Literature DB >> 34120843

Blood Transfusion and Acute Kidney Injury After Total Aortic Arch Replacement for Acute Stanford Type A Aortic Dissection.

Cheng-Nan Li1, Yi-Peng Ge1, Hao Liu1, Chen-Han Zhang1, Yong-Liang Zhong1, Su-Wei Chen1, Yong-Min Liu1, Jun Zheng1, Jun-Ming Zhu1, Li-Zhong Sun2.   

Abstract

AIM: To evaluate the effect of packed red blood cells (pRBCs), fresh frozen plasma (FFP), and platelet concentrate (PC) transfusions on acute kidney injury (AKI) in patients with acute Stanford type A aortic dissection (ATAAD) with total arch replacement (TAR).
METHOD: From December 2015 to October 2017, 421 consecutive patients with ATAAD undergoing TAR were included in the study. The clinical data of the patients and the amount of pRBCs, FFP, and PC were collected. Acute kidney injury was defined using the Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Logistic regression was used to identify whether pRBCs, FFP, and platelet transfusions were risk factors for KDIGO AKI, stage 3 AKI, and AKI requiring renal replacement therapy (RRT).
RESULTS: The mean ± standard deviation age of the patients was 47.67±10.82 years; 77.7% were men; and the median time from aortic dissection onset to operation was 1 day (range, 0-2 days). The median transfusion amount was 8 units (range, 4-14 units) for pRBCs, 400 mL (range, 0-800 mL) for FFP, and no units (range, 0-2 units) for PC. Forty-one (41; 9.7%) patients did not receive any blood products. The rates of pRBC, PC, and FFP transfusions were 86.9%, 49.2%, and 72.9%, respectively. The incidence of AKI was 54.2%. Considering AKI as the endpoint, multivariate logistic regression showed that pRBCs (odds ratio [OR], 1.11; p<0.001) and PC transfusions (OR, 1.28; p=0.007) were independent risk factors. Considering KDIGO stage 3 AKI as the endpoint, multivariate logistic regression showed that pRBC transfusion (OR, 1.15; p<0.001), PC transfusion (OR, 1.28; p<0.001), a duration of cardiopulmonary bypass (CPB) ≥293 minutes (OR, 2.95; p=0.04), and a creatinine clearance rate of ≤85 mL/minute (OR, 2.12; p=0.01) were independent risk factors. Considering RRT as the endpoint, multivariate logistic regression showed that pRBC transfusion (OR, 1.12; p<0.001), PC transfusion (OR, 1.33; p=0.001), a duration of CPB ≥293 minutes (OR, 3.79; p=0.02), and a creatinine clearance rate of ≤85 mL/minute (OR, 3.34; p<0.001) were independent risk factors.
CONCLUSIONS: Kidney Disease: Improving Global Outcomes-defined stage AKI was common after TAR for ATAAD. Transfusions of pRBCs and PC increased the incidence of AKI, stage 3 AKI, and RRT. Fresh frozen plasma transfusion was not a risk factor for AKI.
Copyright © 2021 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Acute Stanford Type A aortic dissection; Acute kidney injury; Fresh frozen plasma; Packed red blood cells; Platelet concentrates; Total aortic arch replacement

Mesh:

Year:  2021        PMID: 34120843     DOI: 10.1016/j.hlc.2021.05.087

Source DB:  PubMed          Journal:  Heart Lung Circ        ISSN: 1443-9506            Impact factor:   2.975


  4 in total

1.  Identification of risk factors for postoperative stage 3 acute kidney injury in patients who received surgical repair for acute type A aortic dissection.

Authors:  Zhigang Wang; Min Ge; Zheyun Wang; Cheng Chen; Lichong Lu; Lifang Zhang; Dongjin Wang
Journal:  BMC Surg       Date:  2022-03-02       Impact factor: 2.102

2.  Serum Lactate Level in Early Stage Is Associated With Acute Kidney Injury in Traumatic Brain Injury Patients.

Authors:  Ruoran Wang; Shaobo Wang; Jing Zhang; Min He; Jianguo Xu
Journal:  Front Surg       Date:  2022-01-31

3.  Risk factors for acute kidney injury after Stanford type A aortic dissection repair surgery: a systematic review and meta-analysis.

Authors:  Lei Wang; Guodong Zhong; Xiaochai Lv; Yi Dong; Yanting Hou; Xiaofu Dai; Liangwan Chen
Journal:  Ren Fail       Date:  2022-12       Impact factor: 3.222

4.  Prediction model of acute kidney injury after different types of acute aortic dissection based on machine learning.

Authors:  Li Xinsai; Wang Zhengye; Huang Xuan; Chu Xueqian; Peng Kai; Chen Sisi; Jiang Xuyan; Li Suhua
Journal:  Front Cardiovasc Med       Date:  2022-09-21
  4 in total

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