The Application Prospects of Artificial Intelligence in the Comprehensive Management of Patients with Cardiovascular-Kidney-Metabolic Syndrome

Abstract

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic diseases are closely interrelated and frequently co-occur, significantly increasing the complexity of disease management, posing serious threats to human health, and representing a major public health challenge in China. In response, the American Heart Association has released a Presidential Advisory on Cardiovascular-Kidney-Metabolic (CKM) syndrome, aiming to enhance the collaborative management of patients with these comorbidities. However, current clinical management practices for CKM syndrome face multiple challenges, and the management status is suboptimal. Integrated interventions, interdisciplinary collaboration, and innovative therapies are required to improve outcomes in patients with CKM syndrome [38].There is an urgent need to introduce efficient and precise scientific technologies to assist in the comprehensive management of CKM syndrome patients to reduce cardiovascular and renal risks and improve prognoses. In recent years, artificial intelligence (AI) technology has rapidly advanced in the medical field, methods such as machine learning (ML) have, to a certain extent, enhanced clinicians' ability to obtain accurate diagnoses and make sound clinical decisions [13，24], showing promise as a powerful tool to further enhance the efficiency of clinical management for CKM syndrome. This article will elaborate on the epidemiological status, current management challenges, and the application prospects of AI in CKM syndrome management, providing insights for promoting the integration of AI and CKM syndrome care.