Innovative technologies for the identifying risks of chronic kidney disease
Abstract
Chronic kidney disease (CKD) represents a growing global health burden, affecting more than 10% of the adult population worldwide and significantly increasing morbidity, mortality, and healthcare costs. Early identification of individuals at risk of CKD progression remains a major clinical challenge, as traditional diagnostic approaches based on serum creatinine and estimated glomerular filtration rate (eGFR) often detect disease only at advanced stages. Recent advances in innovative technologies—including novel biomarkers, artificial intelligence (AI), omics sciences, digital health tools, and advanced imaging—have transformed risk stratification and early detection of CKD. This review summarizes current and emerging technologies for identifying CKD risk, highlighting their clinical relevance, limitations, and future perspectives. Integration of these innovative tools into routine clinical practice holds promise for improving early diagnosis, personalized risk prediction, and prevention of CKD progression.