Introduction. Acute Kidney Injury (AKI) is characterized by an abrupt decrease in kidney function that triggers severe long term consequences after the event. Prediction of the development of AKI in the (ICU) is limited. Therefore, three prediction tools for AKI were characterized. Methodology. Retrospective observational study, developed from January 31 to September 30, 2020, in adults admitted to the ICU. Patients on renal replacement therapy prior to admission, AKI at the time of admission, history of kidney transplantation, referred from another ICU or a stay of < 48 hours were excluded. Data was collected for a week after admission to intensive care and applied to the renal angina tools (Cruz et al., renal angina index and AKIpredictor). AKI was defined with the KDIGO classification. Results. 1625 patients were admitted to the ICU, of which 490 patients were included. 160 (32.6%) patients presented AKI. The Cruz et al. score presented a sensitivity of 92.8% and specificity of 56.6%, with a negative likelihood ratio (-LR) of 0.13. The renal angina index and AKIpredictor presented an area under the curve of 0.66 (95% CI 0.6-0.73) and 0.66 (95% CI 0.59-0.73) respectively, with a -LR of 0.73 (95% CI 0.6-0.89) and 0.4 (95% CI 0.17-0.77) respectively. Conclusions. The characterization of renal angina tools showed that their usefulness lies in determining which patients are at low risk and require fewer interventions for the prevention of AKI.
publication date
July 28, 2021 8:55 PM
Research
keywords
Analysis of Acute Kidney Injury (AKI) prediction tools
Biomarkers for the diagnosis of Acute Kidney Injury (AKI)
Renal Angina (Clinical Methodology for AKI Risk Stratification)
Risk evolution strategies for AKI in patients admitted to the intensive care
Strategies for the evolution of AKI risk in patients admitted to intensive care
