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Browse 3,902 clinical trials for kidney disease. Find studies that match your criteria and connect with research centers.
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NCT06846034
Diabetes mellitus is a non-transmissible disease whose incidence is growing worldwide . This pathology is defined by a chronic hyperglycaemia linked to a deficiency of either insulin secretion or its action or both. This increased prevalence is linked to the growing of the obese population on one hand, and to the ageing of the population, on the other hand, which is associated with an increased prevalence of metabolic diseases. The number of patients with diabetes, particularly type 2 diabetes (T2D) is regularly increasing. In France, the prevalence of diabetes is 4- 6% of the adult population. Diabetic kidney disease (DKD) is a growing public health problem and therefore constitutes a major factor in progressive kidney disease. DKD has become the leading cause of end stage kidney disease (ESKD), requiring dialysis or transplantation. Current routine screening for DKD is limited to detecting of impaired glomerular filtration rate (GFR) and/or elevated albuminuria, typically manifests in later stages of DKD. Therefore, the current methods to screen for DKD lack the resolution to capture the earliest functional changes associated with DKD. Chronic renal hypoxia plays a crucial role in the development and progression of DKD and may affect Renal hemodynamic. The aim to assess the feasibility of the measure of hypoxa-induced renal hemodynamics parameters.
NCT06842927
The goal of this prospective diagnostic test (correlation) study is to develop and investigate the performance of artificial intelligence in predicting peritoneum transporter status and dialysis efficiency in adult patients undergoing peritoneal dialysis (PD). The main questions it aims to answer are: Can artificial intelligence predict peritoneal transporter status based on simple clinical and biochemical measurements? Can artificial intelligence predict dialysis adequacy (Kt/V) using these features? Researchers will compare the performance of the AI model with the gold standard Peritoneal Equilibration Test (PET) and Kt/V to evaluate its accuracy and reliability. Participants will: Provide peritoneal dialysate and spot urine samples for biochemical analysis. Undergo routine dialysis adequacy and peritoneal equilibration testing (PET). Have clinical and laboratory data collected for AI model training and validation. The study will recruit approximately 350 peritoneal dialysis patients, with 280 participants in the training/validation arm and 70 participants in the test arm. The study duration is 12 months following enrollment.