PURPOSE OF REVIEW: Acute brain injury (ABI) is a broad category of pathologies, including traumatic brain injury, and is commonly complicated by seizures. Electroencephalogram (EEG) studies are used to detect seizures or other epileptiform patterns. This review seeks to clarify EEG findings relevant to ABI, explore practical barriers limiting EEG implementation, discuss strategies to leverage EEG monitoring in various clinical settings, and suggest an approach to utilize EEG for triage. RECENT FINDINGS: Current literature suggests there is an increased morbidity and mortality risk associated with seizures or patterns on the ictal-interictal continuum (IIC) due to ABI. Further, increased use of EEG is associated with better clinical outcomes. However, there are many logistical barriers to successful EEG implementation that prohibit its ubiquitous use. Solutions to these limitations include the use of rapid EEG systems, non-expert EEG analysis, machine learning algorithms, and the incorporation of EEG data into prognostic models.
PURPOSE OF REVIEW: Acute brain injury (ABI) is a broad category of pathologies, including traumatic brain injury, and is commonly complicated by seizures. Electroencephalogram (EEG) studies are used to detect seizures or other epileptiform patterns. This review seeks to clarify EEG findings relevant to ABI, explore practical barriers limiting EEG implementation, discuss strategies to leverage EEG monitoring in various clinical settings, and suggest an approach to utilize EEG for triage. RECENT FINDINGS: Current literature suggests there is an increased morbidity and mortality risk associated with seizures or patterns on the ictal-interictal continuum (IIC) due to ABI. Further, increased use of EEG is associated with better clinical outcomes. However, there are many logistical barriers to successful EEG implementation that prohibit its ubiquitous use. Solutions to these limitations include the use of rapid EEG systems, non-expert EEG analysis, machine learning algorithms, and the incorporation of EEG data into prognostic models.
Authors: Lidia M V R Moura; Mouhsin M Shafi; Marcus Ng; Sandipan Pati; Sydney S Cash; Andrew J Cole; Daniel Brian Hoch; Eric S Rosenthal; M Brandon Westover Journal: Neurology Date: 2014-05-23 Impact factor: 9.910
Authors: Jin Jing; Haoqi Sun; Jennifer A Kim; Aline Herlopian; Ioannis Karakis; Marcus Ng; Jonathan J Halford; Douglas Maus; Fonda Chan; Marjan Dolatshahi; Carlos Muniz; Catherine Chu; Valeria Sacca; Jay Pathmanathan; Wendong Ge; Justin Dauwels; Alice Lam; Andrew J Cole; Sydney S Cash; M Brandon Westover Journal: JAMA Neurol Date: 2020-01-01 Impact factor: 18.302
Authors: Michael J Ward; Lori A Shutter; Charles C Branas; Opeolu Adeoye; Karen C Albright; Brendan G Carr Journal: Neurocrit Care Date: 2012-04 Impact factor: 3.210
Authors: Marjolein E Haveman; Michel J A M Van Putten; Harold W Hom; Carin J Eertman-Meyer; Albertus Beishuizen; Marleen C Tjepkema-Cloostermans Journal: Crit Care Date: 2019-12-11 Impact factor: 9.097
Authors: Meike van Sleuwen; Haoqi Sun; Christine Eckhardt; Anudeepthi Neelagiri; Ryan A Tesh; Mike Westmeijer; Luis Paixao; Subapriya Rajan; Parimala Velpula Krishnamurthy; Pooja Sikka; Michael J Leone; Ezhil Panneerselvam; Syed A Quadri; Oluwaseun Akeju; Eyal Y Kimchi; M Brandon Westover Journal: Crit Care Med Date: 2022-01-01 Impact factor: 7.598