Timing of kidney replacement therapy in critically ill patients: A call to shift the paradigm in the era of artificial intelligence

Abstract

Acute kidney injury (AKI) is a common condition in intensive care units (ICUs) and is associated with high mortality rates, particularly when kidney replacement therapy (KRT) becomes necessary. The optimal timing for initiating KRT remains a subject of ongoing debate. Emerging tools and methodologies, such as machine learning and advanced sub-phenotyping, offer promising insights into refining AKI management. Moving beyond the traditional "early" versus "delayed" paradigm and the heavy reliance on serum creatinine measurements, there is an opportunity to develop treatment strategies tailored to the unique pathophysiological and medical context of each patient. Such individualized approaches could potentially improve outcomes and transform AKI management into ICUs. However, KRT is not without risks. Hemodynamic instability poses a significant challenge, complicating the management of critically ill patients. The selection of a KRT modality-whether intermittent hemodialysis, continuous renal replacement therapy, or peritoneal dialysis-introduces additional complexities. Each modality has distinct advantages and limitations, requiring a careful, patient-specific approach to ensure optimal care. This decision-making process is further influenced by the availability of specialized equipment and trained personnel, resources that may be limited in some settings. Notably, current evidence does not demonstrate a clear survival or recovery benefit from the early initiation of dialysis. This narrative review explores the ongoing debates surrounding KRT timing and methodology, highlighting the importance of adopting patient-centric, individualized strategies to navigate the evolving landscape of AKI management.