall into a very high-risk category because of high event rates. For individuals with diabetes and ASCVD, high-intensity statins are recommended first-line lipid-lowering therapy. Based on clinical trial data, both American and European guidelines support the addition of ezetimibe, followed by PCSK9 inhibitors when needed, as reasonable for very high-risk patients with diabetes and ASCVD on maximally tolerated statins who have not achieved a 50% reduction of LDL-C or with an LDL-C >70 mg/dL.62,63 American and European guidelines differ on the use of PCSK9 inhibitors for primary prevention; European guidelines support consideration of PCSK9 inhibitors in very high-risk patients without familial hypercholesterolemia not meeting LDL-C goals.63 In the primary prevention population, there are key questions about the value and net benefit of adding PCSK9 inhibitors or other novel LDL-lowering therapies to statins and ezetimibe.63 Further research is needed to delineate whether there are subgroups of very high-risk primary prevention patients for whom such an approach could be both beneficial and cost-effective.

Hypertriglyceridemia is commonly encountered in diabetes, is a component of MetS, and is linked to greater ASCVD risk. For patients with hypertriglyceridemia in the setting of ASCVD or diabetes with additional comorbidities, data support considering the addition of icosapent ethyl (also known as eicosapentaenoic acid) to statin therapy for further lowering ASCVD risk.137 There have been conflicting results from trials of fish oil supplementation, and there are questions about the extent to which harm from the use of mineral oil in the control arm of the REDUCE-IT trial (Reduction of Cardiovascular Events With Icosapent Ethyl—Intervention Trial) contributed to the favorable results observed for eicosapentaenoic acid in that study. However, consistent differences between studies of eicosapentaenoic acid and eicosapentaenoic acid/docosahexaenoic acid suggest that physiological differences between these supplements likely primarily account for disparate outcomes of clinical trials. In addition, it is unclear why lesser or no risk reduction is seen in fibrate trials in patients with hypertriglyceridemia despite greater impact on triglycerides than icosapent ethyl.206 It has been speculated that this may be linked to greater reduction of apolipoprotein B concentrations with icosapent ethyl,207 but more research on this topic is needed.

Management of CVD in Patients With CKD

Most trials for GDMT in HF and CKD do not have adequate representation, especially for patients in the more advanced stages of CKD (eGFR<30 mL·min−1·1.73 m−2).176 Hence, evidence for most GDMT for HF in patients with advanced CKD is limited.71,208 There is also limited guidance with respect to interpretation of fluctuation of kidney function changes seen with decongestion and initiation/titration of GDMT in HF,183 with considerable misinterpretation of expected fluctuations in markers of glomerular filtration as acute kidney injury. This results in the reflexive de-escalation of GDMT for HF, especially in the setting of CKD stage 4 and 5. Last, given concerns about hyperkalemia and the perception of worsening kidney function in CKD, there is no standard approach to the initiation and titration of GDMT in HF with CKD.71 Comparative-effectiveness data for multidisciplinary involvement of subspecialty services and allied health personnel for GDMT optimization compared with usual care in patients with HF and CKD remain understudied at this time.209 Data on the management of ASCVD in CKD are also lacking because of the underrepresentation of patients with CKD in CVD trials. Therefore, evidence for continued use of various components of guideline support care for ASCVD in advanced CKD stages is lacking.210


CKM syndrome reflects the impact of multisystem pathophysiological interrelationships, nested within multilevel SDOH, the confluence of which determines clinical outcomes. To achieve new frontiers in our understanding of CKM syndrome, our scientific approach will need to reflect this fundamental interdependence. Research efforts must involve collaboration across specialties, ensuring that perspectives from pediatrics, adult primary care specialties, nephrology, cardiology, and endocrinology are equitably incorporated. It is important that clinical research studies include the full spectrum of patients with CKM syndrome, with a particular need for inclusion of patients with CKD who have traditionally been underrepresented in cardiovascular trials. It is also critical that research studies include greater proportions of underrepresented racial and ethnic groups and postmenopausal women to ensure greater generalizability of investigative findings. Cross-disciplinary research is critical, with basic, translational, clinical, and epidemiological investigations having potential to provide complementary insights into mechanistic pathways, populations at risk, prediction strategies, and novel therapeutic approaches.

Many of the key considerations for CKM syndrome care moving forward relate to where, when, and how to deploy an increasing array of cardioprotective therapies with multisystem effects. In navigating these decisions, it is important to consider short- and long-term risk, net clinical benefit, the anticipated duration of therapies, access to care, cost-effectiveness, and patient preferences and values. Risk algorithms that reflect the multiple adverse cardiovascular and kidney outcomes that occur with increased frequency among patients with CKM syndrome can help to better target therapies to subpopulations in whom they will have the greatest impact. With the present low rates of control of individual CKM risk factors, there is a need to define optimal strategies for prioritizing and managing multiple risk factors at various stages of CKM syndrome. Real-world effectiveness and implementation studies, with both quantitative and qualitative components, will be needed to refine CKM care models in the population.

In addition to ongoing efforts to optimize CKM care, it is crucial that there are concurrent efforts to address the historic influx of patients with CKM syndrome, driven by epidemics of obesity and diabetes. This necessitates enhanced approaches to preserving ideal cardiovascular health across the life course and across diverse populations. Enhanced CKM screening strategies across the life course, particularly for those at highest risk, will facilitate early interventions to avoid the progression of CKM syndrome and to mitigate risk for CVD events and kidney failure. Prevention efforts must extend beyond clinical settings to consider the social context in which individuals live, work, eat, and play. There is also a need to address the interplay between SDOH and biological predisposing factors, which can, in combination, have a profound impact on CKM-related risk. Holistic approaches to both prevention and management are needed to fully and equitably address the population impact of CKM syndrome, with the goal of advancing cardiovascular health for all.



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This statement was approved by the American Heart Association Science Advisory and Coordinating Committee on August 25, 2023, and the American Heart Association Executive Committee on September 7, 2023. A copy of the document is available at by using either “Search for Guidelines & Statements” or the “Browse by Topic” area. To purchase additional reprints, call 215-356-2721 or email

The American Heart Association requests that this document be cited as follows: Ndumele CE, Neeland IJ, Tuttle KR, Chow SL, Mathew RO, Khan SS, Coresh J, Baker-Smith CM, Carnethon MR, Després J-P, Ho JE, Joseph JJ, Kernan WN, Khera A, Kosiborod MN, Lekavich CL, Lewis EF, Lo KB, Ozkan B, Palaniappan LP, Patel SS, Pencina MJ, Powell-Wiley TM, Sperling LS, Virani SS, Wright JT, Rajgopal Singh R, Elkind MSV, Rangaswami J; on behalf of the American Heart Association. A synopsis of the evidence for the science and clinical management of cardiovascular-kidney-metabolic (CKM) syndrome: a scientific statement from the American Heart Association. Circulation. 2023;148:1636–1664. doi: 10.1161/CIR.0000000000001186

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  • 1. Ndumele CE, Rangaswami J, Chow SL, Neeland IJ, Tuttle KR, Khan SS, Coresh J, Mathew RO, Baker-Smith CM, Carnethon MR, et al; on behalf of the American Heart Association. Cardiovascular-kidney-metabolic health: a presidential advisory from the American Heart Association [published online ahead of print October 9, 2023]. Circulation. doi: 10.1161/CIR.0000000000001184LinkGoogle Scholar
  • 2. Powell-Wiley TM, Poirier P, Burke LE, Despres JP, Gordon-Larsen P, Lavie CJ, Lear SA, Ndumele CE, Neeland IJ, Sanders P, et al; on behalf of the American Heart Association Council on Lifestyle and Cardiometabolic Health; Council on Cardiovascular and Stroke Nursing; Council on Clinical Cardiology; Council on Epidemiology and Prevention; and Stroke Council. Obesity and cardiovascular disease: a scientific statement from the American Heart Association.Circulation. 2021; 143:e984–e1010. doi: 10.1161/CIR.0000000000000973LinkGoogle Scholar
