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The aim of this study was to identify and validate novel biomarkers for predict acute kidney injury (AKI) subphenotype, major adverse kidney events and other poor outcomes.
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Cardiac surgery-associated acute kidney injury (CSA-AKI) is a serious condition that is associated with increased mortality and morbidity. However, the current criteria for assessing the severity of AKI may not adequately capture the heterogeneity of this condition. This can lead to difficulties in identifying treatment effects in specific patient subgroups, which may contribute to the growing number of negative interventional trials in AKI. To address this issue, researchers have developed and validated two subphenotypes of AKI: resolving and nonresolving. These subphenotypes are based on the trajectory of serum creatinine (SCr) levels in the first 3 days after hospital presentation. By stratifying AKI patients based on these subphenotypes, we can better assess their risk and predict outcomes.
Several novel biomarkers have been developed to aid in the early detection of AKI, discrimination of its underlying causes, and prediction of outcomes. However, it remains unclear whether these biomarkers can accurately predict the development of a nonresolving AKI subphenotype. In our present study, we aim to address this gap in knowledge by conducting a large cohort study. Our goal is to identify and validate novel biomarkers that can effectively detect the resolving subphenotype of AKI, as well as predict major adverse kidney events and other poor outcomes.
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Ying Su, Dr.
Data sourced from clinicaltrials.gov
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