Clinical Validation and Comparative Study Between the KDIGO 2012 AKI Criteria and the AACC Guidance Document 2020

Acute kidney injury (AKI), formerly acute renal failure (ARF), is characterized by a sudden deterioration in renal function, evidenced by a reversible increase in nitrogenous waste products, like serum creatinine and blood urea nitrogen (BUN) over hours to weeks. Up to 15% of hospitalized patients experience these episodes, often leading to complications and mortality. To standardize AKI clinical practice and research, various classifications exist including the Kidney Disease Improving Global Outcomes (KDIGO) guidelines and the American Association for Clinical Chemistry (AACC) (now known as Association for Diagnostics & Laboratory Medicine (ADLM)) guidance document which address biological and assay variability. This study compares two AKI identification criteria the KDIGO 2012 and 20/20 AACC AKI criteria. Two AKI flagging algorithms were developed based on the identification criteria and AKI was flagged for both respectively. AACC diagnostic criteria demonstrate superior performance compared to the KDIGO criteria across matrices including sensitivity, specificity, negative predictive value, and positive predictive value. AACC exhibit a lower false positive rate and false negative rate compared to KDIGO. These findings underscore the practical advantages of the AACC Guidance Document over KDIGO. Additionally, the need for a nephrology consultation to identify AKI was highlighted (P < 0.0001). This study is the first attempt to create and implement algorithms based on both KDIGO 2012 guidelines and AACC 20/20 guidance document to facilitate early diagnosis and timely intervention for management of Acute Kidney Injury in India. The efficacy of the algorithms was tested and compared with data validated by a nephrologist.