Neill K J Adhikari1,2, Damon C Scales3,4, Carmen Lopez Soto1,2,5, Laura Dragoi1,2, Chinthaka C Heyn6, Andreas Kramer7, Ruxandra Pinto1. 1. Department of Critical Care Medicine, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada. 2. Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada. 3. Department of Critical Care Medicine, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada. damon.scales@sunnybrook.ca. 4. Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada. damon.scales@sunnybrook.ca. 5. Department of Critical Care Medicine, King's College Hospital NHS Foundation Trust, London, UK. 6. Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada. 7. Departments of Critical Care Medicine and Clinical Neurosciences, University of Calgary, Calgary, AB, Canada.
Abstract
BACKGROUND: Predicting neurological outcome in comatose survivors of cardiac arrest relies on clinical findings, radiological and neurophysiological test results. To evaluate the predictive accuracy of brain computed tomography (CT) and magnetic resonance imaging (MRI) for prognostication of neurological outcomes after cardiac arrest. METHODS: We searched MEDLINE (database inception to August 2018) and included all observational cohort studies or randomized controlled trials including adult (16 years or older) survivors of cardiac arrest which evaluated the diagnostic accuracy of CT or MRI for predicting neurologic outcome or mortality. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. All review stages were conducted independently by 2 reviewers, and where possible data were pooled using bivariate meta-analysis. The main outcome was to evaluate the of accuracy of CT and MRI in neuroprognostication of patients after cardiac arrest. RESULTS: We included 44 studies that examined brain CT (n = 24) or MRI (n = 21) in 4008 (n per study, 9-398) patients. Decreased grey to white matter ratio on CT (20 studies) was useful for predicting poor neurological outcome (sensitivity 0.44, 95% CI 0.29-0.60; specificity 0.97, 95% CI 0.93-0.99; positive likelihood ratio [LR+] 13.8, 95% CI 6.9-27.7). Similarly, diffusion-weighted imaging (DWI) on MRI (16 studies; sensitivity 0.77, 95% CI 0.65-0.85; specificity 0.92, 95% CI 0.85-0.96; LR+ 9.2, 95% CI 5.2-16.4) and DWI and fluid-attenuated inversion recovery (FLAIR) MRI (4 studies, sensitivity 0.70, 95% CI 0.43-0.88; specificity 0.95, 95% CI 0.79-0.99; LR+ 13.4, 95% CI 3.5-51.2) were useful for predicting poor neurological outcomes. We found marked heterogeneity in timing of radiological examinations and neurological assessments relative to the cardiac arrest. CONCLUSION: Decreased grey to white matter ratio on CT and DWI or DWI and FLAIR on MRI are useful adjuncts for predicting poor early neurological outcome after cardiac arrest.
BACKGROUND: Predicting neurological outcome in comatose survivors of cardiac arrest relies on clinical findings, radiological and neurophysiological test results. To evaluate the predictive accuracy of brain computed tomography (CT) and magnetic resonance imaging (MRI) for prognostication of neurological outcomes after cardiac arrest. METHODS: We searched MEDLINE (database inception to August 2018) and included all observational cohort studies or randomized controlled trials including adult (16 years or older) survivors of cardiac arrest which evaluated the diagnostic accuracy of CT or MRI for predicting neurologic outcome or mortality. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. All review stages were conducted independently by 2 reviewers, and where possible data were pooled using bivariate meta-analysis. The main outcome was to evaluate the of accuracy of CT and MRI in neuroprognostication of patients after cardiac arrest. RESULTS: We included 44 studies that examined brain CT (n = 24) or MRI (n = 21) in 4008 (n per study, 9-398) patients. Decreased grey to white matter ratio on CT (20 studies) was useful for predicting poor neurological outcome (sensitivity 0.44, 95% CI 0.29-0.60; specificity 0.97, 95% CI 0.93-0.99; positive likelihood ratio [LR+] 13.8, 95% CI 6.9-27.7). Similarly, diffusion-weighted imaging (DWI) on MRI (16 studies; sensitivity 0.77, 95% CI 0.65-0.85; specificity 0.92, 95% CI 0.85-0.96; LR+ 9.2, 95% CI 5.2-16.4) and DWI and fluid-attenuated inversion recovery (FLAIR) MRI (4 studies, sensitivity 0.70, 95% CI 0.43-0.88; specificity 0.95, 95% CI 0.79-0.99; LR+ 13.4, 95% CI 3.5-51.2) were useful for predicting poor neurological outcomes. We found marked heterogeneity in timing of radiological examinations and neurological assessments relative to the cardiac arrest. CONCLUSION: Decreased grey to white matter ratio on CT and DWI or DWI and FLAIR on MRI are useful adjuncts for predicting poor early neurological outcome after cardiac arrest.
