External validation of a 2-year all-cause mortality prediction tool developed using machine learning in patients with stage 4-5 chronic kidney disease.

Background: Chronic kidney disease (CKD) is associated with increased mortality. Individual mortality prediction could be of interest to improve individual clinical outcomes. Using an independent regional dataset, the aim of the present study was to externally validate the recently published 2-year all-cause mortality prediction tool developed using machine learning.

External validation of the 2-year mortality prediction tool in hemodialysis patients developed using a Bayesian network.

Background: In recent years, a number of predictive models have appeared to predict the risk of medium-term mortality in hemodialysis patients, but only one, limited to patients aged over 70 years, has undergone sufficiently powerful external validation. Recently, using a national learning database and an innovative approach based on Bayesian networks and 14 carefully selected predictors, we have developed a clinical prediction tool to predict all-cause mortality at 2 years in all incident hemodialysis patients. In order to generalize the results of this tool and propose its use in routine clinical practice, we carried out an external validation using an independent external validation database.

Management of patients with hypertension and chronic kidney disease referred to Hypertension Excellence Centres among 27 countries. On behalf of the European Society of Hypertension Working Group on Hypertension and the Kidney.

Objective Real-life management of patients with hypertension and chronic kidney disease (CKD) among European Society of Hypertension Excellence Centres (ESH-ECs) is unclear : we aimed to investigate it. Methods A survey was conducted in 2023. The questionnaire contained 64 questions asking ESH-ECs representatives to estimate how patients with CKD are managed.

Factors associated with kalemia in renal disease.

Background: International recommendations promote a strict potassium diet in order to avoid hyperkalemia in chronic kidney disease (CKD) patients. However, the efficiency of such a dietary recommendation has never been demonstrated. The objectives of this study were to define the relationship between kalemia, dietary potassium intake estimated by kaliuresis and renal function, and to define the factors associated with kalemia in patients using artificial intelligence.