Cardiovascular-kidney-metabolic (CKM) syndrome is a systemic disorder characterized by pathophysiological interactions among metabolic risk factors, chronic kidney disease, and the cardiovascular system, leading to multiorgan dysfunction and increased risk of atrial fibrillation, stroke, and heart failure. Atrial cardiomyopathy (ACM) - defined as any structural, contractile, or electrical abnormality of the atria - is an increasingly recognized contributor to cardiovascular morbidity and mortality in this population. Despite growing interest in both conditions, their interplay remains poorly understood, limiting effective preventive strategies and risk-stratification approaches for this high-risk group.
CKM staging offers a practical framework for anticipating ACM onset and progression. Because adiposity-driven inflammation, insulin resistance, hypertension, and early kidney injury act as upstream drivers in CKM, the left atrium becomes an early indicator of hemodynamic load and fibrosis - often preceding sustained atrial fibrillation. Early non-invasive detection of ACM across CKM stages could shift care from treating complications to modifying the underlying substrate.
This prospective observational single-center cohort study aims to phenotype ACM non-invasively across all CKM stages at first diagnosis, using standard 12-lead ECG, advanced transthoracic echocardiography with speckle-tracking, a mechanistically selected biomarker panel (NT-proBNP, MR-proANP, Fetuin-A, FGF23), and cardiac MRI.
Adults aged 18 years or older presenting for cardiovascular evaluation are enrolled and grouped as CKM with ACM (study group) versus CKM without ACM (control group). All participants undergo a single standardized baseline evaluation including clinical examination, 12-lead ECG with Bayés interatrial block grading, comprehensive laboratory panel, and advanced echocardiography including left atrial global longitudinal strain by speckle-tracking.
Primary objective: characterize the relationship between ACM and CKM syndrome stages using non-invasive parameters at first diagnosis. Secondary objectives include assessment of clinical, biological, ECG, and imaging profiles of ACM in CKM; evaluation of left atrial function across CKM stages; examination of Bayés interatrial block correlations and the impact of SGLT2 inhibitors and GLP-1 receptor agonists on left atrial remodeling in HFpEF; and identification of independent ACM risk factors incorporating the full biomarker panel.
Statistical analyses include multivariable logistic regression, biomarker ROC analyses, and penalized regression for derivation of a pragmatic ACM risk score with internal validation. Expected outputs include prevalence estimates, effect sizes for ACM and CKM joint categories, biomarker performance metrics, and a clinic-ready checklist for risk-stratified prevention in outpatient settings.