  • 3. Rana MN, Neeland IJ. Adipose tissue inflammation and cardiovascular disease: an update.Curr Diab Rep. 2022; 22:27–37. doi: 10.1007/s11892-021-01446-9CrossrefMedlineGoogle Scholar
  • 4. Despres JP, Carpentier AC, Tchernof A, Neeland IJ, Poirier P. Management of obesity in cardiovascular practice: JACC focus seminar.J Am Coll Cardiol. 2021; 78:513–531. doi: 10.1016/j.jacc.2021.05.035CrossrefMedlineGoogle Scholar
  • 5. Neeland IJ, Ross R, Despres JP, Matsuzawa Y, Yamashita S, Shai I, Seidell J, Magni P, Santos RD, Arsenault B, et al. Visceral and ectopic fat, atherosclerosis, and cardiometabolic disease: a position statement.Lancet Diabetes Endocrinol. 2019; 7:715–725. doi: 10.1016/S2213-8587(19)30084-1CrossrefMedlineGoogle Scholar
  • 6. Yano Y, Vongpatanasin W, Ayers C, Turer A, Chandra A, Carnethon MR, Greenland P, de Lemos JA, Neeland IJ. Regional fat distribution and blood pressure level and variability: the Dallas Heart Study.Hypertension. 2016; 68:576–583. doi: 10.1161/HYPERTENSIONAHA.116.07876LinkGoogle Scholar
  • 7. Rinella ME, Lazarus JV, Ratziu V, Francque SM, Sanyal AJ, Kanwal F, Romero D, Abdelmalek MF, Anstee QM, Arab JP, et al. A multi-society Delphi consensus statement on new fatty liver disease nomenclature [published online June 20, 2023].Hepatology. doi: 10.1097/HEP.0000000000000520. Scholar
  • 8. Wong RJ, Singal AK. Trends in liver disease etiology among adults awaiting liver transplantation in the United States, 2014-2019.JAMA Netw Open. 2020; 3:e1920294. doi: 10.1001/jamanetworkopen.2019.20294CrossrefMedlineGoogle Scholar
  • 9. Sheng X, Qiu C, Liu H, Gluck C, Hsu JY, He J, Hsu CY, Sha D, Weir MR, Isakova T, et al. Systematic integrated analysis of genetic and epigenetic variation in diabetic kidney disease.Proc Natl Acad Sci U S A. 2020; 117:29013–29024. doi: 10.1073/pnas.2005905117CrossrefMedlineGoogle Scholar
  • 10. Wilson PW, D’Agostino RB, Parise H, Sullivan L, Meigs JB. Metabolic syndrome as a precursor of cardiovascular disease and type 2 diabetes mellitus.Circulation. 2005; 112:3066–3072. doi: 10.1161/CIRCULATIONAHA.105.539528LinkGoogle Scholar
  • 11. Tuttle KR, Agarwal R, Alpers CE, Bakris GL, Brosius FC, Kolkhof P, Uribarri J. Molecular mechanisms and therapeutic targets for diabetic kidney disease.Kidney Int. 2022; 102:248–260. doi: 10.1016/j.kint.2022.05.012CrossrefMedlineGoogle Scholar
  • 12. Amdur RL, Feldman HI, Dominic EA, Anderson AH, Beddhu S, Rahman M, Wolf M, Reilly M, Ojo A, Townsend RR, et al. Use of measures of inflammation and kidney function for prediction of atherosclerotic vascular disease events and death in patients with CKD: findings from the CRIC study.Am J Kidney Dis. 2019; 73:344–353. doi: 10.1053/j.ajkd.2018.09.012CrossrefMedlineGoogle Scholar
  • 13. Ridker PM, Tuttle KR, Perkovic V, Libby P, MacFadyen JG. Inflammation drives residual risk in chronic kidney disease: a CANTOS substudy.Eur Heart J. 2022; 43:4832–4844. doi: 10.1093/eurheartj/ehac444CrossrefMedlineGoogle Scholar
  • 14. Ridker PM, Luscher TF. Anti-inflammatory therapies for cardiovascular disease.Eur Heart J. 2014; 35:1782–1791. doi: 10.1093/eurheartj/ehu203CrossrefMedlineGoogle Scholar
  • 15. Pichler R, Afkarian M, Dieter BP, Tuttle KR. Immunity and inflammation in diabetic kidney disease: translating mechanisms to biomarkers and treatment targets.Am J Physiol Renal Physiol. 2017; 312:F716–F731. doi: 10.1152/ajprenal.00314.2016CrossrefMedlineGoogle Scholar
  • 16. Rangaswami J, Bhalla V, Blair JEA, Chang TI, Costa S, Lentine KL, Lerma EV, Mezue K, Molitch M, Mullens W, et al. Cardiorenal syndrome: classification, pathophysiology, diagnosis, and treatment strategies: a scientific statement from the American Heart Association.Circulation. 2019; 139:e840–e878. doi: 10.1161/CIR.0000000000000664LinkGoogle Scholar
  • 17. Zhao L, Zou Y, Liu F. Transforming growth factor-beta1 in diabetic kidney disease.Front Cell Dev Biol. 2020; 8:187. doi: 10.3389/fcell.2020.00187CrossrefMedlineGoogle Scholar
  • 18. Shahzad K, Bock F, Dong W, Wang H, Kopf S, Kohli S, Al-Dabet MM, Ranjan S, Wolter J, Wacker C, et al. Nlrp3-inflammasome activation in non-myeloid-derived cells aggravates diabetic nephropathy.Kidney Int. 2015; 87:74–84. doi: 10.1038/ki.2014.271CrossrefMedlineGoogle Scholar
  • 19. Sakai N, Wada T. Revisiting inflammation in diabetic nephropathy: the role of the Nlrp3 inflammasome in glomerular resident cells.Kidney Int. 2015; 87:12–14. doi: 10.1038/ki.2014.322CrossrefMedlineGoogle Scholar
  • 20. Wong MG, Perkovic V, Chalmers J, Woodward M, Li Q, Cooper ME, Hamet P, Harrap S, Heller S, MacMahon S, et al. Long-term benefits of intensive glucose control for preventing end-stage kidney disease: ADVANCE-ON.Diabetes Care. 2016; 39:694–700. doi: 10.2337/dc15-2322CrossrefMedlineGoogle Scholar
  • 21. Kato M, Natarajan R. Epigenetics and epigenomics in diabetic kidney disease and metabolic memory.Nat Rev Nephrol. 2019; 15:327–345. doi: 10.1038/s41581-019-0135-6CrossrefMedlineGoogle Scholar
  • 22. Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization.N Engl J Med. 2004; 351:1296–1305. doi: 10.1056/NEJMoa041031CrossrefMedlineGoogle Scholar
  • 23. van der Velde M, Matsushita K, Coresh J, Astor BC, Woodward M, Levey A, de Jong P, Gansevoort RT; Chronic Kidney Disease Prognosis Consortium. Lower estimated glomerular filtration rate and higher albuminuria are associated with all-cause and cardiovascular mortality: a collaborative meta-analysis of high-risk population cohorts.Kidney Int. 2011; 79:1341–1352. doi: 10.1038/ki.2010.536CrossrefMedlineGoogle Scholar
  • 24. GBD 2013 Mortality and Causes of Death Collaborators. Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.Lancet. 2015; 385:117–171. doi: 10.1016/S0140-6736(14)61682-2CrossrefMedlineGoogle Scholar
  • 25. Packham DK, Alves TP, Dwyer JP, Atkins R, de Zeeuw D, Cooper M, Shahinfar S, Lewis JB, Lambers Heerspink HJ. Relative incidence of ESRD versus cardiovascular mortality in proteinuric type 2 diabetes and nephropathy: results from the DIAMETRIC (Diabetes Mellitus Treatment for Renal Insufficiency Consortium) database.Am J Kidney Dis. 2012; 59:75–83. doi: 10.1053/j.ajkd.2011.09.017CrossrefMedlineGoogle Scholar
  • 26. Afkarian M, Sachs MC, Kestenbaum B, Hirsch IB, Tuttle KR, Himmelfarb J, de Boer IH. Kidney disease and increased mortality risk in type 2 diabetes.J Am Soc Nephrol. 2013; 24:302–308. doi: 10.1681/ASN.2012070718CrossrefMedlineGoogle Scholar
  • 27. Benjamin EJ, Blaha MJ, Chiuve SE, Cushman M, Das SR, Deo R, de Ferranti SD, Floyd J, Fornage M, Gillespie C, et al. Heart disease and stroke statistics–2017 update: a report from the American Heart Association [published corrections appear in Circulation. 2017;135:e646 and Circulation. 2017;136:e196].Circulation. 2017; 135:e146–e603. doi: 10.1161/CIR.0000000000000485LinkGoogle Scholar
  • 28. Burrows NR, Koyama A, Pavkov ME. reported cases of end-stage kidney disease–United States, 2000-2019.MMWR Morb Mortal Wkly Rep. 2022; 71:412–415. doi: 10.15585/mmwr.mm7111a3CrossrefMedlineGoogle Scholar
  • 29. USRD System. 2022 USRDS annual data report: epidemiology of kidney disease in the United States.Accessed June 1, 2023. Scholar
  • 30. Harding JL, Pavkov ME, Magliano DJ, Shaw JE, Gregg EW. Global trends in diabetes complications: a review of current evidence.Diabetologia. 2019; 62:3–16. doi: 10.1007/s00125-018-4711-2CrossrefMedlineGoogle Scholar
  • 31. Gregg EW, Li Y, Wang J, Burrows NR, Ali MK, Rolka D, Williams DE, Geiss L. Changes in diabetes-related complications in the United States, 1990-2010.N Engl J Med. 2014; 370:1514–1523. doi: 10.1056/NEJMoa1310799CrossrefMedlineGoogle Scholar
  • 32. Koye DN, Magliano DJ, Nelson RG, Pavkov ME. The global epidemiology of diabetes and kidney disease.Adv Chronic Kidney Dis. 2018; 25:121–132. doi: 10.1053/j.ackd.2017.10.011CrossrefMedlineGoogle Scholar
  • 33. Friedman AN, Schauer PR, Beddhu S, Kramer H, le Roux CW, Purnell JQ, Sunwold D, Tuttle KR, Jastreboff AM, Kaplan LM. Obstacles and opportunities in managing coexisting obesity and CKD: report of a scientific workshop cosponsored by the National Kidney Foundation and The Obesity Society.Am J Kidney Dis. 2022; 80:783–793. doi: 10.1053/j.ajkd.2022.06.007CrossrefMedlineGoogle Scholar
  • 34. Speer T, Dimmeler S, Schunk SJ, Fliser D, Ridker PM. Targeting innate immunity-driven inflammation in CKD and cardiovascular disease.Nat Rev Nephrol. 2022; 18:762–778. doi: 10.1038/s41581-022-00621-9CrossrefMedlineGoogle Scholar
  • 35. Chen J, Budoff MJ, Reilly MP, Yang W, Rosas SE, Rahman M, Zhang X, Roy JA, Lustigova E, Nessel L, et al. Coronary artery calcification and risk of cardiovascular disease and death among patients with chronic kidney disease.JAMA Cardiol. 2017; 2:635–643. doi: 10.1001/jamacardio.2017.0363CrossrefMedlineGoogle Scholar
  • 36. American Diabetes Association. Peripheral arterial disease in people with diabetes.Diabetes Care. 2003; 26:3333–3341. doi: 10.2337/diacare.26.12.3333CrossrefMedlineGoogle Scholar
  • 37. Beckman JA, Schneider PA, Conte MS. Advances in revascularization for peripheral artery disease: revascularization in PAD.Circ Res. 2021; 128:1885–1912. doi: 10.1161/CIRCRESAHA.121.318261LinkGoogle Scholar
