• Ewan C Goligher, Ghislaine Douflé, and Eddy Fan.
• 1 Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada.
• Am. J. Respir. Crit. Care Med. 2015 Jun 15; 191 (12): 1367-73.

AbstractNovel approaches to the management of acute respiratory distress syndrome include strategies to enhance alveolar liquid clearance, promote epithelial cell growth and recovery after acute lung injury, and individualize ventilator care on the basis of physiological responses. The use of extracorporeal membrane oxygenation (ECMO) is growing rapidly, and centers providing ECMO must strive to meet stringent quality standards such as those set out by the ECMONet working group. Prognostic tools such as the RESP score can assist clinicians in predicting outcomes for patients with severe acute respiratory failure but do not predict whether ECMO will enhance survival. Evidence continues to grow that novel modes of mechanical ventilation such as neurally adjusted ventilatory assist are feasible and improve patient physiology and patient-ventilator interaction; data on clinical outcomes are limited but supportive. Critical illness causes long-term psychological and function sequelae: the risk of a new psychiatric diagnosis and severe physical impairment is significantly increased in the months after discharge from the intensive care unit. These long-term effects might be amenable to changes in sedation practice and increased early mobilization. Daily sedation discontinuation enhances the validity of routine delirium assessment. Many critically ill patients merit assessment by palliative care clinicians; the demand for palliative care services among critically ill patients is expected to grow. Future trials to test therapies for critical illness must ensure that study designs are adequately powered to detect benefit using realistic event rates. Integrating "big data" approaches into treatment decisions and trial designs offers a potential means of individualizing care to enhance outcomes for critically ill patients.

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