Acute Kidney Injury Classifications in the Prediction of In-hospital Mortality and Renal Function Non-recovery

Aida Hamzic-Mehmedbasic; Melina Mackic; Damir Rebic; Hajrudin Spahovic; Ajla Arnautovic-Halimic; Nadina Jakirlic

doi:10.5455/msm.2023.35.304-308

Acute Kidney Injury Classifications in the Prediction of In-hospital Mortality and Renal Function Non-recovery

Mater Sociomed. 2023;35(4):304-308. doi: 10.5455/msm.2023.35.304-308.

Authors

Aida Hamzic-Mehmedbasic¹, Melina Mackic¹, Damir Rebic², Hajrudin Spahovic³, Ajla Arnautovic-Halimic⁴, Nadina Jakirlic⁵

Affiliations

¹ Juraklinik Scheßlitz, Scheßlitz, Deutschland.
² Nephrology Clinic, Clinical Center University of Sarajevo, Sarajevo, Bosnia and Herzegovina.
³ Urology Clinic, Clinical Center University of Sarajevo, Sarajevo, Bosnia and Herzegovina.
⁴ Clinic for Nuclear Medicine and Endocrinology, Clinical Center University of Sarajevo, Nephrology Clinic, Sarajevo, Bosnia and Herzegovina.
⁵ Radiology Clinic, Clinical Center University of Sarajevo, Nephrology Clinic, Sarajevo, Bosnia and Herzegovina.

Abstract

Background: In the last two decades diagnostic criteria for acute kidney injury (AKI) were developed: Risk, Injury, Failure, Loss of Kidney Function, End-Stage Kidney Disease (RIFLE), Acute Kidney Injury Network (AKIN), and Kidney Disease: Improving Global Outcomes (KDIGO) classifications.

Objective: The study aimed to determine the incidence of AKI based on the RIFLE, AKIN, and KDIGO criteria, as well as analyze their predictive value for mortality and renal function outcome.

Methods: This was a single-center prospective study of patients diagnosed with AKI. Acute kidney injury was defined and classified according to the RIFLE, AKIN, and KDIGO criteria. The outcomes were renal function outcome and in-hospital mortality.

Results: The incidence rates of AKI based on the RIFLE, AKIN, and KDIGO criteria were 13.4%, 14-36%, and 14.64%, respectively. Multiple regression analysis showed that higher stages of AKI according to the KDIGO criteria were independently associated with non-recovery of renal function (p=0.011). However, the predictive ability of RIFLE, AKIN and KDIGO classifications for renal function recovery was poor (Area Under the Receiver Operating Characteristics-AUROC=0.599, AUROC=0.637, AUROC=0.659, respectively). According to the RIFLE and AKIN criteria, in-hospital mortality was statistically significantly higher in stage Failure/3 (p=0.0403 and p=0.0329, respectively) compared to stages Risk/1 and Injury/2. Receiver Operating Characteristics (ROC) analysis showed that all three classifications had poor predictive ability for in-hospital mortality (AUROC=0.675, AUROC=0.66, AUROC=0.681).

Conclusions: KDIGO classification is an independent predictor of renal function non-recovery. However, by ROC analysis, all three classifications have poor predictive ability for renal function outcome and mortality.

Keywords: acute kidney injury; classifications; in-hospital mortality; renal function non-recovery.