Nephrology

Multilevel predictors categorization for post-CABG atrial fibrillation prediction

Postoperative atrial fibrillation (PoAF) is known as common coronary artery bypass grafting (CABG) complication. Despite its association with increased risk of ischemic stroke, bleeding, acute renal failure and mortality there is still no ideal predictive tool with proper clinical interpretability. A retrospective single-center cohort study enrolled 1305 electronic medical records of patients with...

Risk Prediction Modelling of 30-day all-cause mortality following percutaneous coronary intervention in an Australian population: Leveraging Machine Learning

Pre-procedural risk prediction of 30-day all-cause mortality after percutaneous coronary intervention (PCI) aids in clinical decision-making and benchmarking hospital performance. This study aimed to identify pre-procedural factors to predict the risk of 30-day all-cause mortality post-PCI using machine learning (ML) approaches. The study analysed 93,055 consecutive PCI procedures. Boruta feature ...

Predicting Near-term Mortality in Heart Failure: External Validation of Electronic Health Record-Based Deep Learning Model

The dire consequences of heart failure (HF) patient non-response to guideline directed medical therapy often fuel early, non-selective referral for su...

Using discrete- and continuous-time machine learning models (Nnet, CoxNet, GLMnet) to explore sex and age differences in stroke prediction among hypertensive individuals

Stroke is one of the leading causes of death and long-term disability globally. Several studies have investigated the incidence and predictors of stro...

Incidence, Outcomes and Risk Factors of Cardiac Arrest Among Surgical Patients in the UK Biobank: A Population-Based Cohort Study

Perioperative cardiac arrest (CA) is a devastating surgical complication, yet its epidemiology and risk factors across diverse surgical populations ar...

Protective Dietary Antioxidants Intake Attenuate Cardiovascular-Kidney-Metabolic Syndrome Progression

Cardiovascular-kidney-metabolic (CKM) syndrome is characterized by complex pathophysiological interactions among cardiovascular diseases, and chronic ...

Characterizing and Predicting End-of-Life Patient Trajectories Using Routine Clinical Data

Understanding the biological processes that precede death is critical for making informed clinical decisions and facilitating care transitions. Here, ...

Using deep learning methods to shorten acquisition time in children’s renal cortical imaging

This study evaluates the capability of diffusion-based generative models to reconstruct diagnostic-quality renal cortical images from reduced-acquisit...

Symbolic Regression for Mycophenolic Acid Dosage Prediction in Kidney Transplant Recipients

Chronic kidney disease (CKD) affects millions worldwide and often progresses to end-stage renal disease (ESRD), for which kidney transplantation remai...

Metabolic Subphenotypes of Obstructive Sleep Apnea: NHANES 2017-2020 (pre-pandemic)

OSA and MetS have a bidirectional relationship but increasing evidence suggests metabolic heterogeneity in OSA, systematic phenotyping of metabolic dr...

Performance of o1 pro and GPT-4 in self-assessment questions for nephrology board renewal

Large language models (LLMs) are increasingly evaluated in medical education and clinical decision support, but their performance in highly specialize...

A Novel Framework for Evaluating the Clinical Reasoning Process of Large Language Models: A Comparative Study in Nephrology

Although interest in the application of large language models (LLMs) in medicine is growing, accuracy evaluations have largely relied on static knowle...

Deep learning-based prediction of cardiopulmonary disease in retinal images of premature infants

Bronchopulmonary dysplasia (BPD) and pulmonary hypertension (PH) are leading causes of morbidity and mortality in premature infants. To determine whet...

The HeartMagic prospective observational study protocol – characterizing subtypes of heart failure with preserved ejection fraction

Heart failure (HF) is a life-threatening syndrome with significant morbidity and mortality. While evidence-based drug treatments have effectively redu...

Dramatic increases in redundant publications in the Generative AI era

Redundant publication, the practice of submitting the same or substantially overlapping manuscripts multiple times, distorts the scientific record and...

Predicting Rejection Risk in Heart Transplantation: An Integrated Clinical–Histopathologic Framework for Personalized Post-Transplant Care

Cardiac allograft rejection (CAR) remains the leading cause of early graft failure after heart transplantation (HT). Current diagnostics, including hi...

Development of a Hypertension Risk Prediction Model using Nationally Representative Survey Data: A Machine Learning Approach and Web Application Deployment

Hypertension is a major modifiable risk factor for cardiovascular diseases. Early identification of high-risk individuals using predictive models can ...

Non-Traditional Lipid Ratios Predict Cardiovascular-Kidney-Metabolic Syndrome: Insights from Machine Learning Model Using NHANES Data

Cardiovascular-kidney-metabolic (CKM) syndrome is a newly defined multisystem disease continuum characterized by the coexistence of metabolic dysfunct...

Plasma Proteomics Linking Primary and Secondary diseases: Insights into Molecular Mediation from UK Biobank Data

Diabetes, hypertension, and dyslipidemia are major risk factors for cardiovascular (CVD), cerebral, and renal diseases (RD). However, the underlying m...

Comprehensive, Transparent, and Fair Machine Learning Models for Hypertension Risk Prediction: Benchmarking With Framingham, External Validation, Individual-Level Analysis, and Equitable Clinical Utility

Hypertension (HTN) is a leading, yet often underdiagnosed, cause of cardiovascular diseases worldwide. While clinical risk scores like the Framingham ...