Predictive Capacity of Oxygen Delivery During Cardiopulmonary Bypass on Acute Kidney Injury.

Autor: Newland RF; Quality and Outcomes, Cardiothoracic Surgical Unit, Flinders Medical Centre, Adelaide, Australia; Perfusion Service, Cardiothoracic Surgical Unit, Flinders Medical Centre, Adelaide, Australia; Department of Surgery, College of Medicine and Public Health, Flinders University, Adelaide, Australia., Baker RA; Quality and Outcomes, Cardiothoracic Surgical Unit, Flinders Medical Centre, Adelaide, Australia; Perfusion Service, Cardiothoracic Surgical Unit, Flinders Medical Centre, Adelaide, Australia; Department of Surgery, College of Medicine and Public Health, Flinders University, Adelaide, Australia. Electronic address: rob.baker@sa.gov.au., Woodman RJ; Flinders Centre for Epidemiology and Biostatistics, Flinders University, Adelaide, Australia., Barnes MB; Flinders Centre for Epidemiology and Biostatistics, Flinders University, Adelaide, Australia., Willcox TW; Greenlane Perfusion, Auckland City Hospital, Auckland, New Zealand; Department of Anaesthesia, University of Auckland, Auckland, New Zealand.
Jazyk: angličtina
Zdroj: The Annals of thoracic surgery [Ann Thorac Surg] 2019 Dec; Vol. 108 (6), pp. 1807-1814. Date of Electronic Publication: 2019 Jun 22.
DOI: 10.1016/j.athoracsur.2019.04.115
Abstrakt: Background: The randomized goal-directed perfusion trial confirmed retrospective findings that a goal-directed perfusion strategy to maintain oxygen delivery index (DO 2 i) during cardiopulmonary bypass greater than 280 mL/min/m 2 reduces the incidence of acute kidney injury (AKI). We developed a predictive model for AKI using data from the Australian and New Zealand Collaborative Perfusion Registry to determine whether these findings could be validated in a real-world clinical setting and to identify an optimal DO 2 i threshold for predictive diagnostic accuracy.
Methods: Data in 19,410 cardiopulmonary bypass procedures were randomly divided into training (n = 9705) and validation (n = 9705) datasets. Multivariate logistic regression was used to determine the best predictive models for AKI (RIFLE [renal Risk, Injury, Failure, Loss of renal function and End-stage renal disease] classification), incremental predictive value of minimum cardiopulmonary bypass DO 2 i, and optimal threshold.
Results: Minimum DO 2 i was significantly associated with any AKI, AKI risk, and AKI injury or greater class in both datasets (validation dataset; any AKI odds ratio [OR], 0.993; 95% confidence interval [CI], 0.991-0.995; P < .001; AKI risk OR, 0.994; 95% CI, 0.992-0.996; P < .001, AKI injury or greater 0.993; 95% CI, 0.991-0.996; P < .001), representing on average a 7% increase in the likelihood of AKI for every 10-mL/min/m 2 decrease in DO 2 i. Diagnostic accuracy was similar for both datasets, with an optimal DO 2 i threshold of 270 mL/min/m 2 . The odds of any AKI were increased by 52% in those below the threshold (OR, 1.52; 95% CI, 1.29-1.77; P < .001).
Conclusions: This study confirms previous findings that minimum DO 2 i during cardiopulmonary bypass is independently associated with AKI, supporting previous findings in a broader-risk, multicenter cohort.
(Copyright © 2019 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
Externí odkaz: