The importance of the urinary output criterion for the detection and prognostic meaning of AKI.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
27 05 2021
Historique:
received: 24 01 2021
accepted: 13 05 2021
entrez: 28 5 2021
pubmed: 29 5 2021
medline: 3 11 2021
Statut: epublish

Résumé

Most reports on AKI claim to use KDIGO guidelines but fail to include the urinary output (UO) criterion in their definition of AKI. We postulated that ignoring UO alters the incidence of AKI, may delay diagnosis of AKI, and leads to underestimation of the association between AKI and ICU mortality. Using routinely collected data of adult patients admitted to an intensive care unit (ICU), we retrospectively classified patients according to whether and when they would be diagnosed with KDIGO AKI stage ≥ 2 based on baseline serum creatinine (Screa) and/or urinary output (UO) criterion. As outcomes, we assessed incidence of AKI and association with ICU mortality. In 13,403 ICU admissions (62.2% male, 60.8 ± 16.8 years, SOFA 7.0 ± 4.1), incidence of KDIGO AKI stage ≥ 2 was 13.2% when based only the SCrea criterion, 34.3% when based only the UO criterion, and 38.7% when based on both criteria. By ignoring the UO criterion, 66% of AKI cases were missed and 13% had a delayed diagnosis. The cause-specific hazard ratios of ICU mortality associated with KDIGO AKI stage ≥ 2 diagnosis based on only the SCrea criterion, only the UO criterion and based on both criteria were 2.11 (95% CI 1.85-2.42), 3.21 (2.79-3.69) and 2.85 (95% CI 2.43-3.34), respectively. Ignoring UO in the diagnosis of KDIGO AKI stage ≥ 2 decreases sensitivity, may lead to delayed diagnosis and results in underestimation of KDIGO AKI stage ≥ 2 associated mortality.

Identifiants

pubmed: 34045582
doi: 10.1038/s41598-021-90646-0
pii: 10.1038/s41598-021-90646-0
pmc: PMC8159993
doi:

Substances chimiques

Creatinine AYI8EX34EU

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

11089

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Auteurs

Jill Vanmassenhove (J)

Renal Department, Gent University Hospital 0K12IA, C. Heymanslaan 10, 9000, Ghent, Belgium.

Johan Steen (J)

Renal Department, Gent University Hospital 0K12IA, C. Heymanslaan 10, 9000, Ghent, Belgium.
Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.
Centre for Justifiable Digital Healthcare, Ghent University Hospital, Ghent, Belgium.
Department of Intensive Care Medicine, Ghent University Hospital, Ghent, Belgium.

Stijn Vansteelandt (S)

Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.
Centre for Justifiable Digital Healthcare, Ghent University Hospital, Ghent, Belgium.
Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK.

Pawel Morzywolek (P)

Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.
Centre for Justifiable Digital Healthcare, Ghent University Hospital, Ghent, Belgium.

Eric Hoste (E)

Department of Intensive Care Medicine, Ghent University Hospital, Ghent, Belgium.

Johan Decruyenaere (J)

Centre for Justifiable Digital Healthcare, Ghent University Hospital, Ghent, Belgium.
Department of Intensive Care Medicine, Ghent University Hospital, Ghent, Belgium.

Dominique Benoit (D)

Department of Intensive Care Medicine, Ghent University Hospital, Ghent, Belgium.

Wim Van Biesen (W)

Renal Department, Gent University Hospital 0K12IA, C. Heymanslaan 10, 9000, Ghent, Belgium. wim.vanbiesen@ugent.be.
Centre for Justifiable Digital Healthcare, Ghent University Hospital, Ghent, Belgium. wim.vanbiesen@ugent.be.

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