  • 38. Covic A, Vervloet M, Massy ZA, Torres PU, Goldsmith D, Brandenburg V, Mazzaferro S, Evenepoel P, Bover J, Apetrii M, et al. Bone and mineral disorders in chronic kidney disease: implications for cardiovascular health and ageing in the general population.Lancet Diabetes Endocrinol. 2018; 6:319–331. doi: 10.1016/S2213-8587(17)30310-8CrossrefMedlineGoogle Scholar
  • 39. Rangaswami J, Bhalla V, de Boer IH, Staruschenko A, Sharp JA, Singh RR, Lo KB, Tuttle K, Vaduganathan M, Ventura H, et al; on behalf of the American Heart Association Council on the Kidney in Cardiovascular Disease; Council on Arteriosclerosis, Thrombosis and Vascular Biology; Council on Cardiovascular and Stroke Nursing; Council on Clinical Cardiology; and Council on Lifestyle and Cardiometabolic Health. Cardiorenal protection with the newer antidiabetic agents in patients with diabetes and chronic kidney disease: a scientific statement from the American Heart Association [published corrections appear in Circulation. 2020;142:e304 and Circulation. 2021;143:e1019–1020].Circulation. 2020; 142:e265–e286. doi: 10.1161/CIR.0000000000000920LinkGoogle Scholar
  • 40. Zalunardo N, Tuttle KR. Atherosclerotic renal artery stenosis: current status and future directions.Curr Opin Nephrol Hypertens. 2004; 13:613–621. doi: 10.1097/00041552-200411000-00006CrossrefMedlineGoogle Scholar
  • 41. Safian RD. Renal artery stenosis.Prog Cardiovasc Dis. 2021; 65:60–70. doi: 10.1016/j.pcad.2021.03.003CrossrefMedlineGoogle Scholar
  • 42. Fakhry M, Sidhu MS, Bangalore S, Mathew RO. Accelerated and intensified calcific atherosclerosis and microvascular dysfunction in patients with chronic kidney disease.Rev Cardiovasc Med. 2020; 21:157–162. doi: 10.31083/j.rcm.2020.02.99CrossrefMedlineGoogle Scholar
  • 43. Baker-Smith CM, Yang W, McDuffie MJ, Nescott EP, Wolf BJ, Wu CH, Zhang Z, Akins RE. Association of area deprivation with primary hypertension diagnosis among youth Medicaid recipients in Delaware.JAMA Netw Open. 2023; 6:e233012. doi: 10.1001/jamanetworkopen.2023.3012CrossrefMedlineGoogle Scholar
  • 44. Borlaug BA, Sharma K, Shah SJ, Ho JE. Heart failure with preserved ejection fraction: JACC scientific statement.J Am Coll Cardiol. 2023; 81:1810–1834. doi: 10.1016/j.jacc.2023.01.049CrossrefMedlineGoogle Scholar
  • 45. Mongraw-Chaffin M, Foster MC, Anderson CAM, Burke GL, Haq N, Kalyani RR, Ouyang P, Sibley CT, Tracy R, Woodward M, et al. Metabolically healthy obesity, transition to metabolic syndrome, and cardiovascular risk.J Am Coll Cardiol. 2018; 71:1857–1865. doi: 10.1016/j.jacc.2018.02.055CrossrefMedlineGoogle Scholar
  • 46. Despres JP. Body fat distribution and risk of cardiovascular disease: an update.Circulation. 2012; 126:1301–1313. doi: 10.1161/CIRCULATIONAHA.111.067264LinkGoogle Scholar
  • 47. Zhu Y, Sidell MA, Arterburn D, Daley MF, Desai J, Fitzpatrick SL, Horberg MA, Koebnick C, McCormick E, Oshiro C, et al. Racial/ethnic disparities in the prevalence of diabetes and prediabetes by BMI: Patient Outcomes Research To Advance Learning (PORTAL) multisite cohort of adults in the U.S.Diabetes Care. 2019; 42:2211–2219. doi: 10.2337/dc19-0532CrossrefMedlineGoogle Scholar
  • 48. Powell-Wiley TM, Baumer Y, Baah FO, Baez AS, Farmer N, Mahlobo CT, Pita MA, Potharaju KA, Tamura K, Wallen GR. Social determinants of cardiovascular disease.Circ Res. 2022; 130:782–799. doi: 10.1161/CIRCRESAHA.121.319811LinkGoogle Scholar
  • 49. Hill-Briggs F, Adler NE, Berkowitz SA, Chin MH, Gary-Webb TL, Navas-Acien A, Thornton PL, Haire-Joshu D. Social determinants of health and diabetes: a scientific review.Diabetes Care. 2020; 44:258–279. doi: 10.2337/dci20-0053CrossrefMedlineGoogle Scholar
  • 50. Carpenter CL, Yan E, Chen S, Hong K, Arechiga A, Kim WS, Deng M, Li Z, Heber D. Body fat and body-mass index among a multiethnic sample of college-age men and women.J Obes. 2013; 2013:790654. doi: 10.1155/2013/790654CrossrefMedlineGoogle Scholar
  • 51. Baccarelli AA, Ordovas J. Epigenetics of early cardiometabolic disease: mechanisms and precision medicine.Circ Res. 2023; 132:1648–1662. doi: 10.1161/CIRCRESAHA.123.322135LinkGoogle Scholar
  • 52. Schuster NA, Hoogendijk EO, Kok AAL, Twisk JWR, Heymans MW. Ignoring competing events in the analysis of survival data may lead to biased results: a nonmathematical illustration of competing risk analysis.J Clin Epidemiol. 2020; 122:42–48. doi: 10.1016/j.jclinepi.2020.03.004CrossrefMedlineGoogle Scholar
  • 53. Cooper H, Wells S, Mehta S. Are competing-risk models superior to standard Cox models for predicting cardiovascular risk in older adults? Analysis of a whole-of-country primary prevention cohort aged >/=65 years.Int J Epidemiol. 2022; 51:604–614. doi: 10.1093/ije/dyab116CrossrefMedlineGoogle Scholar
  • 54. Huebner M, Wolkewitz M, Enriquez-Sarano M, Schumacher M. Competing risks need to be considered in survival analysis models for cardiovascular outcomes.J Thorac Cardiovasc Surg. 2017; 153:1427–1431. doi: 10.1016/j.jtcvs.2016.12.039CrossrefMedlineGoogle Scholar
  • 55. Shastri S, Tangri N, Tighiouart H, Beck GJ, Vlagopoulos P, Ornt D, Eknoyan G, Kusek JW, Herzog C, Cheung AK, et al. Predictors of sudden cardiac death: a competing risk approach in the hemodialysis study.Clin J Am Soc Nephrol. 2012; 7:123–130. doi: 10.2215/CJN.06320611CrossrefMedlineGoogle Scholar
  • 56. Al-Wahsh H, Tangri N, Quinn R, Liu P, Ferguson T, Fiocco M, Lam NN, Tonelli M, Ravani P. Accounting for the competing risk of death to predict kidney failure in adults with stage 4 chronic kidney disease.JAMA Netw Open. 2021; 4:e219225. doi: 10.1001/jamanetworkopen.2021.9225CrossrefMedlineGoogle Scholar
  • 57. Charytan DM, Zelevinsky K, Wolf R, Normand ST. All-cause mortality and progression to end-stage kidney disease following percutaneous revascularization or surgical coronary revascularization in patients with CKD.Kidney Int Rep. 2021; 6:1580–1591. doi: 10.1016/j.ekir.2021.03.882CrossrefMedlineGoogle Scholar
  • 58. ElSayed NA, Aleppo G, Aroda VR, Bannuru RR, Brown FM, Bruemmer D, Collins BS, Hilliard ME, Isaacs D, Johnson EL, et al. 11: Chronic kidney disease and risk management: Standards of Care in Diabetes–2023.Diabetes Care. 2023; 46:S191–S202. doi: 10.2337/dc23-S011CrossrefMedlineGoogle Scholar
  • 59. Weir MR. Microalbuminuria and cardiovascular disease.Clin J Am Soc Nephrol. 2007; 2:581–590. doi: 10.2215/CJN.03190906CrossrefMedlineGoogle Scholar
  • 60. Wilson AC, Mitsnefes MM. Cardiovascular disease in CKD in children: update on risk factors, risk assessment, and management.Am J Kidney Dis. 2009; 54:345–360. doi: 10.1053/j.ajkd.2009.04.027CrossrefMedlineGoogle Scholar
  • 61. Joseph JJ, Deedwania P, Acharya T, Aguilar D, Bhatt DL, Chyun DA, Di Palo KE, Golden SH, Sperling LS, et al; on behalf of the American Heart Association Diabetes Committee of the Council on Lifestyle and Cardiometabolic Health; Council on Arteriosclerosis, Thrombosis and Vascular Biology; Council on Clinical Cardiology; and Council on Hypertension. Comprehensive management of cardiovascular risk factors for adults with type 2 diabetes: a scientific statement from the American Heart Association.Circulation. 2022; 145:e722–e759. doi: 10.1161/CIR.0000000000001040LinkGoogle Scholar
  • 62. Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn EJ, Himmelfarb CD, Khera A, Lloyd-Jones D, McEvoy JW, et al. 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines [published corrections appear in Circulation. 2019;140:e649–e650, Circulation. 2020;141:e60, and Circulation. 2020;141:e774].Circulation. 2019; 140:e596–e646. doi: 10.1161/CIR.0000000000000678LinkGoogle Scholar
  • 63. Visseren FLJ, Mach F, Smulders YM, Carballo D, Koskinas KC, Back M, Benetos A, Biffi A, Boavida JM, Capodanno D, et al. 2021 ESC guidelines on cardiovascular disease prevention in clinical practice.Eur Heart J. 2021; 42:3227–3337. doi: 10.1093/eurheartj/ehab484CrossrefMedlineGoogle Scholar
  • 64. 2023 Standards of Medical Care in Diabetes.Diabetes Care. 2023; 46(suppl 1):S1–S280. Scholar
  • 65. Whelton PK, Carey RM, Aronow WS, Casey DE, Collins KJ, Dennison Himmelfarb C, DePalma SM, Gidding S, Jamerson KA, Jones DW, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.Hypertension. 2018; 71:e13–e115. doi: 10.1161/HYP.0000000000000065LinkGoogle Scholar
  • 66. Grundy SM, Stone NJ, Bailey AL, Beam C, Birtcher KK, Blumenthal RS, Braun LT, de Ferranti S, Faiella-Tommasino J, Forman DE, et al. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA guideline on the management of blood cholesterol: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines [published corrections appear in Circulation. 2019;139:e1182–e1186 and Circulation. 2023;148:e5].Circulation. 2019; 139:e1082–e1143. doi: 10.1161/CIR.0000000000000625LinkGoogle Scholar
  • 67. Jensen MD, Ryan DH, Apovian CM, Ard JD, Comuzzie AG, Donato KA, Hu FB, Hubbard VS, Jakicic JM, Kushner RF, et al. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and The Obesity Society [published correction appears in Circulation. 2014;129(suppl 2):S139–S140].Circulation. 2014; 129(suppl 2):S102–S138. doi: 10.1161/01.cir.0000437739.71477.eeLinkGoogle Scholar
  • 68. Hall ME, Cohen JB, Ard JD, Egan BM, Hall JE, Lavie CJ, Ma J, Ndumele CE, Schauer PR, Shimbo D; on behalf of the American Heart Association Council on Hypertension; Council on Arteriosclerosis, Thrombosis and Vascular Biology; Council on Lifestyle and Cardiometabolic Health; and Stroke Council. Weight-loss strategies for prevention and treatment of hypertension: a scientific statement from the American Heart Association.Hypertension. 2021; 78:e38–e50. doi: 10.1161/HYP.0000000000000202LinkGoogle Scholar
