Mustafa Aykut Kural1, Hatice Tankisi1, Lene Duez1, Vibeke Sejer Hansen1, Aparna Udupi2, Richard Wennberg3, Stefan Rampp4, Pål G Larsson5, Reinhard Schulz6, Sándor Beniczky7. 1. Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark. 2. Section for Biostatistics, Department of Public Health, Aarhus University, Denmark. 3. Krembil Brain Institute, Toronto Western Hospital, University of Toronto, Toronto, Canada. 4. Department of Neurosurgery, University Hospital Erlangen, Germany and Department of Neurosurgery, University Hospital Halle (Saale), Germany. 5. Department of Neurosurgery, Rikshospitalet, Oslo University Hospital, Oslo, Norway. 6. Epilepsy Center Bethel, Mara Hospital, Bielefeld, Germany. 7. Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Neurophysiology, Danish Epilepsy Centre, Dianalund, Denmark; Department of Clinical Medicine, Aarhus University, Denmark. Electronic address: sbz@filadelfia.dk.
Abstract
OBJECTIVE: To find and validate the optimal combination of criteria that define interictal epileptiform EEG discharges (IEDs). Our target was a specificity over 95%, to avoid over-reading in clinical EEG. METHODS: We constructed 63 combinations of the six criteria from the operational definition of IEDs, recently issued in the EEG-glossary of the International Federation of Clinical Neurophysiology (IFCN). The diagnostic gold standard was derived from video-EEG recordings. In a testing EEG dataset from 100 patients, we selected the best performing combinations of criteria and then we validated them in an independent dataset from 70 patients. We compared their performance with subjective, expert-scorings and we determined inter-rater agreement (IRA). RESULTS: Without using criteria, the specificity of expert-scorings was lower than the pre-defined threshold (86%). The best performing combination of criteria was the following: waves with spiky morphology, followed by a slow-afterwave and voltage map suggesting a source in the brain. In the validation dataset this achieved a specificity of 97% and a sensitivity of 89%. IRA was substantial. CONCLUSIONS: The optimized set of criteria for defining IEDs has high accuracy and IRA. SIGNIFICANCE: Using these criteria will contribute to decreasing over-reading of EEG and avoid misdiagnosis of epilepsy.
OBJECTIVE: To find and validate the optimal combination of criteria that define interictal epileptiform EEG discharges (IEDs). Our target was a specificity over 95%, to avoid over-reading in clinical EEG. METHODS: We constructed 63 combinations of the six criteria from the operational definition of IEDs, recently issued in the EEG-glossary of the International Federation of Clinical Neurophysiology (IFCN). The diagnostic gold standard was derived from video-EEG recordings. In a testing EEG dataset from 100 patients, we selected the best performing combinations of criteria and then we validated them in an independent dataset from 70 patients. We compared their performance with subjective, expert-scorings and we determined inter-rater agreement (IRA). RESULTS: Without using criteria, the specificity of expert-scorings was lower than the pre-defined threshold (86%). The best performing combination of criteria was the following: waves with spiky morphology, followed by a slow-afterwave and voltage map suggesting a source in the brain. In the validation dataset this achieved a specificity of 97% and a sensitivity of 89%. IRA was substantial. CONCLUSIONS: The optimized set of criteria for defining IEDs has high accuracy and IRA. SIGNIFICANCE: Using these criteria will contribute to decreasing over-reading of EEG and avoid misdiagnosis of epilepsy.
Authors: A E Vaudano; L Mirandola; F Talami; G Giovannini; G Monti; P Riguzzi; L Volpi; R Michelucci; F Bisulli; E Pasini; P Tinuper; L Di Vito; G Gessaroli; M Malagoli; G Pavesi; F Cardinale; L Tassi; L Lemieux; S Meletti Journal: Brain Topogr Date: 2021-06-21 Impact factor: 3.020
Authors: Christos Papadelis; Shannon E Conrad; Yanlong Song; Sabrina Shandley; Daniel Hansen; Madhan Bosemani; Saleem Malik; Cynthia Keator; M Scott Perry Journal: Front Hum Neurosci Date: 2022-01-25 Impact factor: 3.169