Hiba A Haider1, Rosana Esteller2, Cecil D Hahn2, M Brandon Westover2, Jonathan J Halford2, Jong W Lee2, Mouhsin M Shafi2, Nicolas Gaspard2, Susan T Herman2, Elizabeth E Gerard2, Lawrence J Hirsch2, Joshua A Ehrenberg2, Suzette M LaRoche2. 1. From the Department of Neurology (H.A.H., J.A.E., S.M.L.), Emory University School of Medicine, Atlanta, GA; Neuropace Inc. (R.E.), Mountain View, CA; Division of Neurology (C.D.H.), The Hospital for Sick Children, and Department of Paediatrics, University of Toronto, Canada; Department of Neurology (M.B.W.), Massachusetts General Hospital, Harvard Medical School, Boston; Department of Neurology (J.J.H.), Medical University of South Carolina, Charleston; Brigham and Women's Hospital (J.W.L., M.M.S., S.T.H.), Harvard Medical School, Boston, MA; Université Libre de Bruxelles (N.G.), Brussels, Belgium; Department of Neurology (E.E.G.), Northwestern University Feinberg School of Medicine, Chicago, IL; and Yale University Hospital (L.J.H.), New Haven, CT. hiba.arif@emory.edu. 2. From the Department of Neurology (H.A.H., J.A.E., S.M.L.), Emory University School of Medicine, Atlanta, GA; Neuropace Inc. (R.E.), Mountain View, CA; Division of Neurology (C.D.H.), The Hospital for Sick Children, and Department of Paediatrics, University of Toronto, Canada; Department of Neurology (M.B.W.), Massachusetts General Hospital, Harvard Medical School, Boston; Department of Neurology (J.J.H.), Medical University of South Carolina, Charleston; Brigham and Women's Hospital (J.W.L., M.M.S., S.T.H.), Harvard Medical School, Boston, MA; Université Libre de Bruxelles (N.G.), Brussels, Belgium; Department of Neurology (E.E.G.), Northwestern University Feinberg School of Medicine, Chicago, IL; and Yale University Hospital (L.J.H.), New Haven, CT.
Abstract
OBJECTIVE: To evaluate the sensitivity of quantitative EEG (QEEG) for electrographic seizure identification in the intensive care unit (ICU). METHODS: Six-hour EEG epochs chosen from 15 patients underwent transformation into QEEG displays. Each epoch was reviewed in 3 formats: raw EEG, QEEG + raw, and QEEG-only. Epochs were also analyzed by a proprietary seizure detection algorithm. Nine neurophysiologists reviewed raw EEGs to identify seizures to serve as the gold standard. Nine other neurophysiologists with experience in QEEG evaluated the epochs in QEEG formats, with and without concomitant raw EEG. Sensitivity and false-positive rates (FPRs) for seizure identification were calculated and median review time assessed. RESULTS: Mean sensitivity for seizure identification ranged from 51% to 67% for QEEG-only and 63%-68% for QEEG + raw. FPRs averaged 1/h for QEEG-only and 0.5/h for QEEG + raw. Mean sensitivity of seizure probability software was 26.2%-26.7%, with FPR of 0.07/h. Epochs with the highest sensitivities contained frequent, intermittent seizures. Lower sensitivities were seen with slow-frequency, low-amplitude seizures and epochs with rhythmic or periodic patterns. Median review times were shorter for QEEG (6 minutes) and QEEG + raw analysis (14.5 minutes) vs raw EEG (19 minutes; p = 0.00003). CONCLUSIONS: A panel of QEEG trends can be used by experts to shorten EEG review time for seizure identification with reasonable sensitivity and low FPRs. The prevalence of false detections confirms that raw EEG review must be used in conjunction with QEEG. Studies are needed to identify optimal QEEG trend configurations and the utility of QEEG as a screening tool for non-EEG personnel. CLASSIFICATION OF EVIDENCE REVIEW: This study provides Class II evidence that QEEG + raw interpreted by experts identifies seizures in patients in the ICU with a sensitivity of 63%-68% and FPR of 0.5 seizures per hour.
OBJECTIVE: To evaluate the sensitivity of quantitative EEG (QEEG) for electrographic seizure identification in the intensive care unit (ICU). METHODS: Six-hour EEG epochs chosen from 15 patients underwent transformation into QEEG displays. Each epoch was reviewed in 3 formats: raw EEG, QEEG + raw, and QEEG-only. Epochs were also analyzed by a proprietary seizure detection algorithm. Nine neurophysiologists reviewed raw EEGs to identify seizures to serve as the gold standard. Nine other neurophysiologists with experience in QEEG evaluated the epochs in QEEG formats, with and without concomitant raw EEG. Sensitivity and false-positive rates (FPRs) for seizure identification were calculated and median review time assessed. RESULTS: Mean sensitivity for seizure identification ranged from 51% to 67% for QEEG-only and 63%-68% for QEEG + raw. FPRs averaged 1/h for QEEG-only and 0.5/h for QEEG + raw. Mean sensitivity of seizure probability software was 26.2%-26.7%, with FPR of 0.07/h. Epochs with the highest sensitivities contained frequent, intermittent seizures. Lower sensitivities were seen with slow-frequency, low-amplitude seizures and epochs with rhythmic or periodic patterns. Median review times were shorter for QEEG (6 minutes) and QEEG + raw analysis (14.5 minutes) vs raw EEG (19 minutes; p = 0.00003). CONCLUSIONS: A panel of QEEG trends can be used by experts to shorten EEG review time for seizure identification with reasonable sensitivity and low FPRs. The prevalence of false detections confirms that raw EEG review must be used in conjunction with QEEG. Studies are needed to identify optimal QEEG trend configurations and the utility of QEEG as a screening tool for non-EEG personnel. CLASSIFICATION OF EVIDENCE REVIEW: This study provides Class II evidence that QEEG + raw interpreted by experts identifies seizures in patients in the ICU with a sensitivity of 63%-68% and FPR of 0.5 seizures per hour.
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