  • 69. Kidney Disease: Improving Global Outcomes Diabetes Work Group. KDIGO 2022 clinical practice guideline for diabetes management in chronic kidney disease.Kidney Int. 2022; 102:S1–S127. doi: 10.1016/j.kint.2022.06.008CrossrefMedlineGoogle Scholar
  • 70. Kidney Disease: Improving Global Outcomes (KDIGO) Lipid Work Group. Kidney Disease: Improving Global Outcomes (KDIGO) clinical practice guideline for lipid management in chronic kidney disease.Kidney Int Suppl. 2013; 3:259–305.Google Scholar
  • 71. Heidenreich PA, Bozkurt B, Aguilar D, Allen LA, Byun JJ, Colvin MM, Deswal A, Drazner MH, Dunlay SM, Evers LR, et al. 2022 AHA/ACC/HFSA guideline for the management of heart failure: a report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines [published corrections appear in Circulation. 2022;145:e1033, Circulation. 2022;146:e185, and Circulation. 2023;147:e674].Circulation. 2022; 145:e895–e1032. doi: 10.1161/CIR.0000000000001063LinkGoogle Scholar
  • 72. McDonagh TA, Metra M, Adamo M, Gardner RS, Baumbach A, Bohm M, Burri H, Butler J, Celutkiene J, Chioncel O, et al. 2021 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure.Eur Heart J. 2021; 42:3599–3726. doi: 10.1093/eurheartj/ehab368CrossrefMedlineGoogle Scholar
  • 73. Hindricks G, Potpara T, Dagres N, Arbelo E, Bax JJ, Blomstrom-Lundqvist C, Boriani G, Castella M, Dan G-A, Dilaveris PE, et al. 2020 ESC guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS).Eur Heart J. 2021; 42:373–498. doi: 10.1093/eurheartj/ehaa612CrossrefMedlineGoogle Scholar
  • 74. January CT, Wann LS, Calkins H, Chen LY, Cigarroa JE, Cleveland JC, Ellinor PT, Ezekowitz MD, Field ME, Furie KL, et al. 2019 AHA/ACC/HRS focused update of the 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society [published correction appears in Circulation. 2019;140:e285].Circulation. 2019; 140:e125–e151. doi: 10.1161/CIR.0000000000000665LinkGoogle Scholar
  • 75. Eknoyan G, Lameire N, Eckardt K, Kasiske B, Wheeler D, Levin A, Stevens PE, Bilous RW, Lamb EJ, Coresh J. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease.Kidney Int. 2013; 3:5–14.Google Scholar
  • 76. ElSayed NA, Aleppo G, Aroda VR, Bannuru RR, Brown FM, Bruemmer D, Collins BS, Das SR, Hilliard ME, Isaacs D, et al. 10: Cardiovascular disease and risk management: Standards of Care in Diabetes–2023.Diabetes Care. 2023; 46:S158–S190. doi: 10.2337/dc23-S010CrossrefMedlineGoogle Scholar
  • 77. Kidney Disease: Improving Global Outcomes Blood Pressure Work Group. KDIGO 2021 clinical practice guideline for the management of blood pressure in chronic kidney disease.Kidney Int. 2021; 99:S1–S87. doi: 10.1016/j.kint.2020.11.003CrossrefMedlineGoogle Scholar
  • 78. Fliotsos M, Zhao D, Rao VN, Ndumele CE, Guallar E, Burke GL, Vaidya D, Delaney JCA, Michos ED. Body mass index from early-, mid-, and older-adulthood and risk of heart failure and atherosclerotic cardiovascular disease: MESA.J Am Heart Assoc. 2018; 7:e009599. doi: 10.1161/JAHA.118.009599LinkGoogle Scholar
  • 79. Moyer VA, US Preventive Services Task Force. Screening for chronic kidney disease: U.S. Preventive Services Task Force recommendation statement.Ann Intern Med. 2012; 157:567–570. doi: 10.7326/0003-4819-157-8-201210160-00533CrossrefMedlineGoogle Scholar
  • 80. de Boer IH, Khunti K, Sadusky T, Tuttle KR, Neumiller JJ, Rhee CM, Rosas SE, Rossing P, Bakris G. Diabetes management in chronic kidney disease: a consensus report by the American Diabetes Association (ADA) and Kidney Disease: Improving Global Outcomes (KDIGO).Diabetes Care. 2022; 45:3075–3090. doi: 10.2337/dci22-0027CrossrefMedlineGoogle Scholar
  • 81. Chapter 1: definition and classification of CKD.Kidney Int Suppl (2011). 2013; 3:19–62. doi: 10.1038/kisup.2012.64CrossrefMedlineGoogle Scholar
  • 82. Lloyd-Jones DM, Allen NB, Anderson CAM, Black T, Brewer LC, Foraker RE, Grandner MA, Lavretsky H, Perak AM, Sharma G, et al; on behalf of the American Heart Association. Life’s Essential 8: updating and enhancing the American Heart Association’s construct of cardiovascular health: a presidential advisory from the American Heart Association.Circulation. 2022; 146:e18–e43. doi: 10.1161/CIR.0000000000001078LinkGoogle Scholar
  • 83. US Preventive Services Task Force, Bibbins-Domingo K, Grossman DC, Curry SJ, Davidson KW, Epling JW, Garcia FA, Gillman MW, Kemper AR, Krist AH, Kurth AE, et al. Screening for lipid disorders in children and adolescents: US Preventive Services Task Force recommendation statement.JAMA. 2016; 316:625–633. doi: 10.1001/jama.2016.9852CrossrefMedlineGoogle Scholar
  • 84. US Preventive Services Task Force, Krist AH, Davidson KW, Mangione CM, Barry MJ, Cabana M, Caughey AB, Donahue K, Doubeni CA, Epling JW, Kubik M, et al. Screening for high blood pressure in children and adolescents: US Preventive Services Task Force recommendation statement.JAMA. 2020; 324:1878–1883. doi: 10.1001/jama.2020.20122CrossrefMedlineGoogle Scholar
  • 85. US Preventive Services Task Force, Grossman DC, Bibbins-Domingo K, Curry SJ, Barry MJ, Davidson KW, Doubeni CA, Epling JW, Kemper AR, Krist AH, Kurth AE, et al. Screening for obesity in children and adolescents: US Preventive Services Task Force recommendation statement.JAMA. 2017; 317:2417–2426. doi: 10.1001/jama.2017.6803CrossrefMedlineGoogle Scholar
  • 86. US Preventive Services Task Force, Mangione CM, Barry MJ, Nicholson WK, Cabana M, Chelmow D, Coker TR, Davidson KW, Davis EM, Donahue KE, Jaén CR, et al. Screening for prediabetes and type 2 diabetes in children and adolescents: US Preventive Services Task Force recommendation statement.JAMA. 2022; 328:963–967. doi: 10.1001/jama.2022.14543CrossrefMedlineGoogle Scholar
  • 87. Flynn JT, Kaelber DC, Baker-Smith CM, Blowey D, Carroll AE, Daniels SR, de Ferranti SD, Dionne JM, Falkner B, Flinn SK, et al. Clinical practice guideline for screening and management of high blood pressure in children and adolescents.Pediatrics. 2017; 140:e20171904. doi: 10.1542/peds.2017-1904CrossrefMedlineGoogle Scholar
  • 88. Kavey RE, Allada V, Daniels SR, Hayman LL, McCrindle BW, Newburger JW, Parekh RS, Steinberger J. Cardiovascular risk reduction in high-risk pediatric patients: a scientific statement from the American Heart Association Expert Panel on Population and Prevention Science; the Councils on Cardiovascular Disease in the Young, Epidemiology and Prevention, Nutrition, Physical Activity and Metabolism, High Blood Pressure Research, Cardiovascular Nursing, and the Kidney in Heart Disease; and the Interdisciplinary Working Group on Quality of Care and Outcomes Research.Circulation. 2006; 114:2710–2738. doi: 10.1161/circulationaha.106.179568LinkGoogle Scholar
  • 89. Perak AM, Ning H, Khan SS, Bundy JD, Allen NB, Lewis CE, Jacobs DR, Van Horn LV, Lloyd-Jones DM. Associations of late adolescent or young adult cardiovascular health with premature cardiovascular disease and mortality.J Am Coll Cardiol. 2020; 76:2695–2707. doi: 10.1016/j.jacc.2020.10.002CrossrefMedlineGoogle Scholar
  • 90. Jacobs DR, Woo JG, Sinaiko AR, Daniels SR, Ikonen J, Juonala M, Kartiosuo N, Lehtimäki T, Magnussen CG, Viikari JSA, et al. Childhood cardiovascular risk factors and adult cardiovascular events.N Engl J Med. 2022; 386:1877–1888. doi: 10.1056/NEJMoa2109191CrossrefMedlineGoogle Scholar
  • 91. Hampl SE, Hassink SG, Skinner AC, Armstrong SC, Barlow SE, Bolling CF, Avila Edwards KC, Eneli I, Hamre R, Joseph MM, et al. Clinical practice guideline for the evaluation and treatment of children and adolescents with obesity.Pediatrics. 2023; 151:e2022060640. doi: 10.1542/peds.2022-060640CrossrefMedlineGoogle Scholar
  • 92. Juonala M, Magnussen CG, Berenson GS, Venn A, Burns TL, Sabin MA, Srinivasan SR, Daniels SR, Davis PH, Chen W, et al. Childhood adiposity, adult adiposity, and cardiovascular risk factors.N Engl J Med. 2011; 365:1876–1885. doi: 10.1056/NEJMoa1010112CrossrefMedlineGoogle Scholar
  • 93. Jebeile H, Kelly AS, O’Malley G, Baur LA. Obesity in children and adolescents: epidemiology, causes, assessment, and management.Lancet Diabetes Endocrinol. 2022; 10:351–365. doi: 10.1016/S2213-8587(22)00047-XCrossrefMedlineGoogle Scholar
  • 94. Mitsnefes MM. Cardiovascular disease in children with chronic kidney disease.J Am Soc Nephrol. 2012; 23:578–585. doi: 10.1681/ASN.2011111115CrossrefMedlineGoogle Scholar
  • 95. ESCAPE Trial Group, Wuhl E, Trivelli A, Picca S, Litwin M, Peco-Antic A, Zurowska A, Testa S, Jankauskiene A, Emre S, Caldas-Afonso A, et al. Strict blood-pressure control and progression of renal failure in children.N Engl J Med. 2009; 361:1639–1650. doi: 10.1056/NEJMoa0902066CrossrefMedlineGoogle Scholar
  • 96. Aroda VR, Christophi CA, Edelstein SL, Zhang P, Herman WH, Barrett-Connor E, Delahanty LM, Montez MG, Ackermann RT, Zhuo X, et al. The effect of lifestyle intervention and metformin on preventing or delaying diabetes among women with and without gestational diabetes: the Diabetes Prevention Program outcomes study 10-year follow-up.J Clin Endocrinol Metab. 2015; 100:1646–1653. doi: 10.1210/jc.2014-3761CrossrefMedlineGoogle Scholar
