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Improving the Prediction of Cardiac Surgery–Associated Acute Kidney Injury

INTRODUCTION: Acute kidney injury (AKI) is a potentially fatal complication of cardiac surgery. The inability to predict cardiac surgery-associated AKI is a major barrier to prevention and early treatment. Current clinical risk models for the prediction of cardiac surgery-associated AKI are insuffic...

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Autores principales: Crosina, Jordan, Lerner, Jordyn, Ho, Julie, Tangri, Navdeep, Komenda, Paul, Hiebert, Brett, Choi, Nora, Arora, Rakesh C., Rigatto, Claudio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5678656/
https://www.ncbi.nlm.nih.gov/pubmed/29142955
http://dx.doi.org/10.1016/j.ekir.2016.10.003
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author Crosina, Jordan
Lerner, Jordyn
Ho, Julie
Tangri, Navdeep
Komenda, Paul
Hiebert, Brett
Choi, Nora
Arora, Rakesh C.
Rigatto, Claudio
author_facet Crosina, Jordan
Lerner, Jordyn
Ho, Julie
Tangri, Navdeep
Komenda, Paul
Hiebert, Brett
Choi, Nora
Arora, Rakesh C.
Rigatto, Claudio
author_sort Crosina, Jordan
collection PubMed
description INTRODUCTION: Acute kidney injury (AKI) is a potentially fatal complication of cardiac surgery. The inability to predict cardiac surgery-associated AKI is a major barrier to prevention and early treatment. Current clinical risk models for the prediction of cardiac surgery-associated AKI are insufficient, particularly in patients with preexisting kidney dysfunction. METHODS: To identify intraoperative variables that might improve the performance of a validated clinical risk score (Cleveland Clinic Score, CCS) for the prediction of cardiac surgery-associated AKI, we conducted a prospective cohort study in 289 consecutive elective cardiac surgery patients at a tertiary care center. We compared the area under the receiver operator characteristic curve (AUC) of a base model including only the CCS with models containing additional selected intraoperative variables including mean arterial pressure, hematocrit, duration of procedure, blood transfusions, and fluid balance. AKI was defined by the Kidney Disease Improving Global Outcomes 2012 criteria. RESULTS: The CCS alone gave an AUC of 0.72 (95% confidence interval, 0.62–0.82) for postoperative AKI. Nadir intraoperative hematocrit was the only variable that improved AUC for postoperative AKI when added to the CCS (AUC = 0.78; 95% confidence interval, 0.70–0.87; P = 0.002). In the subcohort of patients without preexisting chronic kidney disease (n = 214), where the CCS underperformed (AUC, 0.60 [0.43–0.76]), the improvement with the addition of nadir hematocrit was more marked (AUC, 0.74 [0.62–0.86]). Other variables did not improve discrimination. DISCUSSION: Nadir intraoperative hematocrit is useful in improving discrimination of clinical risk scores for AKI, and may provide a target for intervention.
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spelling pubmed-56786562017-11-15 Improving the Prediction of Cardiac Surgery–Associated Acute Kidney Injury Crosina, Jordan Lerner, Jordyn Ho, Julie Tangri, Navdeep Komenda, Paul Hiebert, Brett Choi, Nora Arora, Rakesh C. Rigatto, Claudio Kidney Int Rep Clinical Research INTRODUCTION: Acute kidney injury (AKI) is a potentially fatal complication of cardiac surgery. The inability to predict cardiac surgery-associated AKI is a major barrier to prevention and early treatment. Current clinical risk models for the prediction of cardiac surgery-associated AKI are insufficient, particularly in patients with preexisting kidney dysfunction. METHODS: To identify intraoperative variables that might improve the performance of a validated clinical risk score (Cleveland Clinic Score, CCS) for the prediction of cardiac surgery-associated AKI, we conducted a prospective cohort study in 289 consecutive elective cardiac surgery patients at a tertiary care center. We compared the area under the receiver operator characteristic curve (AUC) of a base model including only the CCS with models containing additional selected intraoperative variables including mean arterial pressure, hematocrit, duration of procedure, blood transfusions, and fluid balance. AKI was defined by the Kidney Disease Improving Global Outcomes 2012 criteria. RESULTS: The CCS alone gave an AUC of 0.72 (95% confidence interval, 0.62–0.82) for postoperative AKI. Nadir intraoperative hematocrit was the only variable that improved AUC for postoperative AKI when added to the CCS (AUC = 0.78; 95% confidence interval, 0.70–0.87; P = 0.002). In the subcohort of patients without preexisting chronic kidney disease (n = 214), where the CCS underperformed (AUC, 0.60 [0.43–0.76]), the improvement with the addition of nadir hematocrit was more marked (AUC, 0.74 [0.62–0.86]). Other variables did not improve discrimination. DISCUSSION: Nadir intraoperative hematocrit is useful in improving discrimination of clinical risk scores for AKI, and may provide a target for intervention. Elsevier 2016-10-21 /pmc/articles/PMC5678656/ /pubmed/29142955 http://dx.doi.org/10.1016/j.ekir.2016.10.003 Text en © 2016 International Society of Nephrology. Published by Elsevier Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Clinical Research
Crosina, Jordan
Lerner, Jordyn
Ho, Julie
Tangri, Navdeep
Komenda, Paul
Hiebert, Brett
Choi, Nora
Arora, Rakesh C.
Rigatto, Claudio
Improving the Prediction of Cardiac Surgery–Associated Acute Kidney Injury
title Improving the Prediction of Cardiac Surgery–Associated Acute Kidney Injury
title_full Improving the Prediction of Cardiac Surgery–Associated Acute Kidney Injury
title_fullStr Improving the Prediction of Cardiac Surgery–Associated Acute Kidney Injury
title_full_unstemmed Improving the Prediction of Cardiac Surgery–Associated Acute Kidney Injury
title_short Improving the Prediction of Cardiac Surgery–Associated Acute Kidney Injury
title_sort improving the prediction of cardiac surgery–associated acute kidney injury
topic Clinical Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5678656/
https://www.ncbi.nlm.nih.gov/pubmed/29142955
http://dx.doi.org/10.1016/j.ekir.2016.10.003
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