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.
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.
Study Type
OBSERVATIONAL
Enrollment
358
Shanghai Zhongshan Hospital
Shanghai, Shanghai Municipality, China
AKI nonresolving subphenotype
The resolving subphenotype was defined by a decrease of 0.3 mg/dl or 25% in SCr from its maximum during the first 3 days of study enrollment. All subjects with AKI who did not meet this criterion were classified as having a nonresolving subphenotype
Time frame: 7 days
Major adverse kidney events at 30 days
Major adverse kidney events (MAKE) was defined as the composite of≥25% loss in estimated glomerular filtration rate (eGFR), dialysis, or death. Estimated GFR was calculated from serum creatinine using the MDRD equation.
Time frame: 30 days
Major adverse kidney events at 90 days
MAKE was defined as the composite of≥25% loss in estimated glomerular filtration rate (eGFR), dialysis, or death. Estimated GFR was calculated from serum creatinine using the MDRD equation.
Time frame: 90 days
Major adverse kidney events at 365 days
MAKE was defined as the composite of≥25% loss in estimated glomerular filtration rate (eGFR), dialysis, or death. Estimated GFR was calculated from serum creatinine using the modification of diet in renal disease (MDRD) equation.
Time frame: 365 days
Mortality
Mortality at 30 days, 90 days and 365 days
Time frame: 365 days
Receipt of renal replacement treatment
Patients received renal replacement treatment during hospital stay
Time frame: 365 days
Moderate and severe AKI
Kidney Disease Improving Global Outcomes (KDIGO) stage 2 or stage 3
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Time frame: 7 days
AKI progression
worsening of KDIGO stage within 1 week (progressing from stage 1 to either stage 2 or stage 3, or from stage 2 to stage 3). Patients diagnosed with progressive or persisting stage 3 AKI (stage 3 AKI for \>3 consecutive days) were classified as having AKI progression. If patients who presented with stage 3 AKI but not requiring RRT subsequently required dialysis or developing persist severe AKI or death within 7 days, this was considered progression.
Time frame: 7 days
Composite Outcome
Stage 3 AKI, renal replacement therapy or death through outpatient or telephone follow-up
Time frame: 30 days