Clustering-based spatial analysis (CluSA) framework through graph neural network for chronic kidney disease prediction using histopathology images.

Machine learning applied to digital pathology has been increasingly used to assess kidney function and diagnose the underlying cause of chronic kidney disease (CKD). We developed a novel computational framework, clustering-based spatial analysis (CluSA), that leverages unsupervised learning to learn spatial relationships between local visual patterns in kidney tissue. This framework minimizes the need for time-consuming and impractical expert annotations.

Unsupervised machine learning for identifying important visual features through bag-of-words using histopathology data from chronic kidney disease.

Pathologists use visual classification to assess patient kidney biopsy samples when diagnosing the underlying cause of kidney disease. However, the assessment is qualitative, or semi-quantitative at best, and reproducibility is challenging. To discover previously unknown features which predict patient outcomes and overcome substantial interobserver variability, we developed an unsupervised bag-of-words model.

Management of Acute Kidney Injury/Renal Replacement Therapy in the Intensive Care Unit.

Common causes of acute kidney injury (AKI) in the ICU setting include acute tubular necrosis (due to shock, hemolysis, rhabdomyolysis, or procedures that compromise renal perfusion), abdominal compartment syndrome, urinary retention, and interstitial nephritis. Treatment is geared toward addressing the underlying cause. Dialysis may be required if renal injury does not resolve.

Continuous Renal Replacement Therapy among Patients with COVID-19 and Acute Kidney Injury.

Background And Objectives: Acute kidney injury (AKI) is a common complication among patients with COVID-19 and acute respiratory distress syndrome. Reports suggest that COVID-19 confers a pro-thrombotic state, which presents challenges in maintaining hemofilter patency and delivering continuous renal replacement therapy (CRRT). We present our initial experience with CRRT in critically ill patients with COVID-19, emphasizing circuit patency and the association between fluid balance during CRRT and respiratory parameters.

Current Understanding of Clinical Manifestations of COVID-19 in Glomerular Disease.

Background: The novel coronavirus disease (COVID-19), also known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is an evolving pandemic with significant mortality. Information about the impact of infection on glomerular disease patients in particular has been lacking. Understanding the virus's effect in glomerular disease is constantly changing.

Deployment of a New CRRT/PIRRT Device during the COVID-19 Pandemic Emergency: Organizational Challenges and Implementation Results.

Introduction: The coronavirus disease 2019 (COVID-19) pandemic led to increased demand nationwide for dialysis equipment, including supplies and machines. To meet the demand in our institution, our surge plan included rapid mobilization of a novel continuous renal replacement treatment (CRRT) machine named SAMI. The SAMI is a push-pull filtration enhanced dialysis machine that can conjugate extremely high single-pass solute removal efficiency with very precise fluid balance control.