  • 97. O’Brien MJ, Zhang Y, Bailey SC, Khan SS, Ackermann RT, Ali MK, Benoit SR, Imperatore G, Holliday CS, Bullard KM. Screening for prediabetes and diabetes: clinical performance and implications for health equity.Am J Prev Med. 2023; 64:814–823. doi: 10.1016/j.amepre.2023.01.007CrossrefMedlineGoogle Scholar
  • 98. US Preventive Services Task Force, Krist AH, Davidson KW, Mangione CM, Cabana M, Caughey AB, Davis EM, Donahue KE, Doubeni CA, Kubik M, Li L, et al. Screening for hypertension in adults: US Preventive Services Task Force reaffirmation recommendation statement.JAMA. 2021; 325:1650–1656. doi: 10.1001/jama.2021.4987CrossrefMedlineGoogle Scholar
  • 99. Commodore-Mensah Y, Lazo M, Tang O, Echouffo-Tcheugui JB, Ndumele CE, Nambi V, Wang D, Ballantyne C, Selvin E. High burden of subclinical and cardiovascular disease risk in adults with metabolically healthy obesity: the Atherosclerosis Risk in Communities (ARIC) study.Diabetes Care. 2021; 44:1657–1663. doi: 10.2337/dc20-2227CrossrefMedlineGoogle Scholar
  • 100. Rosenzweig JL, Bakris GL, Berglund LF, Hivert MF, Horton ES, Kalyani RR, Murad MH, Verges BL. Primary prevention of ASCVD and T2DM in patients at metabolic risk: an Endocrine Society clinical practice guideline.J Clin Endocrinol Metab. 2019; 104:3939–3985. doi: 10.1210/jc.2019-01338CrossrefMedlineGoogle Scholar
  • 101. Lloyd-Jones DM, Braun LT, Ndumele CE, Smith SC, Sperling LS, Virani SS, Blumenthal RS. Use of risk assessment tools to guide decision-making in the primary prevention of atherosclerotic cardiovascular disease: a special report from the American Heart Association and American College of Cardiology [published correction appears in Circulation. 2019;138:e1188].Circulation. 2019; 139:e1162–e1177. doi: 10.1161/CIR.0000000000000638LinkGoogle Scholar
  • 102. Gepner AD, Young R, Delaney JA, Tattersall MC, Blaha MJ, Post WS, Gottesman RF, Kronmal R, Budoff MJ, Burke GL, et al. Comparison of coronary artery calcium presence, carotid plaque presence, and carotid intima-media thickness for cardiovascular disease prediction in the Multi-Ethnic Study of Atherosclerosis.Circ Cardiovasc Imaging. 2015; 8:e002262. doi: 10.1161/CIRCIMAGING.114.002262LinkGoogle Scholar
  • 103. Parcha V, Malla G, Kalra R, Li P, Pandey A, Nasir K, Arora G, Arora P. Coronary artery calcium score for personalization of antihypertensive therapy: a pooled cohort analysis.Hypertension. 2021; 77:1106–1118. doi: 10.1161/HYPERTENSIONAHA.120.16689LinkGoogle Scholar
  • 104. Cainzos-Achirica M, Miedema MD, McEvoy JW, Al Rifai M, Greenland P, Dardari Z, Budoff M, Blumenthal RS, Yeboah J, Duprez DA, et al. Coronary artery calcium for personalized allocation of aspirin in primary prevention of cardiovascular disease in 2019: the MESA study (Multi-Ethnic Study of Atherosclerosis).Circulation. 2020; 141:1541–1553. doi: 10.1161/CIRCULATIONAHA.119.045010LinkGoogle Scholar
  • 105. Jia X, Al Rifai M, Ndumele CE, Virani SS, de Lemos JA, Lee E, Shah AM, Echouffo-Tcheugui JB, Bozkurt B, Hoogeveen R, et al. Reclassification of pre-heart failure stages using cardiac biomarkers: Atherosclerosis Risk in Communities (ARIC) study.JACC Heart Fail. 2023; 11:449–450. doi: Scholar
  • 106. Ledwidge M, Gallagher J, Conlon C, Tallon E, O’Connell E, Dawkins I, Watson C, O’Hanlon R, Bermingham M, Patle A, et al. Natriuretic peptide-based screening and collaborative care for heart failure: the STOP-HF randomized trial.JAMA. 2013; 310:66–74. doi: 10.1001/jama.2013.7588CrossrefMedlineGoogle Scholar
  • 107. Huelsmann M, Neuhold S, Resl M, Strunk G, Brath H, Francesconi C, Adlbrecht C, Prager R, Luger A, Pacher R, et al. PONTIAC (NT-proBNP selected prevention of cardiac events in a population of diabetic patients without a history of cardiac disease): a prospective randomized controlled trial.J Am Coll Cardiol. 2013; 62:1365–1372. doi: 10.1016/j.jacc.2013.05.069CrossrefMedlineGoogle Scholar
  • 108. Ledwidge MT, O’Connell E, Gallagher J, Tilson L, James S, Voon V, Bermingham M, Tallon E, Watson C, O’Hanlon R, et al. Cost-effectiveness of natriuretic peptide-based screening and collaborative care: a report from the STOP-HF (St Vincent’s Screening TO Prevent Heart Failure) study.Eur J Heart Fail. 2015; 17:672–679. doi: 10.1002/ejhf.286CrossrefMedlineGoogle Scholar
  • 109. Pop-Busui R, Januzzi JL, Bruemmer D, Butalia S, Green JB, Horton WB, Knight C, Levi M, Rasouli N, Richardson CR. Heart failure: an underappreciated complication of diabetes: a consensus report of the American Diabetes Association.Diabetes Care. 2022; 45:1670–1690. doi: 10.2337/dci22-0014CrossrefMedlineGoogle Scholar
  • 110. Januzzi JL, Butler J, Jarolim P, Sattar N, Vijapurkar U, Desai M, Davies MJ. Effects of canagliflozin on cardiovascular biomarkers in older adults with type 2 diabetes.J Am Coll Cardiol. 2017; 70:704–712. doi: 10.1016/j.jacc.2017.06.016CrossrefMedlineGoogle Scholar
  • 111. Hildebrandt P, Collinson PO, Doughty RN, Fuat A, Gaze DC, Gustafsson F, Januzzi J, Rosenberg J, Senior R, Richards M. Age-dependent values of N-terminal pro-B-type natriuretic peptide are superior to a single cut-point for ruling out suspected systolic dysfunction in primary care.Eur Heart J. 2010; 31:1881–1889. doi: 10.1093/eurheartj/ehq163CrossrefMedlineGoogle Scholar
  • 112. deFilippi CR, Christenson RH, Gottdiener JS, Kop WJ, Seliger SL. Dynamic cardiovascular risk assessment in elderly people: the role of repeated N-terminal pro-B-type natriuretic peptide testing.J Am Coll Cardiol. 2010; 55:441–450. doi: 10.1016/j.jacc.2009.07.069CrossrefMedlineGoogle Scholar
  • 113. Bibbins-Domingo K. Integrating social care into the delivery of health care.JAMA. 2019; 322:1763–1764. doi: 10.1001/jama.2019.15603CrossrefMedlineGoogle Scholar
  • 114. Kreuter MW, Thompson T, McQueen A, Garg R. Addressing social needs in health care settings: evidence, challenges, and opportunities for public health.Annu Rev Public Health. 2021; 42:329–344. doi: 10.1146/annurev-publhealth-090419-102204CrossrefMedlineGoogle Scholar
  • 115. Mensah GA, Brown AGM, Pratt CA. Nutrition disparities and cardiovascular health.Curr Atheroscler Rep. 2020; 22:15. doi: 10.1007/s11883-020-0833-3CrossrefMedlineGoogle Scholar
  • 116. Narain R, Bijman L, Joshi H, Chen M. Novel multidisciplinary cardiometabolic clinic in a UK tertiary cardiology centre: early activity, interventions and potential for cardiovascular risk optimisation.Eur Heart J. 2021; 42(suppl 1):ehab724.2631. doi: 10.1093/eurheartj/ehab724.2631CrossrefGoogle Scholar
  • 117. Anderegg MD, Gums TH, Uribe L, MacLaughlin EJ, Hoehns J, Bazaldua OV, Ives TJ, Hahn DL, Coffey CS, Carter BL. Pharmacist intervention for blood pressure control in patients with diabetes and/or chronic kidney disease.Pharmacotherapy. 2018; 38:309–318. doi: 10.1002/phar.2083CrossrefMedlineGoogle Scholar
  • 118. Katz IJ, Pirabhahar S, Williamson P, Raghunath V, Brennan F, O’Sullivan A, Youssef G, Lane C, Jacobson G, Feldman P, et al. iConnect CKD: virtual medical consulting: a web-based chronic kidney disease, hypertension and diabetes integrated care program.Nephrology (Carlton). 2018; 23:646–652. doi: 10.1111/nep.13070CrossrefMedlineGoogle Scholar
  • 119. Thomas M, Magwire M, Gosch K, Sammour Y, Mehta R, O’Keefe J, Nassif ME, Kosiborod M. Cardiometabolic center of excellence: a novel care delivery model for secondary prevention of cardiovascular disease in type 2 diabetes.Circ Cardiovasc Qual Outcomes. 2021; 14:e007682. doi: 10.1161/CIRCOUTCOMES.120.007682LinkGoogle Scholar
  • 120. Pagidipati NJ, Nelson AJ, Kaltenbach LA, Leyva M, McGuire DK, Pop-Busui R, Cavender MA, Aroda VR, Magwire ML, Richardson CR, et al. Coordinated care to optimize cardiovascular preventive therapies in type 2 diabetes: a randomized clinical trial.JAMA. 2023; 329:1261–1270. doi: 10.1001/jama.2023.2854CrossrefMedlineGoogle Scholar
  • 121. Yan AF, Chen Z, Wang Y, Campbell JA, Xue QL, Williams MY, Weinhardt LS, Egede LE. Effectiveness of social needs screening and interventions in clinical settings on utilization, cost, and clinical outcomes: a systematic review.Health Equity. 2022; 6:454–475. doi: 10.1089/heq.2022.0010CrossrefMedlineGoogle Scholar
  • 122. Du T, Fernandez C, Barshop R, Fonseca V, Chen W, Bazzano LA. Variabilities in childhood cardiovascular risk factors and incident diabetes in adulthood: the Bogalusa Heart Study.Diabetes Care. 2019; 42:1816–1823. doi: 10.2337/dc19-0430CrossrefMedlineGoogle Scholar
  • 123. Li S, Chen W, Srinivasan SR, Bond MG, Tang R, Urbina EM, Berenson GS. Childhood cardiovascular risk factors and carotid vascular changes in adulthood: the Bogalusa Heart Study.JAMA. 2003; 290:2271–2276. doi: 10.1001/jama.290.17.2271CrossrefMedlineGoogle Scholar
  • 124. Guo P, Zhou Y, Zhu Y. Effects of a school-based lifestyle intervention on ideal cardiovascular health in Chinese children and adolescents: a national, multicentre, cluster-randomised controlled trial.Lancet Glob Health. 2023; 11:S14. doi: 10.1016/S2214-109X(23)00097-9CrossrefMedlineGoogle Scholar
  • 125. Waters E, de Silva-Sanigorski A, Hall BJ, Brown T, Campbell KJ, Gao Y, Armstrong R, Prosser L, Summerbell CD. Interventions for preventing obesity in children.Cochrane Database Syst Rev. 2011:CD001871. doi: 10.1002/14651858.CD001871.pub3CrossrefMedlineGoogle Scholar
