Tsung-Yu Tsai1, Hao Chien2, Feng-Chun Tsai3, Heng-Chih Pan1, Huang-Yu Yang1, Shen-Yang Lee1, Hsiang-Hao Hsu1, Ji-Tseng Fang1, Chih-Wei Yang1, Yung-Chang Chen4. 1. Chang Gung University College of Medicine, Taoyuan, Taiwan; Kidney Research Center, Department of Nephrology, Chang Gung Memorial Hospital, Taiwan. 2. Chang Gung University College of Medicine, Taoyuan, Taiwan. 3. Chang Gung University College of Medicine, Taoyuan, Taiwan; Division of Cardiovascular Surgery, Chang Gung Memorial Hospital, Taiwan. 4. Chang Gung University College of Medicine, Taoyuan, Taiwan; Kidney Research Center, Department of Nephrology, Chang Gung Memorial Hospital, Taiwan. Electronic address: cyc2356@adm.cgmh.org.tw.
Abstract
BACKGROUND/ PURPOSE: Acute kidney injury (AKI) developing during extracorporeal membrane oxygenation (ECMO) is associated with very poor outcome. The Kidney Disease: Improving Global Outcomes (KDIGO) group published a new AKI definition in 2012. This study analyzed the outcomes of patients treated with ECMO and identified the relationship between the prognosis and the KDIGO classification. METHODS: This study examined total 312 patients initially, and finally reviewed the medical records of 167 patients on ECMO support at a tertiary care university hospital between March 2002 and November 2011. Demographic, clinical, and laboratory variables were retrospectively collected as survival predicators. RESULTS: The overall mortality rate was 55.7%. In the analysis of the areas under the receiver operating characteristic curves, the KDIGO classification showed relatively higher discriminatory power (0.840 ± 0.032) than the Risk of renal failure, Injury to the kidney, Failure of kidney function, Loss of kidney function, and End-stage renal failure (RIFLE) (0.826 ± 0.033) and Acute Kidney Injury Network (AKIN) (0.836 ± 0.032) criteria in predicting in-hospital mortality. Furthermore, multiple logistic regression analysis showed that KDIGO, hemoglobin, and Glasgow Coma Scale score on the first day of patients on ECMO were independent predictors for in-hospital mortality. Finally, cumulative survival rates at 6-month follow-up after hospital discharge differed significantly for KDIGO stage 3 versus KDIGO stage 0, 1, and 2 (p < 0.001); and KDIGO stage 2 versus KDIGO stage 0 (p < 0.05). CONCLUSION: For those patients with ECMO support, the KDIGO classification proved to be a more reproducible evaluation tool with excellent prognostic abilities than RIFLE or AKIN classification.
BACKGROUND/ PURPOSE:Acute kidney injury (AKI) developing during extracorporeal membrane oxygenation (ECMO) is associated with very poor outcome. The Kidney Disease: Improving Global Outcomes (KDIGO) group published a new AKI definition in 2012. This study analyzed the outcomes of patients treated with ECMO and identified the relationship between the prognosis and the KDIGO classification. METHODS: This study examined total 312 patients initially, and finally reviewed the medical records of 167 patients on ECMO support at a tertiary care university hospital between March 2002 and November 2011. Demographic, clinical, and laboratory variables were retrospectively collected as survival predicators. RESULTS: The overall mortality rate was 55.7%. In the analysis of the areas under the receiver operating characteristic curves, the KDIGO classification showed relatively higher discriminatory power (0.840 ± 0.032) than the Risk of renal failure, Injury to the kidney, Failure of kidney function, Loss of kidney function, and End-stage renal failure (RIFLE) (0.826 ± 0.033) and Acute Kidney Injury Network (AKIN) (0.836 ± 0.032) criteria in predicting in-hospital mortality. Furthermore, multiple logistic regression analysis showed that KDIGO, hemoglobin, and Glasgow Coma Scale score on the first day of patients on ECMO were independent predictors for in-hospital mortality. Finally, cumulative survival rates at 6-month follow-up after hospital discharge differed significantly for KDIGO stage 3 versus KDIGO stage 0, 1, and 2 (p < 0.001); and KDIGO stage 2 versus KDIGO stage 0 (p < 0.05). CONCLUSION: For those patients with ECMO support, the KDIGO classification proved to be a more reproducible evaluation tool with excellent prognostic abilities than RIFLE or AKIN classification.
Authors: Michael W Manning; Yi-Ju Li; Dean Linder; John C Haney; Yi-Hung Wu; Mihai V Podgoreanu; Madhav Swaminathan; Jacob N Schroder; Carmelo A Milano; Ian J Welsby; Mark Stafford-Smith; Kamrouz Ghadimi Journal: J Cardiothorac Vasc Anesth Date: 2020-11-24 Impact factor: 2.628
Authors: Murat Sargın; Müge Taşdemir Mete; Sevinç Bayer Erdoğan; Hüseyin Kuplay; Murat Baştopçu; Fatih Bayraktar; Murat Acarel; Serap Aykut Aka Journal: Turk Gogus Kalp Damar Cerrahisi Derg Date: 2019-06-21 Impact factor: 0.332