• Xiaoqing Liu, Yonghao Xu, Rong Zhang, Yongbo Huang, Weiqun He, Ling Sang, Sibei Chen, Lingbo Nong, Xi Li, Pu Mao, and Yimin Li.
• The State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Diseases, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou 510120, China.
• Plos One. 2016 Jan 1; 11 (6): e0158061.

AbstractExtracorporeal membrane oxygenation (ECMO) is increasingly being applied as life support for acute respiratory distress syndrome (ARDS) patients. However, the outcomes of this procedure have not yet been characterized in severe ARDS patients. The aim of this study was to evaluate the outcomes of severe ARDS patients supported with ECMO and to identify potential predictors of mortality in these patients. A total of 38 severe ARDS patients (aged 51.39±13.27 years, 32 males) who were treated with ECMO in the specialized medical intensive care unit of Guangzhou Institute of Respiratory Diseases from July 2009 to December 2014 were retrospectively reviewed. The clinical data of the patients on the day before ECMO initiation, on the first day of ECMO treatment and on the day of ECMO removal were collected and analyzed. All patients were treated with veno-venous ECMO after a median mechanical ventilation duration of 6.4±7.6 days. Among the 20 patients (52.6%) who were successfully weaned from ECMO, 16 patients (42.1%) survived to hospital discharge. Of the identified pre-ECMO factors, advanced age, a long duration of ventilation before ECMO, a higher Acute Physiology and Chronic Health Evaluation II (APACHE II) score, underlying lung disease, and pulmonary barotrauma prior to ECMO were associated with unsuccessful weaning from ECMO. Furthermore, multiple logistic regression analysis indicated that both barotrauma pre-ECMO and underlying lung disease were independent predictors of hospital mortality. In conclusion, for severe ARDS patients treated with ECMO, barotrauma prior to ECMO and underlying lung disease may be major predictors of ARDS prognosis based on multivariate analysis.

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