Nephrology

Solvent-Anion Counterpoised Electrolyte Enables High-Rate Magnesium Metal Batteries.

Magnesium batteries are compelling post-lithium energy storage candidates but suffer from sluggish charge transfer kinetics, fundamentally restricted by the high energy barrier of Mg2+ desolvation. Herein, we address the compact and tenacious solvation sheath induced by the high charge density of Mg2+, characterized by strong electrostatic binding. To effectively weaken the coordination strength a...

Deep learning-based renal artery segmentation and angle estimation for registration of endoscopic images and 3D models in robot-assisted partial nephrectomy.

PURPOSE: Image-guided robot-assisted partial nephrectomy (RAPN) that incorporates three-dimensional (3D) models has improved both oncological and functional outcomes. However, registration between the physical endoscopic image and the 3D virtual model is often performed manually at the kidney level, limiting accuracy and usability. This study aimed to develop a framework built on deep learning to ...

An interpretable machine learning model for predicting stroke in patients with hypertension: insights from the SPRINT.

Stroke is a leading cause of mortality worldwide, with hypertension being its most significant risk factor. However, few studies have specifically dev...

Machine learning prediction of CKD progression in hyperglycemic elderly adults: a prospective community cohort study.

Hyperglycemia is a major risk factor for chronic kidney disease (CKD). This multicenter prospective study developed and validated a machine learning (...

Adapting the REVEAL Lite 2 score to the pediatric population through machine learning: insights from the REHIPED registry for pediatric pulmonary hypertension.

INTRODUCTION AND OBJECTIVES: Risk scores for pulmonary hypertension (PH) have been proven useful in adults. However, no risk score has been validated ...

Empowering Patients and Clinicians: LLMs in Hypertension Care: A Scoping Review.

Large language models have emerged as potential tools to support hypertension care, including diagnosis, treatment decision-making, and patient educat...

Multi-modal machine learning highlights recipient genetic and clinical factors as primary drivers of post-transplant MASLD: A two-center study.

Comprehensive validation of machine learning models predicting chemotherapy related electrolyte disorders in a multicenter study.

BACKGROUND: Electrolyte abnormalities following chemotherapy are common and clinically significant complications in cancer patients and are often asso...

Unsupervised Agglomerative Cluster Phenotyping of Young Patients With Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention.

BACKGROUND: Young patients with acute coronary syndrome (ACS) exhibit diverse demographic, clinical and angiographic characteristics. We hypothesized ...

Using tree-based ensemble methods to produce a population-based mortality risk score in Ontario, Canada.

INTRODUCTION: Risk adjustment is critical in observational epidemiology to control for confounding of the exposure-outcome relationship. Accurate pred...

Beyond social media: the era of generative AI and intelligent digital platforms in nephrology education.

Explainable machine learning integrating bioelectrical impedance for 6-month cardiovascular risk in peritoneal dialysis.

Peritoneal dialysis (PD) is a common treatment for end-stage renal disease, yet cardiovascular disease (CVD) remains a major cause of morbidity. Inade...

Enhancing mesenteric vascular imaging with dual-energy CTA: a comparison of DLIR and ASIR-V using low contrast agent and low radiation dose protocols.

BACKGROUND: Timely diagnosis of mesenteric vascular diseases, especially acute mesenteric ischemia (AMI) due to embolism in the superior mesenteric ar...

Laboratory Medicine Approaches for Assessing Delayed Graft Function in Renal Transplant.

BACKGROUND: Delayed graft function (DGF) remains a significant complication in renal transplantation, adversely affecting graft survival, patient qual...

FOSL2 regulates endothelial cell state and chromatin accessibility in systemic sclerosis pulmonary vascular remodeling.

Systemic sclerosis (SSc) is characterized by fibrosis and vasculopathy affecting the skin and internal organs, leading to multiorgan dysfunction. Inju...

Precision biomarker discovery in hypertension through explainable AI and proteomics.

Hypertension is a major global health burden and a leading driver of cardiovascular disease, yet reliable blood-based biomarkers for early disease are...

Comparative study on the predictive value of PNI and GNRI for all-cause mortality rates of elderly patients in cardiac care unit and cardiovascular intensive care unit.

BACKGROUND: The prognostic nutritional index (PNI) and geriatric nutritional risk index (GNRI) are reliable alternative biomarkers of nutrition. Howev...

Decoding the renal-cochlear axis: explainable machine learning and phenotype clustering reveal high-risk hearing loss subtypes in CKD.

This study develops a dual-level machine learning framework for risk stratification and phenotyping of hearing loss (HL) in patients with chronic kidn...

Explainable machine learning using urinary metabolomics to predict pediatric sepsis-associated acute kidney injury: a two-center prospective observational study.

Sepsis-induced acute kidney injury (S-AKI) is a common and serious complication in critically ill children with a poor prognosis, and its early and ac...

Raman spectroscopy in renal analysis: Technologies, applications, and advancements.

The advantage of Raman spectroscopy (RS) in renal analysis lies in its capacity to non-invasively acquire label-free molecular vibrational fingerprint...