Ezhar Ersöz
Acta Medica Ruha - 2025;3(3):134-142
Introduction: Cardiovascular diseases (CVDs) remain one of the leading causes of morbidity and mortality worldwide. While conventional diagnostic and therapeutic methods have made significant contributions, they may fall short in detecting the disease at early stages and in developing personalized treatment strategies. Objective: This review discusses three innovative approaches -biomarker-based analyses, artificial intelligence (AI)-assisted decision systems, and gut microbiota-focused applications -that have rapidly advanced in recent years and are expanding in their potential clinical applications. Methods: With the advent of next-generation biomarkers (e.g., soluble urokinase-type plasminogen activator receptor [suPAR], suppression of tumorigenicity 2 [ST2], galectin-3, and growth differentiation factor-15 [GDF-15]), processes such as heart failure, myocardial injury, and vascular inflammation can now be assessed more sensitively and at earlier stages. Results: AI algorithms accelerate and enhance diagnostic accuracy by analyzing imaging data, electrocardiogram (ECG) signals, and multivariate clinical parameters. Meanwhile, the influence of gut microbiota on cardiovascular pathophysiology is increasingly understood, with microbial metabolites such as trimethylamine-N-oxide (TMAO) shown to play a significant role in atherosclerotic processes. Conclusion: A comprehensive evaluation of these three approaches offers new perspectives for the development of personalized cardiology practices and lays the groundwork for more effective strategies in diagnosis, monitoring, and treatment.
