Events and Discharges: First 24 Hours Have the Highest Diagnostic Yield Among Ambulatory EEGs of All Durations
Abstract number :
1.152
Submission category :
3. Neurophysiology / 3C. Other Clinical EEG
Year :
2018
Submission ID :
496539
Source :
www.aesnet.org
Presentation date :
12/1/2018 6:00:00 PM
Published date :
Nov 5, 2018, 18:00 PM
Authors :
Aparna Vaddiparti, University of Connecticut, Hartford Hospital; Medin Karen, Hartford Hospital; and Erica Schuyler, MD, University of Connecticut, Hartford Hospital
Rationale: Ambulatory EEGs are performed to capture a typical clinical event and for identification of ictal and interictal epileptiform discharges. The length of the study (24, 48, or 72 hours) is determined at the discretion of the ordering provider. We aim to determine the diagnostic yield of ambulatory EEGs in increments of 24 hours for these clinical variables in order to guide practitioners when ordering ambulatory studies to achieve the highest diagnostic yield based on their clinical question. Methods: A retrospective analysis of 400 adult ambulatory EEGs with 311, 34 and 55 studies performed for 24, 48 and 72 hours respectively from January 2012 to June 2017 was done with respect to three variables: typical event of interest, inter-ictal epileptiform discharges and electrographic seizures. The median time for identification of these clinical variables and the diagnostic yield of ambulatory EEGs of all durations in the first 24 hours and each subsequent 24-hour time period was determined. The quality of the recording during each time interval was also evaluated. Results: The mean age was 46 years with 51.5% females (n = 206). The overall diagnostic yield of all ambulatory EEGs for all variables was 30.25% (n = 121) with yield for typical event of interest at 11.3% (n=45), inter-ictal discharges at 22.5% (n=90), electrographic seizures at 2% (n=8). The median time for identification of identification of epileptiform discharges was 6hr 23 mins and for electrographic seizures was 29 hr 54 mins. 66% (n=30) of typical events of interest were identified in first 24 hours with 24% (n=11) and 10% (n=4) in 24-48 hour and 48-72-hour time periods. 92% (n=83) of the epileptiform discharges (total n=90) were identified in the first 24-hours with only 7% and 1% (n=1) identified in 24-48 hour and 48-72-hour time periods (p < 0.001). 7.5% (n=30) of all EEGs were degraded by artifact after a median time of 37 hours. Conclusions: The first 24 hours of an ambulatory EEG had the highest diagnostic yield for all clinical variables regardless of the overall duration of EEG. While most (92%) of epileptiform discharges can be identified in the first 24 hours, prolonged ambulatory EEGs may be considered to capture clinical events though a decline in quality with time remains a concern. Funding: None