End Stage Renal Disease

Central venous catheters tip positioning: Insights from a retrospective analysis.

BACKGROUND: Tunneled central venous catheters (tCVCs) are essential in hemodialysis when arteriovenous access is not feasible. Their correct positioning is crucial to ensure efficient dialysis and prevent complications such as stenosis and thrombosis. METHODS: This retrospective, non-randomized study reviewed all tCVC placements performed from January 2017 to December 2024 at the Nephrology Depart...

Digital versus analogue PET in parathyroid imaging: comparison of PET metrics and machine learning-based characterisation of hyperfunctioning lesions (the DIGI-PET study).

PURPOSE: To compare PET-derived metrics between digital and analogue PET/CT in hyperparathyroidism, and to assess whether machine learning (ML) applied to quantitative PET parameters can distinguish parathyroid adenoma (PA) from hyperplasia (PH). METHODS: From an initial multi-centre cohort of 179 patients, 86 were included, comprising 89 PET-positive lesions confirmed histologically (74 PA, 15 PH...

A holistic framework for intradialytic hypotension prediction using generative adversarial networks-based data balancing.

BACKGROUND: Intradialytic Hypotension (IDH) is a frequent complication in hemodialysis, yet predictive modeling is challenged by class imbalance. Trad...

Cellular senescence in renal ischemia-reperfusion injury.

Acute kidney injury (AKI) affects more than 20% of hospitalized patients and is a significant contributor to morbidity and mortality, primarily due to...

Multiple omics-based machine learning reveals peripheral blood immune cell landscape during acute rejection of kidney transplantation and constructs a precise non-invasive diagnostic strategy.

Kidney transplantation is the optimal treatment for end-stage renal disease (ESRD), but acute rejection (AR) remains a major factor affecting graft su...

Effectiveness of a smart management system in improving adherence and clinical outcomes of patients receiving peritoneal dialysis: a retrospective cohort analysis.

BACKGROUND: Peritoneal dialysis (PD) is a widely used form of home dialysis. However, the efficacy of telehealth care in long-term management for PD p...

Identification and validation of parthanatos-related genes in end-stage renal disease.

BACKGROUND: End-Stage Renal Disease (ESRD) is a severe chronic kidney disease with a rising global incidence, often accompanied by various complicatio...

Visit-to-visit blood pressure variability as a prognostic marker in peritoneal dialysis: insights from machine learning-based risk models.

Enhancing sarcasm detection in sentiment analysis for cyberspace safety using advanced deep learning techniques.

Social media has become an integral part of daily life, with platforms like Twitter serving as popular outlets for users to share information and expr...

Exploring predictive models for intradialytic hypotension risk in maintenance hemodialysis patients: A systematic review.

BACKGROUND: This systematic review evaluates existing risk prediction models for intradialytic hypotension (IDH) in maintenance hemodialysis (MHD) pat...

Machine Learning for Discriminating Microcytic Hypochromic Anemia Based on Erythrocyte Parameters.

INTRODUCTION: Thalassemia trait (TT) and iron deficiency anemia (IDA) are two common types of microcytic hypochromic anemia (MHA), but current diagnos...

The Role of Precision Nutrition in Kidney Disease.

Precision nutrition utilizes an individualized approach in which dietary interventions are tailored according to patients' genetic, biologic, and envi...

Machine learning-based prediction model for arteriovenous fistula thrombosis risk: a retrospective cohort study from 2017 to 2024.

BACKGROUND: Thrombosis of arteriovenous fistulas represents a prevalent complication among patients undergoing hemodialysis, characterized by a notabl...

An explainable machine learning model for early warning of hypertensive and hypotensive anomalies in maintenance hemodialysis patients.

BACKGROUND: Intradialytic hypotension (IDH) and intradialytic hypertension (IDHTN) are major complications of maintenance hemodialysis (MHD) that sign...

Method for Predict Stenosis of Arteriovenous Fistula Patients Based on Machine Learning.

OBJECTIVES: Arteriovenous fistula (AVF) is the most ideal vascular access for hemodialysis. People with AVF have a longer vascular access survival rat...

A Comparative Assessment of Large Language Models in Pediatric Dialysis: Reliability, Quality and Readability.

INTRODUCTION: This study evaluated the reliability, quality, and readability of ChatGPT (OpenAI, San Francisco, CA), Gemini (Google, Mountain View, CA...

Advanced molecular approaches to thalassemia disorder and the selection of molecular-level diagnostic testing in resource-limited settings.

Beta-thalassemia is a genetic disorder that significantly burdens healthcare systems globally. This inherited blood disorder, categorized into beta-th...

Sepsis criteria and kidney function: eliminating sex, age and economic status biases.

The kidney is a target organ for the dysregulated host response to infection that defines sepsis, and acute kidney injury (AKI) is often an early mani...

Assessing serum thrombopoietin for enhanced diagnosis of ITP, AA, and MDS using machine learning: A retrospective cohort study.

Differentiating between immune thrombocytopenia (ITP), aplastic anemia (AA), and myelodysplastic syndromes (MDS) is critical due to the distinct treat...

Advancing blood cell detection and classification: performance evaluation of modern deep learning models.

The detection and classification of blood cells are important in diagnosing and monitoring a variety of blood-related illnesses, such as anemia, leuke...