Authors: Paul R Hinchey; J Brent Myers; Ryan Lewis; Valerie J De Maio; Eric Reyer; Daniel Licatese; Joseph Zalkin; Graham Snyder Journal: Ann Emerg Med Date: 2010-03-31 Impact factor: 5.721
Authors: Clifton W Callaway; Jasmeet Soar; Mayuki Aibiki; Bernd W Böttiger; Steven C Brooks; Charles D Deakin; Michael W Donnino; Saul Drajer; Walter Kloeck; Peter T Morley; Laurie J Morrison; Robert W Neumar; Tonia C Nicholson; Jerry P Nolan; Kazuo Okada; Brian J O'Neil; Edison F Paiva; Michael J Parr; Tzong-Luen Wang; Jonathan Witt Journal: Circulation Date: 2015-10-20 Impact factor: 29.690
Authors: Saket Girotra; Brahmajee K Nallamothu; John A Spertus; Yan Li; Harlan M Krumholz; Paul S Chan Journal: N Engl J Med Date: 2012-11-15 Impact factor: 91.245
Authors: Erik Edgren; Per Enblad; Ake Grenvik; Anders Lilja; Sven Valind; Lars Wiklund; Ulf Hedstrand; Hans Stjernström; Lennart Persson; Urban Pontén; Bengt Långström Journal: Resuscitation Date: 2003-05 Impact factor: 5.262
Authors: Alyssa E Smith; Alex P Ganninger; Ali Y Mian; Stuart H Friess; Rejean M Guerriero; Kristin P Guilliams Journal: Resuscitation Date: 2022-02-25 Impact factor: 5.262
Authors: Wen Jie Wang; Jie Cui; Guang Wei Lv; Shun Yi Feng; Yong Zhao; Su Li Zhang; Yong Li Journal: Biomed Res Int Date: 2020-11-03 Impact factor: 3.411
Authors: Chun Song Youn; Kyu Nam Park; Soo Hyun Kim; Byung Kook Lee; Tobias Cronberg; Sang Hoon Oh; Kyung Woon Jeung; In Soo Cho; Seung Pill Choi Journal: Crit Care Date: 2022-04-11 Impact factor: 9.097
Authors: Margareta Lang; Christoph Leithner; Michael Scheel; Martin Kenda; Tobias Cronberg; Joachim During; Christian Rylander; Martin Annborn; Josef Dankiewicz; Nicolas Deye; Thomas Halliday; Jean-Baptiste Lascarrou; Thomas Matthew; Peter McGuigan; Matt Morgan; Matthew Thomas; Susann Ullén; Johan Undén; Niklas Nielsen; Marion Moseby-Knappe Journal: Resusc Plus Date: 2022-10-12
Authors: Matthew P Kirschen; Daniel J Licht; Jennifer Faerber; Antara Mondal; Kathryn Graham; Madeline Winters; Ramani Balu; Ramon Diaz-Arrastia; Robert A Berg; Alexis Topjian; Arastoo Vossough Journal: Neurology Date: 2020-11-18 Impact factor: 9.910
Authors: Travis W Murphy; Scott A Cohen; K Leslie Avery; Meenakshi P Balakrishnan; Ramani Balu; Muhammad Abdul Baker Chowdhury; David B Crabb; Karl W Huesgen; Charles W Hwang; Carolina B Maciel; Sarah S Gul; Francis Han; Torben K Becker Journal: Resusc Plus Date: 2020-11-04