Benoit, Dominique

Decruyenaere, Johan

Hoste, Eric

Steen, Johan

Van Biesen, Wim

Vanmassenhove, Jill

English

Ghent University Academic Bibliography

P0562 DIFFERENT POTENTIAL INTERPRETATIONS OF CRITERIAFOR AKI WHEN USING AUTOMATED DECISION SUPPORT:IMPACT ON ASSOCIATED MORTALITYWim Van Biesen1, Johan Steen1, Johan Decruyenaere2, Dominique Benoit2, EricAdriaan J. Hoste2, Jill Vanmassenhove11Ghent University Hospital, Renal Division, Gent, Belgium and 2Ghent UniversityHospital, Intensive Care Unit, Gent, BelgiumBackground and Aims: The reported associated mortality risks of Acute Kidney Injury(AKI) in the intensive care unit (ICU) are variable. Although the Kidney DiseaseImproving Global Outcome (K-DIGO) improved harmonisation of the definition,there is remaining variability in the actual implementation of this AKI definition, withvariable use of the urinary output (UO) criterion, and different interpretations of thebaseline serum creatinine (Screa). This hampers progress of our understanding of theclinical concept AKI and leads to confusion and unclarity when interpreting models topredict AKI associated outcomes. With the advent of big data and artificial intelligencebased decision algorithms, this problem will only become more of interest, as the userwill not know what exactly the construct AKI in the application used means. Therefore,we intended to explore the impact of different interpretations of the Screa and the UOcriterium as presented in the K-DIGO definition on the associated ICU mortality riskof AKI stage 2 in the ICU.Method: We included all patients of an electronic health data system applied in a terti-ary ICU between 2013 and 2017. Sequential Organ Failure Assessment (SOFA) scorewas calculated, and gender, age, weight and mortality at ICU and in hospital wereextracted. All serum creatinine (sCrea) values during ICU stay and hospitalisation wereextracted, as were UO data, with their time stamps. In addition, all Screa data up to 1year before ICU admission were retrieved from a dataset external to ICU. AKI wasdefined according to KDIGO stage 2, using different possible interpretations of theScrea and/or the UO criterion. For the evolution of Screa as compared to a baselinevalue, we either used a value directly available to ICU staff (def 1), a presumed eGFR of75ml/min (def 2), the first available value after admission to ICU (def 3), the lowestvalue during the current hospitalisation before ICU admission (def 4), the lowest valuebefore the hospitalisation episode as found in an external dataset (def 5). For the UOcriterion, we used either (in line with K-DIGO stage 2) a UO below 6ml/kg during a 12hour block (def 6) or a UO below 0.5ml/kg/hour during each of 12 consecutive onehour intervals (def 7). Definition 8 and 9 identified patients who complied with at leastone out of the Screa criteria 1-5 (def 8) or out of the UO criteria (def 9). Definition 10identified patients who complied both with at least one Screa and one UO criterium.Results: Our dataset comprised 16433 admissions (34.7% female, age 60.7616.4 years).Overall, 8.1% of patients died in Intensive Care Unit (ICU). The SOFA score at admis-sion was 6.964.1. The mortality risk associated with AKI according to the stage 2 defi-nition of K-DIGO varied according to the interpretation of the diagnostic criteria(table). Most important, associated mortality risk was comparable whether a UO (RR2.31, 95% CI 1.90-2.81) or a Screa (RR 2.00, 95% CI 1.57-2.55) criterium was used, andwas highest in patients who complied with both at least one UO and one Screa crite-rium (RR 7.28, 95% CI 6.12-8.65).Conclusion: Unclarity on the actual interpretation of the Screa and UO criteria used inthe K-DIGO definition of AKI leads to substantial differences in AKI associated mortal-ity risk. Omitting the UO criterium leads to substantial underestimation of associatedrisk.Figure: mortality according to different interpretations of the Screa and UO criteria ofK-DIGO AKI stage 2Nephrology Dialysis Transplantation Abstractsdoi:10.1093/ndt/gfaa142 | iii881Downloaded from https://academic.oup.com/ndt/article/35/Supplement_3/gfaa142.P0562/5853028 by Ghent University user on 25 January 2021

Different potential interpretations of criteria for AKI when using automated decision support : impact on associated mortality

https://biblio.ugent.be/publication/8689762/file/8689763.pdf

DIFFERENT POTENTIAL INTERPRETATIONS OF CRITERIA FOR AKI WHEN USING AUTOMATED DECISION SUPPORT: IMPACT ON ASSOCIATED MORTALITY

DIFFERENT POTENTIAL INTERPRETATIONS OF CRITERIA FOR AKI WHEN USING AUTOMATED DECISION SUPPORT: IMPACT ON ASSOCIATED MORTALITY

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