Abstracts

Role of CEEG in prognosticating post cardiac arrest in an inner-city hospital

Abstract number : 683
Submission category : 3. Neurophysiology / 3B. ICU EEG
Year : 2020
Submission ID : 2423024
Source : www.aesnet.org
Presentation date : 12/7/2020 9:07:12 AM
Published date : Nov 21, 2020, 02:24 AM

Authors :
Namita Garg, State University of New York Downstate Medical Center; Milagros Silva-Colon - State University of New York Downstate Medical Center; Geetha Chari - State University of New York Downstate Medical Center;;


Rationale:
About half of the patients afflicted by cardiac arrest will die during the hospital stay, often from hypoxic-ischemic brain injury. The aim of this study was to assess the utility of CEEG in the prognosis of post cardiac arrest patients. 
Method:
Retrospective chart review was performed on patients with cardiac arrest between June 2019 to February 2020 who underwent CEEG at King County Hospital, Brooklyn NY. Demographics and clinical data were collected, including presence of clinical seizures and electrographic features on EEG, downtime duration after cardiac arrest, timing of EEG monitoring after arrest, type and duration of sedation, and number of anti-epileptic drugs (AEDs) used to treat the patients. 
Results:
A total of 15 patients [10/15 (67%) female] were included with a mean age of 60.8 years (range 24-82 years). Cardiac arrest occurred out of the hospital in 10 patients (67%), and the average time of ROSC was 20 minutes.  All patients with clinical suspicion of seizures were started on AEDs before the start of EEG monitoring. Myoclonic jerks were reported in nine patients and two had myoclonic status epilepticus.  EEG showed background diffuse attenuation (5, 33%), diffuse slowing (3, 20%), generalized periodic epileptiform discharges (GPDs) or spike and wave discharges (7, 46%), clinical status epilepticus (2, 13%), non-convulsive status epilepticus (1, 7%) and non-epileptic spells (7, 47%).  A total of ten patients (67%) died, 8 had withdrawal of care, 1 was brain dead and 1 patient died in hospice. Of these 5 had diffuse attenuation, 2 had myoclonic status epilepticus, two had diffuse slowing and one had burst suppression pattern. In 3 of the patients who had GPDs, one was pronounced brain dead, one had withdrawal of care, and one patient was discharged to a nursing home.  Out of the 5 who survived post cardiac arrest, 1 was discharged home, 2 to rehab, 1 to a nursing home requiring ventilator and gastrostomy feedings and 1 expired after 36 days due to a 2nd cardiac arrest. Of these 2 had diffuse slowing, 2 had burst suppression pattern and one had diffuse attenuation. 
Conclusion:
The use of cEEG has become more frequent over the last decade, and it is considered one of the most important tools in multiparametric monitoring of neurocritical care patients. There were no significant differences in the CEEG findings between the high mortality and the survivor group. This poses the question on utility of long term monitoring for post-cardiac arrest patients which has always been a controversial issue. However, this study has limitations of having small sample size and retrospective data collection. Even though it can be used as a tool to guide the management, EEG alone cannot be used to predict the prognosis of post-cardiac arrest patients.
Funding:
:None
Neurophysiology