  • 126. Lloyd-Jones DM, Liu K, Colangelo LA, Yan LL, Klein L, Loria CM, Lewis CE, Savage P. Consistently stable or decreased body mass index in young adulthood and longitudinal changes in metabolic syndrome components: the Coronary Artery Risk Development in Young Adults Study.Circulation. 2007; 115:1004–1011. doi: 10.1161/CIRCULATIONAHA.106.648642LinkGoogle Scholar
  • 127. Gudzune KA, Bennett WL, Cooper LA, Bleich SN. Perceived judgment about weight can negatively influence weight loss: a cross-sectional study of overweight and obese patients.Prev Med. 2014; 62:103–107. doi: 10.1016/j.ypmed.2014.02.001CrossrefMedlineGoogle Scholar
  • 128. Gallagher C, Corl A, Dietz WH. Weight can’t wait: a guide to discussing obesity and organizing treatment in the primary care setting.Obesity (Silver Spring). 2021; 29:821–824. doi: 10.1002/oby.23154CrossrefMedlineGoogle Scholar
  • 129. Look AHEAD Research Group; Pi-Sunyer X, Blackburn G, Brancati FL, Bray GA, Bright R, Clark JM, Curtis JM, Espeland MA, Foreyt JP, Graves K, et al. Reduction in weight and cardiovascular disease risk factors in individuals with type 2 diabetes: one-year results of the Look AHEAD Trial.Diabetes Care. 2007; 30:1374–1383. doi: 10.2337/dc07-0048CrossrefMedlineGoogle Scholar
  • 130. Sjostrom L, Peltonen M, Jacobson P, Sjostrom CD, Karason K, Wedel H, Ahlin S, Anveden A, Bengtsson C, Bergmark G, et al. Bariatric surgery and long-term cardiovascular events.JAMA. 2012; 307:56–65. doi: 10.1001/jama.2011.1914CrossrefMedlineGoogle Scholar
  • 131. Bethel MA, Patel RA, Merrill P, Lokhnygina Y, Buse JB, Mentz RJ, Pagidipati NJ, Chan JC, Gustavson SM, Iqbal N, et al. Cardiovascular outcomes with glucagon-like peptide-1 receptor agonists in patients with type 2 diabetes: a meta-analysis.Lancet Diabetes Endocrinol. 2018; 6:105–113. doi: 10.1016/S2213-8587(17)30412-6CrossrefMedlineGoogle Scholar
  • 132. Janssen I, Heymsfield SB, Allison DB, Kotler DP, Ross R. Body mass index and waist circumference independently contribute to the prediction of nonabdominal, abdominal subcutaneous, and visceral fat.Am J Clin Nutr. 2002; 75:683–688. doi: 10.1093/ajcn/75.4.683CrossrefMedlineGoogle Scholar
  • 133. Ross R, Neeland IJ, Yamashita S, Shai I, Seidell J, Magni P, Santos RD, Arsenault B, Cuevas A, Hu FB, et al. Waist circumference as a vital sign in clinical practice: a consensus statement from the IAS and ICCR Working Group on Visceral Obesity.Nat Rev Endocrinol. 2020; 16:177–189. doi: 10.1038/s41574-019-0310-7CrossrefMedlineGoogle Scholar
  • 134. Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, Nathan DM; Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin.N Engl J Med. 2002; 346:393–403. doi: 10.1056/NEJMoa012512CrossrefMedlineGoogle Scholar
  • 135. Wang K, Hu J, Luo T, Wang Y, Yang S, Qing H, Cheng Q, Li Q. Effects of angiotensin-converting enzyme inhibitors and angiotensin ii receptor blockers on all-cause mortality and renal outcomes in patients with diabetes and albuminuria: a systematic review and meta-analysis.Kidney Blood Press Res. 2018; 43:768–779. doi: 10.1159/000489913CrossrefMedlineGoogle Scholar
  • 136. Wright JT, Probstfield JL, Cushman WC, Pressel SL, Cutler JA, Davis BR, Einhorn PT, Rahman M, Whelton PK, Ford CE, et al. ALLHAT findings revisited in the context of subsequent analyses, other trials, and meta-analyses.Arch Intern Med. 2009; 169:832–842. doi: 10.1001/archinternmed.2009.60CrossrefMedlineGoogle Scholar
  • 137 Bhatt DL, Steg PG, Miller M, Brinton EA, Jacobson TA, Ketchum SB, Doyle RT, Juliano RA, Jiao L, Granowitz C, et al. Cardiovascular risk reduction with icosapent ethyl for hypertriglyceridemia.N Engl J Med. 2019; 380:11–22. doi: 10.1056/NEJMoa1812792CrossrefMedlineGoogle Scholar
  • 138. Sattar N, McMurray J, Boren J, Rawshani A, Omerovic E, Berg N, Holminen J, Skoglund K, Eliasson B, Gerstein HC, et al. Twenty years of cardiovascular complications and risk factors in patients with type 2 diabetes: a nationwide Swedish cohort study.Circulation. 2023; 147:1872–1886. doi: 10.1161/CIRCULATIONAHA.122.063374LinkGoogle Scholar
  • 139. Gaede P, Lund-Andersen H, Parving HH, Pedersen O. Effect of a multifactorial intervention on mortality in type 2 diabetes.N Engl J Med. 2008; 358:580–591. doi: 10.1056/NEJMoa0706245CrossrefMedlineGoogle Scholar
  • 140. Wing RR, Lang W, Wadden TA, Safford M, Knowler WC, Bertoni AG, Hill JO, Brancati FL, Peters A, Wagenknecht L, et al. Benefits of modest weight loss in improving cardiovascular risk factors in overweight and obese individuals with type 2 diabetes.Diabetes Care. 2011; 34:1481–1486. doi: 10.2337/dc10-2415CrossrefMedlineGoogle Scholar
  • 141. Giugliano RP, Cannon CP, Blazing MA, Nicolau JC, Corbalan R, Spinar J, Park JG, White JA, Bohula EA, Braunwald E, et al. Benefit of adding ezetimibe to statin therapy on cardiovascular outcomes and safety in patients with versus without diabetes mellitus: results from IMPROVE-IT (Improved Reduction of Outcomes: Vytorin Efficacy International Trial).Circulation. 2018; 137:1571–1582. doi: 10.1161/CIRCULATIONAHA.117.030950LinkGoogle Scholar
  • 142. Leiter LA, Betteridge DJ, Farnier M, Guyton JR, Lin J, Shah A, Johnson-Levonas AO, Brudi P. Lipid-altering efficacy and safety profile of combination therapy with ezetimibe/statin vs. statin monotherapy in patients with and without diabetes: an analysis of pooled data from 27 clinical trials.Diabetes Obes Metab. 2011; 13:615–628. doi: 10.1111/j.1463-1326.2011.01383.xCrossrefMedlineGoogle Scholar
  • 143. Morales J, Handelsman Y. cardiovascular outcomes in patients with diabetes and kidney disease: JACC review topic of the week.J Am Coll Cardiol. 2023; 82:161–170. doi: 10.1016/j.jacc.2023.04.052CrossrefMedlineGoogle Scholar
  • 144. EMPA-KIDNEY Collaborative Group, Herrington WG, Staplin N, Wanner C, Green JB, Hauske SJ, Emberson JR, Preiss D, Judge P, Mayne KJ, Ng SYA, et al. Empagliflozin in patients with chronic kidney disease.N Engl J Med. 2022; 388:117–127. doi: 10.1056/NEJMoa2204233CrossrefMedlineGoogle Scholar
  • 145. ElSayed NA, Aleppo G, Aroda VR, Bannuru RR, Brown FM, Bruemmer D, Collins BS, Hilliard ME, Isaacs D, Johnson EL, et al. 9: Pharmacologic approaches to glycemic treatment: Standards of Care in Diabetes–2023.Diabetes Care. 2023; 46:S140–S157. doi: 10.2337/dc23-S009CrossrefMedlineGoogle Scholar
  • 146. Pandey A, Vaduganathan M, Patel KV, Ayers C, Ballantyne CM, Kosiborod MN, Carnethon M, DeFilippi C, McGuire DK, Khan SS, et al. Biomarker-based risk prediction of incident heart failure in pre-diabetes and diabetes.JACC Heart Fail. 2021; 9:215–223. doi: 10.1016/j.jchf.2020.10.013CrossrefMedlineGoogle Scholar
  • 147. Lewis CE, Fine LJ, Beddhu S, Cheung AK, Cushman WC, Cutler JA, Evans GW, Johnson KC, Kitzman DW, Oparil S, et al. Final report of a trial of intensive versus standard blood-pressure control.N Engl J Med. 2021; 384:1921–1930. doi: 10.1056/NEJMoa1901281CrossrefMedlineGoogle Scholar
  • 148. Rossing P, Baeres FMM, Bakris G, Bosch-Traberg H, Gislum M, Gough SCL, Idorn T, Lawson J, Mahaffey KW, Mann JFE, et al. The rationale, design and baseline data of FLOW, a kidney outcomes trial with once-weekly semaglutide in people with type 2 diabetes and chronic kidney disease.Nephrol Dial Transplant. 2023; 38:2041–2051.doi: 10.1093/ndt/gfad009CrossrefMedlineGoogle Scholar
  • 149. Agarwal R, Filippatos G, Pitt B, Anker SD, Rossing P, Joseph A, Kolkhof P, Nowack C, Gebel M, Ruilope LM, et al. Cardiovascular and kidney outcomes with finerenone in patients with type 2 diabetes and chronic kidney disease: the FIDELITY pooled analysis.Eur Heart J. 2022; 43:474–484. doi: 10.1093/eurheartj/ehab777CrossrefMedlineGoogle Scholar
  • 150. Baigent C, Landray MJ, Reith C, Emberson J, Wheeler DC, Tomson C, Wanner C, Krane V, Cass A, Craig J, et al. The effects of lowering LDL cholesterol with simvastatin plus ezetimibe in patients with chronic kidney disease (Study of Heart and Renal Protection): a randomised placebo-controlled trial.Lancet. 2011; 377:2181–2192. doi: 10.1016/s0140-6736(11)60739-3CrossrefMedlineGoogle Scholar
  • 151. Konstam MA, Kronenberg MW, Rousseau MF, Udelson JE, Melin J, Stewart D, Dolan N, Edens TR, Ahn S, Kinan D, et al. Effects of the angiotensin converting enzyme inhibitor enalapril on the long-term progression of left ventricular dilatation in patients with asymptomatic systolic dysfunction: SOLVD (Studies of Left Ventricular Dysfunction) investigators.Circulation. 1993; 88:2277–2283. doi: 10.1161/01.cir.88.5.2277LinkGoogle Scholar
  • 152. Vantrimpont P, Rouleau JL, Wun CC, Ciampi A, Klein M, Sussex B, Arnold JM, Moye L, Pfeffer M. Additive beneficial effects of beta-blockers to angiotensin-converting enzyme inhibitors in the Survival and Ventricular Enlargement (SAVE) Study: SAVE investigators.J Am Coll Cardiol. 1997; 29:229–236. doi: 10.1016/s0735-1097(96)00489-5CrossrefMedlineGoogle Scholar
  • 153. McGuire DK, Shih WJ, Cosentino F, Charbonnel B, Cherney DZI, Dagogo-Jack S, Pratley R, Greenberg M, Wang S, Huyck S, et al. Association of SGLT2 inhibitors with cardiovascular and kidney outcomes in patients with type 2 diabetes: a meta-analysis.JAMA Cardiol. 2021; 6:148–158. doi: 10.1001/jamacardio.2020.4511CrossrefMedlineGoogle Scholar
