End Stage Renal Disease

Symptom burden in dialysis patients: determinants and impact on mortality.

BACKGROUND: Symptom burden in chronic kidney disease (CKD) patients has a negative impact on functional status and quality of life. Despite the high prevalence among hemodialysis (HD) patients, symptoms are often underestimated. We investigated the determinants of symptoms and their impact on mortality in a large cohort of HD patients. METHODS: We analyzed 1825 HD patients for whom at least one qu...

Results of a new model of videotraining for patients and caregivers for peritoneal dialysis: food for (AI) thought?

BACKGROUND: In an attempt to overcome the space-time limitations of traditional training we used a new telemedicine home-training model (Videotraining). We report our analysis of Videotraining for automated peritoneal dialysis (APD) carried out between October 1, 2017 and September 30, 2023. METHODS: Videotraining is standardized by breaking down the APD procedures (cycler preparation, connection,...

Endothelial activation and stress index associated with in-hospital mortality risk in patients with end-stage renal disease: a retrospective analysis based on the MIMIC database and machine learning model development.

BACKGROUND: End-stage renal disease (ESRD) is a severe chronic renal disorder with high mortality, requiring dialysis treatment or kidney transplantat...

Development and early feasibility testing of machine-learning algorithms to non-invasively assess hemoglobin levels.

The HeMonitor study evaluated the feasibility and accuracy of non-invasive hemoglobin (Hb) assessment using image-based techniques and machine learnin...

Early Prediction of Diabetic Macular Edema via Machine Learning Survival Analysis on Checkup Data.

PURPOSE: To predict the risk of diabetic macular edema (DME) onset and to identify features of the risk subgroups. DESIGN: Population-based observatio...

Clinical subtypes and prognosis of new-onset atrial fibrillation in critically ill patients.

BACKGROUND: New-onset atrial fibrillation (NOAF) is a common cardiovascular complication in critically ill patients and is consistently associated wit...

Advancing child health: forecasting the next great research achievements.

Advances in pediatric research have improved the lives of infants, children, adolescents, and society at large. A decade ago the American Academy of P...

Machine-learning prediction of 30-day infection-related hospitalization in advanced CKD.

BACKGROUND: Patients with advanced chronic kidney disease (CKD), defined as having an estimated glomerular filtration rate (eGFR) < 45 ml/min/1.73 m²,...

Cyclosporine in hematological disorders: mechanisms, clinical practice and emerging advances.

Cyclosporine A (CsA) functions as a calcineurin inhibitor that perturbs T cell activation via calcineurin-nuclear factor of activated T cells (CaN-NFA...

Capsid Engineering of Adeno-Associated Viruses for Targeted Gene Therapy in Kidney Diseases.

The global burden of chronic and genetic kidney diseases poses a significant challenge to healthcare systems. Current therapies, including dialysis, t...

Time-updated explainable machine learning predicts short-term mortality in peritoneal dialysis patients.

Objective: This study aimed to develop and validate a time-updated, explainable machine learning (ML) early-warning system for short-term mortality ri...

[Application research and evolutionary history of risk prediction models for postoperative pancreatic fistula after pancreaticoduodenectomy].

Postoperative pancreatic fistula (POPF) is a severe complication following pancreaticoduodenectomy,among which clinically relevant postoperative pancr...

Machine Learning Model Predicts Clinical Adverse Events of Small Molecule Kinase Inhibitors in Cancer Patients Using On-/Off-Target Engagement and Tissue Selectivity.

Adverse events (AEs) of small molecule kinase inhibitors (SMKIs) at therapeutic doses in cancer patients are largely unpredictable in phase I-III stud...

Explainable Electronic Medical Record-Based Machine Learning to Predict 1-Year Incident Protein-Energy Wasting in Non-Dialysis Chronic Kidney Disease: A Single-Center Development Study.

BACKGROUND: Protein-energy wasting (PEW) is common in chronic kidney disease (CKD) and is linked to poor outcomes. Early risk stratification may enabl...

Comparative evaluation of information quality, readability, and guideline consistency of large language model-generated educational content on hemodialysis complications: a cross-sectional assessment of generative AI-driven chatbots.

BACKGROUND: Large language models are increasingly becoming a key resource for hemodialysis patients to access information on disease management. Howe...

KIF23 in disease pathogenesis and its therapeutic and diagnostic potential.

BACKGROUND: Kinesin family member 23 (KIF23) is a microtubule-dependent motor protein essential for cytokinesis, organelle transport, and signaling pa...

Evaluating the feasibility of a scalable, digitally supported model for global collaborative surgical research: protocol for a prospective, international, multicentre observational study in cryptoglandular anal fistula treatment (CRAFT).

INTRODUCTION: Management of cryptoglandular anal fistula is characterised by wide variation in diagnostic strategies, surgical techniques and outcome ...

TIME: A Taylor-Inspired Mixed-Effects Model for IDH Prediction.

BACKGROUND: Intradialytic hypotension (IDH) is a critical complication in hemodialysis that increases morbidity and treatment risks, yet existing mach...

Predicting anemia treatment outcomes in maintenance hemodialysis patients using multiple machine learning models.

BACKGROUND: Based on machine learning prediction models, we explored the anemia treatment attainment of patients on maintenance hemodialysis (MHD) and...

Multimodal predictions of end stage chronic kidney disease from asymptomatic individuals for discovery of genomic biomarkers.

Chronic kidney disease (CKD) is a complex condition where the kidneys are damaged and progressively lose their ability to filter blood, 10% of the wor...