Risk Stratification for Targeted AKI Prevention After Surgery: Biomarkers and Bundled Interventions.


Journal

Seminars in nephrology
ISSN: 1558-4488
Titre abrégé: Semin Nephrol
Pays: United States
ID NLM: 8110298

Informations de publication

Date de publication:
09 2019
Historique:
entrez: 14 9 2019
pubmed: 14 9 2019
medline: 19 5 2020
Statut: ppublish

Résumé

Perioperative acute kidney injury (AKI) is a surgery-associated complication with increasing incidence, not only because of enhanced awareness for the diagnosis, but also as a result of the aging society with a growing number of severe comorbidities undergoing major surgical procedures. The dilemma of AKI as a global health burden lies in the discrepancy between its importance as a significant risk factor for morbidity and mortality, and the unavailability of specific therapies to modify these adverse outcomes. Thus, it is all the more important to focus management on AKI prevention, and when AKI occurs to focus on early recognition and immediate adaption of individualized care. AKI is the result of an inter-relationship between patient susceptibility and determinants of perioperative exposures. Screening for constellations of risk factors along with measurement of novel biomarkers allows for early identification of patients who are susceptible to AKI and to initiate early targeted care. Targeted care involves implementation of a bundle of interventions adapted from a consensus management guideline, and is a strategy with growing evidence of a beneficial effect on patients' short- and long-term outcomes.

Identifiants

pubmed: 31514909
pii: S0270-9295(19)30058-0
doi: 10.1016/j.semnephrol.2019.06.005
pii:
doi:

Substances chimiques

Biomarkers 0

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

454-461

Informations de copyright

Copyright © 2019 Elsevier Inc. All rights reserved.

Auteurs

Christina Massoth (C)

Department of Anesthesiology, Intensive Care and Pain Medicine, University of Münster, Münster, Germany.

Alexander Zarbock (A)

Department of Anesthesiology, Intensive Care and Pain Medicine, University of Münster, Münster, Germany.

Melanie Meersch (M)

Department of Anesthesiology, Intensive Care and Pain Medicine, University of Münster, Münster, Germany. Electronic address: meersch@uni-muenster.de.

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Classifications MeSH