Artificial intelligence in chronic kidney diseases: methodology and potential applications.

Chronic kidney disease (CKD) represents a significant global health challenge, characterized by kidney damage and decreased function. Its prevalence has steadily increased, necessitating a comprehensive understanding of its epidemiology, risk factors, and management strategies. While traditional prognostic markers such as estimated glomerular filtration rate (eGFR) and albuminuria provide valuable insights, they may not fully capture the complexity of CKD progression and associated cardiovascular (CV) risks.This paper reviews the current state of renal and CV risk prediction in CKD, highlighting the limitations of traditional models and the potential for integrating artificial intelligence (AI) techniques. AI, particularly machine learning (ML) and deep learning (DL), offers a promising avenue for enhancing risk prediction by analyzing vast and diverse patient data, including genetic markers, biomarkers, and imaging. By identifying intricate patterns and relationships within datasets, AI algorithms can generate more comprehensive risk profiles, enabling personalized and nuanced risk assessments.Despite its potential, the integration of AI into clinical practice faces challenges such as the opacity of some algorithms and concerns regarding data quality, privacy, and bias. Efforts towards explainable AI (XAI) and rigorous data governance are essential to ensure transparency, interpretability, and trustworthiness in AI-driven predictions.

Double glomerulopathies or two-faced janus? A challenging case in the COVID-19 era.

SARS-CoV-2 very often causes kidney involvement through various mechanisms including: acute tubular injury, virus cell invasion, vascular damage due to hypercoagulability and finally dysregulation of the immune system. Even though there are no pathognomonic morphologic features that can rule out or confirm direct damage by SARS-CoV-2, the latest literature suggests that there may be some association. SARS-CoV-2 infection represents a poor prognostic factor, regardless of pulmonary involvement. We report a challenging case with complex renal biopsy findings suggestive of collapsing glomerulopathy and focal proliferative IgA-dominant glomerulonephritis in a patient affected by active hepatitis C virus (HCV), SARS-CoV-2 infection and personal history of cocaine abuse.