End Stage Renal Disease

A study on risk factors for the progression from T2DM to end-stage renal disease based on Mendelian randomization and logistic regression analysis.

Using two-sample Mendelian randomization (MR) based on GWAS data from the IEU OpenGWAS project and a retrospective clinical cohort, this study investigated risk factors for progression from type 2 diabetes mellitus (T2DM) to end-stage renal disease (ESRD) and developed a predictive model. The T2DM GWAS dataset (ebi-a-GCST010118; 2020) included 433,540 individuals (77,418 cases and 356,122 controls...

Identification of intradialytic hemodynamic phenotypes using latent profile analysis.

BACKGROUND: Intradialytic blood pressure variations are frequent and associated with poor clinical outcomes. However, the use of arbitrary, inconsistent diagnostic definitions limits cross-study comparability and hinders the development of evidence-based knowledge guiding management. This study aimed to bypass rigid, threshold-based diagnostic criteria using latent profile analysis, an unsupervise...

Development and external validation of a machine learning model for predicting tigecycline-associated drug-induced liver injury.

Tigecycline (TGC) is widely used to treat severe multidrug-resistant infections but can cause drug-induced liver injury. Existing prediction studies f...

Longitudinal Changes in Acid-Base Parameters From Dialysis Initiation to Death in Maintenance Hemodialysis Patients.

INTRODUCTION: Blood gas analysis is routinely performed in hemodialysis patients to monitor acid-base status and serum potassium. Despite frequent tes...

Predictor Of Mortality In Obstructive Sleep Apnoea: Results of Explainable Deep Learning based Survival Analysis From a 15-Year Follow-Up.

INTRODUCTION: Obstructive sleep apnoea (OSA) is a respiratory disorder with comorbidities of several nature, from cardiovascular to renal ones. OSA is...

Predictive modeling of fluid status in hemodialysis: model development and internal validation using the MONitoring dialysis outcomes (MONDO) global database.

BACKGROUND: Optimized fluid management is crucial in dialysis care because extracellular volume overload drives adverse cardiovascular outcomes. At th...

A clinically interpretable model for predicting pharyngocutaneous fistula after total laryngectomy.

BACKGROUND: Pharyngocutaneous fistula (PCF) is a frequent complication following total laryngectomy. While various risk models exist, their practical ...

Association of Histological Features of Cortical and Medullary Peritubular Capillaries With Progressive CKD.

RATIONALE & OBJECTIVE: Peritubular capillary (PTC) rarefaction occurs in chronic kidney disease (CKD), but the independent association of PTC histolog...

Predictive value of the uric acid to high-density cholesterol ratio (UHR) combined with intact parathyroid hormone for protein-energy wasting after incident hemodialysis: a multicenter study.

Protein-energy wasting (PEW) is common in incident hemodialysis patients and linked to poor outcomes. The uric acid/HDL-cholesterol ratio (UHR) and in...

An explainable real-time artificial intelligence -assisted system to reduce intradialytic hypotension.

BACKGROUND: Intradialytic hypotension (IDH) is a frequent complication in hemodialysis and is associated with adverse cardiovascular and neurological ...

Biomarkers in predicting mortality in hemodialysis patients: recent advances.

Patients undergoing maintenance hemodialysis face annual mortality rates of 15-27%, with cardiovascular causes accounting for more than half of all de...

Circulating T-cell phenotypes are influenced by prior Staphylococcus aureus exposure in hemodialysis patients.

Staphylococcus aureus bloodstream infections are a significant risk for hemodialysis patients, who would significantly benefit from a preventative vac...

An Interactive Virtual Nephrologist to Engage Patients With Advanced CKD About Transplantation.

RATIONALE & OBJECTIVE: Despite advantages in survival and quality of life with kidney transplantation (KT) compared to other treatments for kidney fai...

Personalized survival prediction in elderly dialysis patients: integrating machine learning with traditional survival analysis.

BACKGROUND: Elderly patients undergoing kidney replacement therapy (KRT) face high mortality rates. Traditional statistical models describe overall su...

An ensemble machine learning approach for predicting anemia among under-five children in malaria-endemic sub-Saharan African countries.

BACKGROUND: Worldwide, anemia in children under-five is a major public health issue, particularly in sub-Saharan Africa. Sub-Saharan Africa also has t...

Multiple machine learning models for predicting major adverse cardiovascular events in dialysis with clinical and echocardiographic parameters: a retrospective cohort study.

BACKGROUND: Patients undergoing dialysis are at an elevated risk of cardiovascular events. This study aimed to develop machine learning (ML) predictio...

Artificial Intelligence in Peritoneal Dialysis: Applications, Algorithms, and Future Directions.

BACKGROUND: Peritoneal dialysis (PD) naturally lends itself to artificial intelligence (AI) integration due to its generation of dense, longitudinal a...

LWF-YOLO: a lightweight framework based YOLO for blood cell detection.

Accurate detection of blood cells-red blood cells, white blood cells, and platelets-is essential for diagnosing hematological disorders such as anemia...

Correction: Enterocutaneous Fistula-Associated Sepsis and Mortality: Development and Validation of a Multimodal Artificial Intelligence Prediction Model.

[This corrects the article DOI: 10.2196/79985.].

Using artificial intelligence to identify characteristics associated with clinical and economic outcomes in MASH (FOCUS-MASH).

BACKGROUND: Heterogeneity in the disease characteristics of metabolic dysfunction-associated steatohepatitis (MASH) complicates efforts to identify in...