  • 154. Berg DD, Wiviott SD, Scirica BM, Gurmu Y, Mosenzon O, Murphy SA, Bhatt DL, Leiter LA, McGuire DK, Wilding JPH, et al. Heart failure risk stratification and efficacy of sodium-glucose cotransporter-2 inhibitors in patients with type 2 diabetes mellitus.Circulation. 2019; 140:1569–1577. doi: 10.1161/CIRCULATIONAHA.119.042685LinkGoogle Scholar
  • 155. Budoff MJ, Young R, Burke G, Jeffrey Carr J, Detrano RC, Folsom AR, Kronmal R, Lima JAC, Liu KJ, McClelland RL, et al. Ten-year association of coronary artery calcium with atherosclerotic cardiovascular disease (ASCVD) events: the Multi-Ethnic Study of Atherosclerosis (MESA).Eur Heart J. 2018; 39:2401–2408. doi: 10.1093/eurheartj/ehy217CrossrefMedlineGoogle Scholar
  • 156. Patel J, Pallazola VA, Dudum R, Greenland P, McEvoy JW, Blumenthal RS, Virani SS, Miedema MD, Shea S, Yeboah J, et al. Assessment of coronary artery calcium scoring to guide statin therapy allocation according to risk-enhancing factors: the Multi-Ethnic Study of Atherosclerosis.JAMA Cardiol. 2021; 6:1161–1170. doi: 10.1001/jamacardio.2021.2321CrossrefMedlineGoogle Scholar
  • 157. Mitchell JD, Fergestrom N, Gage BF, Paisley R, Moon P, Novak E, Cheezum M, Shaw LJ, Villines TC. Impact of statins on cardiovascular outcomes following coronary artery calcium scoring.J Am Coll Cardiol. 2018; 72:3233–3242. doi: 10.1016/j.jacc.2018.09.051CrossrefMedlineGoogle Scholar
  • 158. Virani SS, Al Rifai M. The utility of coronary artery calcium for guiding treatment with preventive pharmacotherapy: opportunities and nuances.JACC Cardiovasc Imaging. 2022; 15:652–654. doi: 10.1016/j.jcmg.2021.11.011CrossrefMedlineGoogle Scholar
  • 159. Wright AK, Carr MJ, Kontopantelis E, Leelarathna L, Thabit H, Emsley R, Buchan I, Mamas MA, van Staa TP, Sattar N, et al. Primary prevention of cardiovascular and heart failure events with SGLT2 inhibitors, GLP-1 receptor agonists, and their combination in type 2 diabetes.Diabetes Care. 2022; 45:909–918. doi: 10.2337/dc21-1113CrossrefMedlineGoogle Scholar
  • 160. Kitzman DW, Brubaker P, Morgan T, Haykowsky M, Hundley G, Kraus WE, Eggebeen J, Nicklas BJ. Effect of caloric restriction or aerobic exercise training on peak oxygen consumption and quality of life in obese older patients with heart failure with preserved ejection fraction: a randomized clinical trial.JAMA. 2016; 315:36–46. doi: 10.1001/jama.2015.17346CrossrefMedlineGoogle Scholar
  • 161. Sattar N, Lee MMY, Kristensen SL, Branch KRH, Del Prato S, Khurmi NS, Lam CSP, Lopes RD, McMurray JJV, Pratley RE, et al. Cardiovascular, mortality, and kidney outcomes with GLP-1 receptor agonists in patients with type 2 diabetes: a systematic review and meta-analysis of randomised trials.Lancet Diabetes Endocrinol. 2021; 9:653–662. doi: 10.1016/S2213-8587(21)00203-5CrossrefMedlineGoogle Scholar
  • 162. Ryan DH, Lingvay I, Colhoun HM, Deanfield J, Emerson SS, Kahn SE, Kushner RF, Marso S, Plutzky J, Brown-Frandsen K, et al. Semaglutide Effects on Cardiovascular Outcomes in People With Overweight or Obesity (SELECT) rationale and design.Am Heart J. 2020; 229:61–69. doi: 10.1016/j.ahj.2020.07.008CrossrefMedlineGoogle Scholar
  • 163. Doumouras AG, Wong JA, Paterson JM, Lee Y, Sivapathasundaram B, Tarride JE, Thabane L, Hong D, Yusuf S, Anvari M. Bariatric surgery and cardiovascular outcomes in patients with obesity and cardiovascular disease: a population-based retrospective cohort study.Circulation. 2021; 143:1468–1480. doi: 10.1161/CIRCULATIONAHA.120.052386LinkGoogle Scholar
  • 164. Packer M, Anker SD, Butler J, Filippatos G, Pocock SJ, Carson P, Januzzi J, Verma S, Tsutsui H, Brueckmann M, et al. Cardiovascular and renal outcomes with empagliflozin in heart failure.N Engl J Med. 2020; 383:1413–1424. doi: 10.1056/NEJMoa2022190CrossrefMedlineGoogle Scholar
  • 165. McMurray JJV, Solomon SD, Inzucchi SE, Kober L, Kosiborod MN, Martinez FA, Ponikowski P, Sabatine MS, Anand IS, Belohlavek J, et al. Dapagliflozin in patients with heart failure and reduced ejection fraction.N Engl J Med. 2019; 381:1995–2008. doi: 10.1056/NEJMoa1911303CrossrefMedlineGoogle Scholar
  • 166. Solomon SD, McMurray JJV, Claggett B, de Boer RA, DeMets D, Hernandez AF, Inzucchi SE, Kosiborod MN, Lam CSP, Martinez F, et al. Dapagliflozin in heart failure with mildly reduced or preserved ejection fraction.N Engl J Med. 2022; 387:1089–1098. doi: 10.1056/NEJMoa2206286CrossrefMedlineGoogle Scholar
  • 167. Jhund PS, Kondo T, Butt JH, Docherty KF, Claggett BL, Desai AS, Vaduganathan M, Gasparyan SB, Bengtsson O, Lindholm D, et al. Dapagliflozin across the range of ejection fraction in patients with heart failure: a patient-level, pooled meta-analysis of DAPA-HF and DELIVER.Nat Med. 2022; 28:1956–1964. doi: 10.1038/s41591-022-01971-4CrossrefMedlineGoogle Scholar
  • 168. Kosiborod MN, Abildstrøm SZ, Borlaug BA, Butler J, Christensen L, Davies M, Hovingh KG, Kitzman DW, Lindegaard ML, Møller DV, et al. Design and baseline characteristics of STEP-HFpEF program evaluating semaglutide in patients with obesity HFpEF phenotype.JACC Heart Fail. 2023; 11(pt 1): 1205–1218. doi: 10.1016/j.jchf.2023.05.010CrossrefGoogle Scholar
  • 169. Khan MS, Fonarow GC, McGuire DK, Hernandez AF, Vaduganathan M, Rosenstock J, Handelsman Y, Verma S, Anker SD, McMurray JJV, et al. Glucagon-like peptide 1 receptor agonists and heart failure: the need for further evidence generation and practice guidelines optimization.Circulation. 2020; 142:1205–1218. doi: 10.1161/CIRCULATIONAHA.120.045888LinkGoogle Scholar
  • 170. Rodbard HW, Rosenstock J, Canani LH, Deerochanawong C, Gumprecht J, Lindberg SO, Lingvay I, Sondergaard AL, Treppendahl MB, Montanya E, et al. Oral semaglutide versus empagliflozin in patients with type 2 diabetes uncontrolled on metformin: the PIONEER 2 trial.Diabetes Care. 2019; 42:2272–2281. doi: 10.2337/dc19-0883CrossrefMedlineGoogle Scholar
  • 171. Nuffield Department of Population Health Renal Studies Group; SGLT2 Inhibitor Meta-Analysis Cardio-Renal Trialists’ Consortium. Impact of diabetes on the effects of sodium glucose co-transporter-2 inhibitors on kidney outcomes: collaborative meta-analysis of large placebo-controlled trials.Lancet. 2022; 400:1788–1801. doi: 10.1016/s0140-6736(22)02074-8CrossrefMedlineGoogle Scholar
  • 172. Vaduganathan M, Docherty KF, Claggett BL, Jhund PS, de Boer RA, Hernandez AF, Inzucchi SE, Kosiborod MN, Lam CSP, Martinez F, et al. SGLT-2 inhibitors in patients with heart failure: a comprehensive meta-analysis of five randomised controlled trials.Lancet. 2022; 400:757–767. doi: 10.1016/s0140-6736(22)01429-5CrossrefMedlineGoogle Scholar
  • 173. Brenner BM, Cooper ME, de Zeeuw D, Keane WF, Mitch WE, Parving HH, Remuzzi G, Snapinn SM, Zhang Z, Shahinfar S. Effects of losartan on renal and cardiovascular outcomes in patients with type 2 diabetes and nephropathy.N Engl J Med. 2001; 345:861–869. doi: 10.1056/NEJMoa011161CrossrefMedlineGoogle Scholar
  • 174. Lewis EJ, Hunsicker LG, Bain RP, Rohde RD. The effect of angiotensin-converting-enzyme inhibition on diabetic nephropathy: the Collaborative Study Group.N Engl J Med. 1993; 329:1456–1462. doi: 10.1056/nejm199311113292004CrossrefMedlineGoogle Scholar
  • 175. Parving HH, Lehnert H, Bröchner-Mortensen J, Gomis R, Andersen S, Arner P. The effect of irbesartan on the development of diabetic nephropathy in patients with type 2 diabetes.N Engl J Med. 2001; 345:870–878. doi: 10.1056/NEJMoa011489CrossrefMedlineGoogle Scholar
  • 176. Beldhuis IE, Lam CSP, Testani JM, Voors AA, Van Spall HGC, Ter Maaten JM, Damman K. Evidence-based medical therapy in patients with heart failure with reduced ejection fraction and chronic kidney disease.Circulation. 2022; 145:693–712. doi: 10.1161/circulationaha.121.052792LinkGoogle Scholar
  • 177. Neuen BL, Oshima M, Agarwal R, Arnott C, Cherney DZ, Edwards R, Langkilde AM, Mahaffey KW, McGuire DK, Neal B, et al. Sodium-glucose cotransporter 2 inhibitors and risk of hyperkalemia in people with type 2 diabetes: a meta-analysis of individual participant data from randomized, controlled trials.Circulation. 2022; 145:1460–1470. doi: 10.1161/circulationaha.121.057736LinkGoogle Scholar
  • 178. Nielsen EE, Feinberg JB, Bu FL, Hecht Olsen M, Raymond I, Steensgaard-Hansen F, Jakobsen JC. Beneficial and harmful effects of sacubitril/valsartan in patients with heart failure: a systematic review of randomised clinical trials with meta-analysis and trial sequential analysis.Open Heart. 2020; 7:e001294. doi: 10.1136/openhrt-2020-001294CrossrefMedlineGoogle Scholar
  • 179. Zhang H, Huang T, Shen W, Xu X, Yang P, Zhu D, Fang H, Wan H, Wu T, Wu Y, et al. Efficacy and safety of sacubitril-valsartan in heart failure: a meta-analysis of randomized controlled trials.ESC Heart Fail. 2020; 7:3841–3850. doi: 10.1002/ehf2.12974CrossrefMedlineGoogle Scholar
  • 180. Feng Y, Yin Y, Deng R, Li H. Renal safety and efficacy of angiotensin receptor-neprilysin inhibitor: a meta-analysis of randomized controlled trials.J Clin Pharm Ther. 2020; 45:1235–1243. doi: 10.1111/jcpt.13243CrossrefMedlineGoogle Scholar
  • 181. Spannella F, Giulietti F, Filipponi A, Sarzani R. Effect of sacubitril/valsartan on renal function: a systematic review and meta-analysis of randomized controlled trials.ESC Heart Fail. 2020; 7:3487–3496. doi: 10.1002/ehf2.13002CrossrefMedlineGoogle Scholar
