Abstract: SA-PO133
Comparison of cROCK, KDIGO, and Their Combined Criteria for Detecting AKI in Hospitalized Adults with CKD
Session Information
- AKI: Biomarkers, Imaging, Interventions
November 04, 2023 | Location: Exhibit Hall, Pennsylvania Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Acute Kidney Injury
- 102 AKI: Clinical, Outcomes, and Trials
Authors
- Sun, Ling, Xuzhou Central Hospital, Xuzhou, Jiangsu, China
- Zou, Luxi, Xuzhou Medical University, Xuzhou, Jiangsu, China
Background
Acute kidney injury (AKI) in chronic kidney disease (CKD), also known as acute-on-chronic kidney disease (ACKD) increases the risk of CKD progression, major adverse cardiovascular events (MACEs), and all-cause mortality. Hou et al. set up a reference change value (RCV) of the serum creatinine (SCr) Optimized Criterion for AKI in CKD (cROCK), which is defined as a >25% increase of SCr over 7 days. This study aimed to evaluate the ability of the novel criterion of cROCK to detect ACKD patients and then compared the effects of the criteria of cROCK and KDIGO in predicting long-term outcomes in ACKD patients.
Methods
This was a retrospective observational study with a 3-year follow-up period. The electronic medical records data of inpatients admitted to Xuzhou Central Hospital between January 2016 and June 2018 were screened. All included patients with CKD stage 3 were evaluated using cROCK, KDIGO, and their combined criteria. The renal composite endpoints, MACEs, and all-cause mortality were recorded as the clinical outcomes.
Results
A total of 812 patients was enrolled and assigned to 4 groups depending on the KDIGO and cROCK criteria (Fig 1). The baseline and follow-up data were described in Table 1. The cROCK detected 8.5% more ACKD events than KDIGO criterion (67.98% vs. 59.48%, P < 0.001). During the 3-year follow-up, 683 patients experienced renal composite endpoint events, with groups ranked from high to low percentage of free events as KDIGO(−)&cROCK(−), KDIGO(+)&cROCK(−), KDIGO(−)&cROCK(+), and KDIGO(+)&cROCK(+) (Fig 2A). 650 patients developed MACEs, with groups ranked as KDIGO(−)&cROCK(−), KDIGO(−)&cROCK(+), KDIGO(+)&cROCK(−), and KDIGO(+)&cROCK(+) (Fig 2B). 405 patients died with trends similar to MACEs (Fig 2C).
Conclusion
Compared to the KDIGO criterion, the cROCK detected more ACKD events. Combining the cROCK and KDIGO criteria might improve the predictive ability for long-term outcomes in ACKD patients.
Table and Figure
Funding
- Government Support – Non-U.S.