Ayham Alkhachroum1, Julie Kromm2,3,4, Michael A De Georgia5. 1. Miller School of Medicine, Neurocritical Care Division, Department of Neurology, University of Miami, Miami, FL, 33146, USA. 2. Cumming School of Medicine, Department of Critical Care Medicine, University of Calgary, Calgary, AB, Canada. 3. Cumming School of Medicine, Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada. 4. Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada. 5. Center for Neurocritical Care, Neurological Institute, University Hospital Cleveland Medical Center, 11100 Euclid Avenue, Cleveland, OH, 44106-5040, USA. michael.degeorgia@uhhospitals.org.
Abstract
PURPOSE OF REVIEW: To describe predictive data and workflow in the intensive care unit when managing neurologically ill patients. RECENT FINDINGS: In the era of Big Data in medicine, intensive critical care units are data-rich environments. Neurocritical care adds another layer of data with advanced multimodal monitoring to prevent secondary brain injury from ischemia, tissue hypoxia, and a cascade of ongoing metabolic events. A step closer toward personalized medicine is the application of multimodal monitoring of cerebral hemodynamics, bran oxygenation, brain metabolism, and electrophysiologic indices, all of which have complex and dynamic interactions. These data are acquired and visualized using different tools and monitors facing multiple challenges toward the goal of the optimal decision support system. In this review, we highlight some of the predictive data used to diagnose, treat, and prognosticate the neurologically ill patients. We describe information management in neurocritical care units including data acquisition, wrangling, analysis, and visualization.
PURPOSE OF REVIEW: To describe predictive data and workflow in the intensive care unit when managing neurologically ill patients. RECENT FINDINGS: In the era of Big Data in medicine, intensive critical care units are data-rich environments. Neurocritical care adds another layer of data with advanced multimodal monitoring to prevent secondary brain injury from ischemia, tissue hypoxia, and a cascade of ongoing metabolic events. A step closer toward personalized medicine is the application of multimodal monitoring of cerebral hemodynamics, bran oxygenation, brain metabolism, and electrophysiologic indices, all of which have complex and dynamic interactions. These data are acquired and visualized using different tools and monitors facing multiple challenges toward the goal of the optimal decision support system. In this review, we highlight some of the predictive data used to diagnose, treat, and prognosticate the neurologically ill patients. We describe information management in neurocritical care units including data acquisition, wrangling, analysis, and visualization.
Authors: Xuan Zhang; Joshua E Medow; Bermans J Iskandar; Fa Wang; Mehdi Shokoueinejad; Joyce Koueik; John G Webster Journal: Physiol Meas Date: 2017-07-24 Impact factor: 2.833
Authors: I Timofeev; C Dahyot-Fizelier; N Keong; J Nortje; P G Al-Rawi; M Czosnyka; D K Menon; P J Kirkpatrick; A K Gupta; P J Hutchinson Journal: Acta Neurochir Suppl Date: 2008