  • 182. Adamson C, Docherty KF, Heerspink HJL, de Boer RA, Damman K, Inzucchi SE, Køber L, Kosiborod MN, Martinez FA, Petrie MC, et al. Initial decline (dip) in estimated glomerular filtration rate after initiation of dapagliflozin in patients with heart failure and reduced ejection fraction: insights from DAPA-HF.Circulation. 2022; 146:438–449. doi: 10.1161/circulationaha.121.058910LinkGoogle Scholar
  • 183. Mullens W, Damman K, Testani JM, Martens P, Mueller C, Lassus J, Tang WHW, Skouri H, Verbrugge FH, Orso F, et al. Evaluation of kidney function throughout the heart failure trajectory: a position statement from the Heart Failure Association of the European Society of Cardiology.Eur J Heart Fail. 2020; 22:584–603. doi: 10.1002/ejhf.1697CrossrefMedlineGoogle Scholar
  • 184. Sarnak MJ, Bloom R, Muntner P, Rahman M, Saland JM, Wilson PW, Fried L. KDOQI US commentary on the 2013 KDIGO clinical practice guideline for lipid management in CKD.Am J Kidney Dis. 2015; 65:354–366. doi: 10.1053/j.ajkd.2014.10.005CrossrefMedlineGoogle Scholar
  • 185. Amsterdam EA, Wenger NK, Brindis RG, Casey DE, Ganiats TG, Holmes DR, Jaffe AS, Jneid H, Kelly RF, Kontos MC, et al. 2014 AHA/ACC guideline for the management of patients with non-ST-elevation acute coronary syndromes: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines [published correction appears in Circulation. 2014;1130:e433–e434].Circulation. 2014; 130:e344–e426. doi: 10.1161/CIR.0000000000000134LinkGoogle Scholar
  • 186. Park DY, An S, Murthi M, Kattoor AJ, Kaur A, Ravi V, Huang HD, Vij A. Effect of weight loss on recurrence of atrial fibrillation after ablative therapy: a systematic review and meta-analysis.J Interv Card Electrophysiol. 2022; 64:763–771. doi: 10.1007/s10840-022-01168-2CrossrefMedlineGoogle Scholar
  • 187. Linz D, McEvoy RD, Cowie MR, Somers VK, Nattel S, Levy P, Kalman JM, Sanders P. Associations of obstructive sleep apnea with atrial fibrillation and continuous positive airway pressure treatment: a review.JAMA Cardiol. 2018; 3:532–540. doi: 10.1001/jamacardio.2018.0095CrossrefMedlineGoogle Scholar
  • 188. Sarnak MJ, Auguste BL, Brown E, Chang AR, Chertow GM, Hannan M, Herzog CA, Nadeau-Fredette AC, Tang WHW, Wang AY, et al; on behalf of the American Heart Association Council on the Kidney in Cardiovascular Disease; Council on Arteriosclerosis, Thrombosis and Vascular Biology; Council on Cardiovascular Radiology and Intervention; Council on Clinical Cardiology; Council on Hypertension; and Council on Lifestyle and Cardiometabolic Health. Cardiovascular effects of home dialysis therapies: a scientific statement from the American Heart Association.Circulation. 2022; 146:e146–e164. doi: 10.1161/cir.0000000000001088LinkGoogle Scholar
  • 189. Chertow GM, Levin NW, Beck GJ, Depner TA, Eggers PW, Gassman JJ, Gorodetskaya I, Greene T, James S, Larive B, et al. In-center hemodialysis six times per week versus three times per week.N Engl J Med. 2010; 363:2287–2300. doi: 10.1056/NEJMoa1001593CrossrefMedlineGoogle Scholar
  • 190. Bansal N, Artinian NT, Bakris G, Chang T, Cohen J, Flythe J, Lea J, Vongpatanasin W, Chertow GM; on behalf of the American Heart Association Council on the Kidney in Cardiovascular Disease; Council on Cardiovascular and Stroke Nursing; and Council on Epidemiology and Prevention. Hypertension in patients treated with in-center maintenance hemodialysis: current evidence and future opportunities: a scientific statement from the American Heart Association.Hypertension. 2023; 80:e112–e122.LinkGoogle Scholar
  • 191. Fellström BC, Jardine AG, Schmieder RE, Holdaas H, Bannister K, Beutler J, Chae D-W, Chevaile A, Cobbe SM, Grönhagen-Riska C, et al. Rosuvastatin and cardiovascular events in patients undergoing hemodialysis.N Engl J Med. 2009; 360:1395–1407. doi: 10.1056/NEJMoa0810177CrossrefMedlineGoogle Scholar
  • 192. Wanner C, Krane V, Marz W, Olschewski M, Mann JF, Ruf G, Ritz E; German Diabetes and Dialysis Study Investigators. Atorvastatin in patients with type 2 diabetes mellitus undergoing hemodialysis.N Engl J Med. 2005; 353:238–248. doi: 10.1056/NEJMoa043545CrossrefMedlineGoogle Scholar
  • 193. Holdaas H, Holme I, Schmieder RE, Jardine AG, Zannad F, Norby GE, Fellstrom BC, group A. Rosuvastatin in diabetic hemodialysis patients.J Am Soc Nephrol. 2011; 22:1335–1341. doi: 10.1681/ASN.2010090987CrossrefMedlineGoogle Scholar
  • 194. Streja E, Gosmanova EO, Molnar MZ, Soohoo M, Moradi H, Potukuchi PK, Kalantar-Zadeh K, Kovesdy CP. Association of continuation of statin therapy initiated before transition to chronic dialysis therapy with mortality after dialysis initiation.JAMA Netw Open. 2018; 1:e182311. doi: 10.1001/jamanetworkopen.2018.2311CrossrefMedlineGoogle Scholar
  • 195. Jung J, Bae GH, Kang M, Kim SW, Lee DH. Statins and all-cause mortality in patients undergoing hemodialysis.J Am Heart Assoc. 2020; 9:e014840. doi: 10.1161/JAHA.119.014840LinkGoogle Scholar
  • 196. Page KA, Luo S, Wang X, Chow T, Alves J, Buchanan TA, Xiang AH. Children exposed to maternal obesity or gestational diabetes mellitus during early fetal development have hypothalamic alterations that predict future weight gain.Diabetes Care. 2019; 42:1473–1480. doi: 10.2337/dc18-2581CrossrefMedlineGoogle Scholar
  • 197. Hemmingsson E. Early childhood obesity risk factors: socioeconomic adversity, family dysfunction, offspring distress, and junk food self-medication.Curr Obes Rep. 2018; 7:204–209. doi: 10.1007/s13679-018-0310-2CrossrefMedlineGoogle Scholar
  • 198. Liu Z, Gao P, Gao AY, Lin Y, Feng XX, Zhang F, Xu LQ, Niu WY, Fang H, Zhou S, et al. Effectiveness of a multifaceted intervention for prevention of obesity in primary school children in China: a cluster randomized clinical trial.JAMA Pediatr. 2022; 176:e214375. doi: 10.1001/jamapediatrics.2021.4375CrossrefMedlineGoogle Scholar
  • 199. Wilding JPH, Batterham RL, Calanna S, Davies M, Van Gaal LF, Lingvay I, McGowan BM, Rosenstock J, Tran MTD, Wadden TA, et al. Once-weekly semaglutide in adults with overweight or obesity.N Engl J Med. 2021; 384:989–1002. doi: 10.1056/NEJMoa2032183CrossrefMedlineGoogle Scholar
  • 200. Jastreboff AM, Aronne LJ, Ahmad NN, Wharton S, Connery L, Alves B, Kiyosue A, Zhang S, Liu B, Bunck MC, et al. Tirzepatide Once Weekly for the Treatment of Obesity.N Engl J Med. 2022; 387:205–216. doi: 10.1056/NEJMoa2206038CrossrefMedlineGoogle Scholar
  • 201. Rubino D, Abrahamsson N, Davies M, Hesse D, Greenway FL, Jensen C, Lingvay I, Mosenzon O, Rosenstock J, Rubio MA, et al. Effect of continued weekly subcutaneous semaglutide vs placebo on weight loss maintenance in adults with overweight or obesity: the STEP 4 randomized clinical trial.JAMA. 2021; 325:1414–1425. doi: 10.1001/jama.2021.3224CrossrefMedlineGoogle Scholar
  • 202. Sundstrom J, Bruze G, Ottosson J, Marcus C, Naslund I, Neovius M. Weight loss and heart failure: a nationwide study of gastric bypass surgery versus intensive lifestyle treatment.Circulation. 2017; 135:1577–1585. doi: 10.1161/CIRCULATIONAHA.116.025629LinkGoogle Scholar
  • 203. Khan MS, Segar MW, Usman MS, Patel KV, Van Spall HGC, DeVore AD, Vaduganathan M, Lam CSP, Zannad F, Verma S, et al. Effect of canagliflozin on heart failure hospitalization in diabetes according to baseline heart failure risk.JACC Heart Fail. 2023; 11:825–835. doi: 10.1016/j.jchf.2023.03.025CrossrefMedlineGoogle Scholar
  • 204. Gerstein HC, Sattar N, Rosenstock J, Ramasundarahettige C, Pratley R, Lopes RD, Lam CSP, Khurmi NS, Heenan L, Del Prato S, et al. Cardiovascular and renal outcomes with efpeglenatide in type 2 diabetes.N Engl J Med. 2021; 385:896–907. doi: 10.1056/NEJMoa2108269CrossrefMedlineGoogle Scholar
  • 205. Marso SP, Bain SC, Consoli A, Eliaschewitz FG, Jodar E, Leiter LA, Lingvay I, Rosenstock J, Seufert J, Warren ML, et al. Semaglutide and cardiovascular outcomes in patients with type 2 diabetes.N Engl J Med. 2016; 375:1834–1844. doi: 10.1056/NEJMoa1607141CrossrefMedlineGoogle Scholar
  • 206. Das Pradhan A, Glynn RJ, Fruchart JC, MacFadyen JG, Zaharris ES, Everett BM, Campbell SE, Oshima R, Amarenco P, Blom DJ, et al. Triglyceride lowering with pemafibrate to reduce cardiovascular risk.N Engl J Med. 2022; 387:1923–1934. doi: 10.1056/NEJMoa2210645CrossrefMedlineGoogle Scholar
  • 207. Virani SS. The fibrates story: a tepid end to a PROMINENT drug.N Engl J Med. 2022; 387:1991–1992. doi: 10.1056/NEJMe2213208CrossrefMedlineGoogle Scholar
  • 208. Rossing P, Filippatos G, Agarwal R, Anker SD, Pitt B, Ruilope LM, Chan JCN, Kooy A, McCafferty K, Schernthaner G, et al. Finerenone in predominantly advanced CKD and type 2 diabetes with or without sodium-glucose cotransporter-2 inhibitor therapy.Kidney Int Rep. 2022; 7:36–45. doi: 10.1016/j.ekir.2021.10.008CrossrefMedlineGoogle Scholar
  • 209. Rangaswami J, Tuttle K, Vaduganathan M. Cardio-renal-metabolic care models: toward achieving effective interdisciplinary care.Circ Cardiovasc Qual Outcomes. 2020; 13:e007264. doi: 10.1161/circoutcomes.120.007264LinkGoogle Scholar
  • 210. Rangaswami J, Mathew RO, Parasuraman R, Tantisattamo E, Lubetzky M, Rao S, Yaqub MS, Birdwell KA, Bennett W, Dalal P, et al. Cardiovascular disease in the kidney transplant recipient: epidemiology, diagnosis and management strategies.Nephrol Dial Transpl. 2019; 34:760–773. doi: 10.1093/ndt/gfz053CrossrefMedlineGoogle Scholar


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