View clinical trials related to Acute Kidney Injury.
Filter by:We aim from this study to investigate the role of renal resistance index (RRI) in evaluation of Acute kidney injury development and fluid administration in sepsis patients considering the change in RRI values over 7 days from admission as a predictor of AKI development
A retrospective study evaluating AKI patients in whom RRT was interrupted for at least 48 hours. Patients who were still RRT-independent 7 days after initial RRT cessation were included in the "Success" group, as opposed to the "Failure" group. Baseline characteristics and variables at the time of RRT interruption were collected. Multivariable analysis was performed and a model was generated to evaluate the prediction of success.
The investigators selected patients diagnosed with sepsis who were admitted to the Intensive Care Unit (ICU) of Huai'an First People's Hospital between June 2022 and December 2023, as well as healthy individuals with normal kidney function during the same period, for the research. The investigators collected blood samples from patients with septic shock or sepsis at 6 hours, 12 hours, 24 hours, 48 hours, 3 days, 5 days, and 7 days after diagnosis， and also collected blood samples from the healthy individuals. The blood samples were stored in gel separation vacuum tubes containing heparin as an anticoagulant. The supernatant was removed and stored at -80°C, and the levels of plasma ELA (enzyme-linked immunosorbent assay) were measured using a standardized ELA kit. Additionally, serum NGAL (neutrophil gelatinase-associated lipocalin) and creatinine levels were measured simultaneously. The subjects were divided into three groups based on the KDIGO diagnostic criteria: sepsis-associated acute kidney injury (S-AKI) group, sepsis non-AKI group, and normal control group. Finally, the data were analyzed to determine the early diagnostic value of ELA for S-AKI. Approximately 70 specimens were collected in total.
The goal of this pilot, randomized, single-blind clinical trial is to estimate the effect size of a high and low mean arterial pressure (MAP)-target algorithm among cirrhosis patients hospitalized with acute kidney injury. The main aims to answer are: • Does an algorithm that has low (<80 mmHg) and high (≥80) MAP-targets lead to significant differences in mean arterial pressure? • Are there any serious adverse events (e.g., ischemia) in a high blood pressure algorithm as compared to a low blood pressure algorithm? • Are there any differences in the incidence of AKI reversal in the high v. low MAP-target groups? Participants will be: 1) Randomized to a clinical algorithm that will either target a low (<80 mmHg) or high (≥80 mmHg) MAP. 2) Depending on their group, investigators will titrate commonly used medications to a specific MAP target. Researchers will compare the high and low MAP-target groups to see if these algorithms lead to significant changes in MAP, if they have any impact on AKI reversal, and if there are any adverse events in the high MAP-target group.
Robotic-assisted laparoscopic prostatectomy (RALP) is the gold standard surgical technique in prostate surgery. Many Robotic-laparoscopic surgical techniques also require the intraoperative deep Trendelenburg position and intravenous fluid restriction during surgery. However, the possible side effects of the deep Trendelenburg's position and the fluid restriction on the cardiovascular and renal systems during surgery are unknown. Although the Trendelenburg position is a life-saving maneuver in hypovolemic patients, it also carries undesirable risks. Long console time may contribute to the development of acute kidney injury (AKI) by prolonging the Trendelenburg time and the fluid-restricted time. In this study, investigators aimed to demonstrate the effect of console time on the development of AKI. Investigators also aimed to determine the hemodynamic risk factors that cause the development of AKI in patients monitored with the pressure Recording Analytical Method (PRAM).
The purpose of this Ph2b study is to characterize the dose-response relationship and to evaluate the safety and efficacy of three different single doses of TIN816 in hospitalized adult participants in an intensive care setting with a diagnosis of sepsis-associated acute kidney injury (SA-AKI).
Thrombotic microangiopathies (TMAs) are a diverse, rare but serious group of diseases. Progress has been made regarding the epidemiology of TMA (Bayer CJASN 2019). It has been shown that secondary TMAs account for 95% of cases, whereas primary TMAs (atypical hemolytic syndromes (HUS) and thrombotic thrombocytopenic purpura (TTP)) account for only about 5%. However, in many cases, the pathophysiology, optimal management and prognosis of TMA remains unclear and it has been shown that patients with TMA may have renal-limited TMA or renal and hematological TMA (ie. With (mechanical anemia, thrombocytopenia, elevated LDH, decreased haptoglobin, schistocytes). In most studies, kidney biopsies are not performed and the diagnostic workup is uncomplete. As this is a rare disease, only a multicenter approach (>20 centers) over a long period of time (>10 years), with adequate diagnostic workup including kidney biopsies can help us to answer these questions (investigators in the present are usually members of the CNR-MAT (a network of the TMA centers in France).
The study is a prospective, non-randomized early feasibility study intended to evaluate the safety and performance of the JuxtaFlow System (also known as the JuxtaFlow Renal Assist Device (RAD)) in participants with pre-existing renal insufficiency who are undergoing cardiac surgery.
The study's objective is to evaluate the additive value of renal biomarkers (from blood and urine) for identifying individuals at high risk for severe acute kidney injury (AKI) above that of a novel natural language processing (NLP)-based AKI risk algorithm. The risk algorithm is based on electronic health records (EHR) data (labs, vitals, clinical notes, and test reports). Patients will enroll at the University of Chicago Medical Center and the University of Wisconsin Hospital, where the risk score will run in real time. The risk score will identify those patients with the highest risk for the future development of Stage 2 AKI and collect blood and urine for biomarker measurement over the subsequent 3 days.
<Development of synthetic medical data generation technology to predict postoperative complications> In order to develop a model for predicting the occurrence of complications after surgery, it is necessary to establish a cohort along with statistical indicators related to the occurrence of complications. This study aims to combine synthetic medical data based on actual clinical data and develop a predictive model based on synthetic medical data. This will allow researchers to conduct research only with synthetic data without dealing with actual medical data, allowing them to use and process data without legal constraints, and to create as much data as they want based on various preprocessed, standardized, and labeled raw data. Patients from three hospitals in Korea (Seoul National University Hospital, Seoul National University Bundang Hospital, Seoul Metropolitan City-Boramae Medical Center) were enrolled for the study. Medical data (both clinical and laboratory) from 410,000 patients who were conducted surgery between 2005 and 2020 were collected to evaluate the performance of the prediction model using AKI-based prediction model development and external verification. Based on the collected patient data, synthetic medical data were combined using the machine learning algorithm, and the anonymity and re-identification of the synthesized medical data were evaluated. Also, the development of AI-based prediction model using synthetic medical data and the actual medical data model were compared.