U.S. Clinics Screen for CKM Risk, but Few Use the New Risk Tools
A survey of nearly 100 outpatient and primary care sites participating in a national quality initiative found a wide gap between routine screening for cardiovascular-kidney-metabolic syndrome and the use of the newer tools designed to organize that information into a coherent risk assessment. Most clinics were already checking for pieces of the syndrome. Far fewer were applying the CKM staging framework or the American Heart Association’s PREVENT equations to translate those findings into a formal estimate of cardiovascular risk.
The disconnect matters at the point of care. CKM syndrome is built around the biologic overlap among obesity, type 2 diabetes, chronic kidney disease, hypertension, dyslipidemia, and established cardiovascular disease, conditions that often travel together long before a heart attack, stroke, or heart failure admission occurs. Screening for each condition in isolation can catch fragments of risk, but it does not always tell clinicians how far the disease process has advanced or which patients are most likely to deteriorate next.
Screening Is Common; Structured CKM Assessment Is Not
Across the 97 clinical sites that completed the questionnaire between August 2025 and June 2026, 75% reported screening for CKM-related conditions and 73% said they systematically tested patient populations for CKM risk factors. Social drivers of health screening was also common, reported by 75% of sites. Standardized testing for CKM-related comorbidities reached the same level, suggesting that many practices already recognize the cluster of cardiometabolic and renal problems that define the syndrome.
The more specific tools lagged behind. Only 28% of sites used the PREVENT equations, and just 22% used CKM syndrome staging. Waist circumference, a simple bedside measure that can help identify visceral adiposity and hidden metabolic risk, was used routinely at only 22% of sites. That pattern suggests clinics are seeing the components of CKM syndrome, but not yet fully adopting the framework that connects them.
The gap is especially important because the syndrome is intended to move care upstream. Excess or dysfunctional fat can drive inflammation and metabolic dysfunction, which then accelerates kidney injury and vascular disease. Once chronic kidney disease and subclinical heart disease appear, the risk of progression rises sharply. The staging model is meant to capture that trajectory before the patient reaches overt clinical heart disease.
Why the Staging Framework Changes the Conversation
The CKM staging system divides risk into four stages: excess or dysfunctional fat, chronic kidney disease and/or metabolic risk factors, subclinical heart disease or high-risk equivalents, and clinical heart disease. Each stage marks a deeper layer of vascular and metabolic injury. In practice, that means the clinician is no longer asking only whether hypertension or diabetes is present. The question becomes how much organ damage has already accumulated and how aggressively preventive therapy should be escalated.
PREVENT serves a similar purpose from another angle. Built from contemporary data on more than 6.5 million diverse U.S. adults, the equations estimate 10-year and 30-year cardiovascular risk for adults ages 30 to 79 without known heart disease. The value of a tool like this lies in its ability to anchor decisions about preventive therapy in a broader and more representative risk model than older calculators have provided. When paired with CKM staging, it can help identify people whose heart and kidney risk is greater than a single diagnosis might suggest.
A Quality Initiative Still at an Early Adoption Stage
The survey served as a baseline assessment for sites that joined the American Heart Association’s Cardiovascular-Kidney-Metabolic Health Initiative™, a quality improvement program launched in 2025 and involving about 150 clinical sites nationwide. Participating sites were chosen for reasons that included local CKM burden, structural and societal influences, rural location, and organization type. Most of the responding sites, 92%, were outpatient facilities, with the largest share in primary care. Safety-net organizations made up 44% of the sample, followed by 39% non-academic sites and 16% academic sites.
This mix matters because implementation challenges often differ by setting. A safety-net clinic may have strong exposure to patients with obesity, diabetes, kidney disease, and uncontrolled blood pressure, but limited room for additional workflow complexity. A primary care practice may already perform multiple chronic disease screenings, yet still lack a standardized pathway for CKM staging or unified cardiovascular risk estimation. New tools rarely fail because they are clinically irrelevant; they fail because they are difficult to fit into daily practice without deliberate redesign.
“The baseline is important because it shows we have opportunity to improve patient care as we help clinicians understand how to better incorporate these tools into their practices,” said the study’s lead author, Chiadi Ndumele, MD, PhD, MHS, FAHA, director of the Penn Center for Cardiometabolic Health and Presidential Professor of Medicine at the University of Pennsylvania in Philadelphia.
The Bedside Problem Is Fragmented Risk Recognition
CKM syndrome reflects a biologic chain reaction, not a set of unrelated diagnoses. A patient with excess adiposity may develop insulin resistance and elevated blood glucose, then progressive renal stress, then vascular injury that eventually surfaces as coronary disease, stroke risk, or heart failure. If the evaluation stops at one diagnosis, the care plan may miss the cumulative burden that is driving future events.
This is why the survey’s most striking finding is not that screening is happening, but that comprehensive interpretation remains uncommon. Clinics may be asking about blood pressure, glucose, lipids, kidney function, and weight, yet still not organizing those results through a staging framework. Without that step, it is harder to select the right intensity of statin therapy, antihypertensive treatment, glucose-lowering therapy, weight management, and kidney-protective interventions.
Self-Reported Implementation Leaves Important Gaps
The analysis has clear limits. It relies on self-reported survey data from 97 sites, which leaves room for recall bias and misclassification. Because the initiative selected the sites, selection bias is also possible. The dataset reflects only a portion of the approximately 150 participating sites, so the full implementation picture is still incomplete.
Even with those limitations, the direction of the findings is clinically meaningful. Routine CKM screening appears to be in place at many clinics, but newer assessment tools are not yet embedded in everyday workflow. For now, that means the challenge is less about convincing clinicians that CKM syndrome exists than about helping them turn recognition into a standardized process for staging, risk estimation, and treatment escalation.
Ongoing assessments from the initiative are expected to provide a broader view of adoption barriers and operational opportunities. Until then, the current snapshot shows a field in transition: familiar screening habits on one side, and newer risk tools on the other, still waiting to be absorbed into routine care.