RESUMO
OBJECTIVE: The goal of the study was to measure the performance of academic and private practice (PP) neurologists in detecting interictal epileptiform discharges in routine scalp EEG recordings. METHODS: Thirty-five EEG scorers (EEGers) participated (19 academic and 16 PP) and marked the location of ETs in 200 30-second EEG segments using a web-based EEG annotation system. All participants provided board certification status, years of Epilepsy Fellowship Training (EFT), and years in practice. The Persyst P13 automated IED detection algorithm was also run on the EEG segments for comparison. RESULTS: Academic EEGers had an average of 1.66 years of EFT versus 0.50 years of EFT for PP EEGers (P < 0.0001) and had higher rates of board certification. Inter-rater agreement for the 35 EEGers was fair. There was higher performance for EEGers in academics, with at least 1.5 years of EFT, and with American Board of Clinical Neurophysiology and American Board of Psychiatry and Neurology-E specialty board certification. The Persyst P13 algorithm at its default setting (perception value = 0.4) did not perform as well at the EEGers, but at substantially higher perception value settings, the algorithm performed almost as well human experts. CONCLUSIONS: Inter-rater agreement among EEGers in both academic and PP settings varies considerably. Practice location, years of EFT, and board certification are associated with significantly higher performance for IED detection in routine scalp EEG. Continued medical education of PP neurologists and neurologists without EFT is needed to improve routine scalp EEG interpretation skills. The performance of automated detection algorithms is approaching that of human experts.
Assuntos
Eletroencefalografia , Epilepsia/diagnóstico , Centros Médicos Acadêmicos , Algoritmos , Diagnóstico por Computador , Hospitais Privados , Humanos , Neurologistas , Variações Dependentes do Observador , Reconhecimento Automatizado de Padrão , Estudos RetrospectivosRESUMO
OBJECTIVE: The three important questions in video-EEG monitoring are (1) whether it is productive to monitor patients with low outpatient seizure frequency, (2) whether rapid down-titration of antiepileptic drugs (AEDs) during EMU admission helps generate more recorded seizures, and (3) how long a patient who has not yet had a seizure should be monitored in the EMU. This study aimed to answer these three questions. METHODS: Preadmission seizure frequency, times of AED administration, and times of seizure occurrence were collected on all adult patients admitted to the EMU at the Medical University of South Carolina (MUSC) between 2012 and 2014 - a total of 439 patients. The correlations between EMU seizure frequency and both (1) preadmission seizure frequency and (2) rate of antiepileptic drug (AED) down-titration were evaluated. The time of occurrence of seizures was evaluated. RESULTS: There was no correlation between patient-reported outpatient seizure frequency and EMU seizure frequency. In patients who were tapered off AEDs during monitoring, the rate of AED taper correlated with the EMU seizure frequency. Patients whose AEDs were more quickly tapered had higher EMU seizure frequencies. In order to record a first event in patients of unknown seizure type, approximately 3.5days of EMU monitoring was required. SIGNIFICANCE: Clinicians should not hesitate to admit patients with low preadmission seizure frequency to the EMU since many of these patients will have a seizure during monitoring. Faster AED down-titration in the EMU increases EMU seizure frequency. In patients who have not yet had a seizure in the EMU, monitoring should continue for at least four days.