D CHRISTIADI1,2, M LEVY1, S HERATH1,2, J QIAN2, S BROADMAN2, C CAMPBELL3, S KOTWAL1,2,4, J ERLICH1,2, A HORVATH3, Z ENDRE1,2
1Department of Nephrology, Prince Of Wales Hospital, Randwick, Australia, 2University of New South Wales, Kensington, Australia, 3NSW Health Pathology, Department of Clinical Chemistry and Endocrinology, Prince of Wales Hospital, Randwick, Australia, 4The George Institute for Global Health, University of New South Wales, Newtown, Australia
Aim: To assess if calculation of KeGFR is predictive of hospital-acquired AKI (AKI).
Background: AKI has an incidence of approximately 20% and is associated with increased morbidity and mortality. The most effective tool in improving AKI outcomes is early identification which allows KDIGO-based-intervention to ameliorate AKI severity and outcomes.
Methods: This is an observational, retrospective, single-centre study of inpatients identified by AKI electronic Alerts (KDIGO criteria) between 1 April 2019 until 5 October 2019, and electronically followed for a minimum 6 months.
From this cohort, subjects with at least two creatinine (sCr) values within 72 hours of AKI were selected for the KeGFR calculation (Chen’s Formula). For comparison, sCr values were used from contemporaneous patients matched 2:1 for age and comorbidity. Optimal cut-points were determined with Youden’s Index and bootstrapped 1000 times to assess performance.
Results: Of 321 AKI patients, 107 (33%) were readmitted at least once, at a median 40 days (IQR 15 to 125) after discharge. Patients were readmitted because of AKI (48%), a cardiovascular event or fluid overload (15%), or infection (29%). The 6-month mortality was 24.9% (80/321).
A decrease in KeGFR/ (baseline eGFR) greater than 10% predicted AKI with a sensitivity of 68%, a specificity of 77%, positive predictive value of 64%, and negative predictive value of 80%. (n= 398: 148 AKI and 250 controls). The median lead time between KeGFR decrease and AKI was 24 hours (IQR 19 to 27 hours).
Conclusions: KeGFR is a cheap, simple calculation that predicted AKI 24 hours before diagnosis, which might allow early intervention to reduce AKI severity.
Following AKI, there was a high rate of readmission with recurrent AKI.
Daniel Christiadi is currently working as an Acute Kidney Injury Fellow at Prince of Wales Hospital. Graduated from Airlangga University, Indonesia, he completed nephrology training at Canberra Hospital, Royal Darwin Hospital, and Imperial College London in 2019.
He is a conjoint lecturer at the University of New South Wales.