Abstract
Cardio-Kidney-Metabolic (CKM) disease represents an interconnected spectrum of cardiovascular, renal, and metabolic dysfunctions that significantly contribute to global morbidity and mortality. Recent advances in biomarkers, including trimethylamine N-oxide (TMAO), neutrophil gelatinase-associated lipocalin (NGAL), and soluble ST2 (sST2), have enhanced the precision of early detection and risk stratification. Emerging innovations in artificial intelligence (AI) have further revolutionized CKM care, enabling dynamic risk prediction, personalized treatment, and real-time monitoring. This article discusses cutting- edge biomarkers, AI-driven prevention strategies, and cost-effective interventions while highlighting the integration of environmental and social determinants into CKM prevention frameworks.
Keywords: Cardio-Kidney-Metabolic Disease; Biomarkers; Artificial Intelligence; Prevention Strategies
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