IntroductionAmbulatory electroencephalography (AEEG) is a monitoring technique that allows the recording of continuous EEG activity when patients are at home, without the necessity of admission to the hospital for prolonged video‐EEG monitoring.MethodsThis is a prospective cohort study performed in a Canadian academic centre in order to assess the yield and tolerability of AEEG in the adult population. Over a period of three years, 101 patients were included. The yield of AEEG was assessed by taking into account the questions asked by the clinician before and after the investigation.ResultsOne hundred and one patients undergoing AEEG were prospectively recruited during a three‐year‐period. Our population consisted of 45 males (44.6%) and 56 females (55.4%). The mean age of the group was 36.6±16.1 years. Most of the patients had at least one previous routine EEG (93%). The primary reasons for the AEEGs were subdivided into four categories: a) to differentiate between seizures and non‐epileptic events; b) to determine the frequency of seizures and epileptiform discharges; c) to characterize seizure type or localization; and d) to potentially diagnose epilepsy. The mean duration of AEEG recording was 32±17 hours (15‐96 hours). For 73 (72%) patients, the AEEG provided information that was useful for the management. For 28 (28%) patients, the AEEG did not provide information on diagnosis because no events or epileptiform activity occurred. In only 1 patient was the AEEG inconclusive due to non‐physiological artefacts. Three patients were referred for epilepsy surgery without the necessity of video‐EEG telemetry.ConclusionIn this study, we found that AEEG has a high diagnostic yield (72%) and believe that careful selection of patients is the most important factor for a high diagnostic yield. The main use of AEEG is the characterization of patients with non‐epileptic events, in patients with a diagnosis of epilepsy that is not clear, and quantification of spikes and seizures to improve the medical management. Ambulatory EEG is a cost‐effective solution for increasing demands for in‐hospital video‐EEG monitoring of adult patients.
Surface electroencephalogram (EEG) recording remains the gold standard for noninvasive assessment of electrical brain activity. It is the most efficient way to diagnose and classify epilepsy syndromes as well as define the localization of the epileptogenic zone. The EEG is useful for management decisions and for establishing prognosis in some types of epilepsy. Electroencephalography is an evolving field in which new methods are being introduced. The Canadian Society of Clinical Neurophysiologists convened an expert panel to develop new national minimal guidelines. A comprehensive evidence review was conducted. This document is organized into 10 sections, including indications, recommendations for trained personnel, EEG yield, paediatric and neonatal EEGs, laboratory minimal standards, requisitions, reports, storage, safety measures, and quality assurance.
Background: The StatNet electrode set is a system that can be applied by a non-electroencephalogram (EEG) technologist after minimal training. The primary objectives of this study are to assess the quality and reliability of the StatNet recordings in comparison to the conventional EEG. Methods: Over 10 months, 19 patients with suspected nonconvulsive status epilepticus were included from university hospital emergency settings. Each patient received a StatNet EEG by a trained epilepsy fellow and a conventional EEG by registered technologists. We compared the studies in a blinded fashion, for the timeframe from EEG order to the setup time, start of acquisition, amount of artifact, and detection of abnormalities. The nonparametric Mann-Whitney two-sample t test was used for comparisons. The kappa score was used to assess reliability. Results: Mean age of patients was 61 ± 16.3 (25-93) years. The inter-observer agreement for detection of abnormal findings was 0.83 for StatNet and 0.75 for conventional EEG. Nonconvulsive status epilepticus was detected in 10% (2/19) in both studies. The delay from the time of EEG requisition to acquisition was shorter in the StatNet (22.4 ± 2.5 minutes) than the conventional EEG (217.7 ± 44.6 minutes; p < 0.0001). The setup time was also shorter in the StatNet (9.9 ± 0.8 minutes) compared with the conventional EEG (17.8 ± 0.8 minutes; p < 0.0001). There was no difference in the percentage of artifact duration between the two studies (p = 0.89). Conclusion: This study demonstrates that StatNet EEG is a practical and reliable tool in the emergency setting, which reduces the delay of testing compared with conventional EEG, without significant compromise of study quality.RÉSUMÉ: L'EEG StatNet, une option rapide et fiable pour le diagnostic de crises d'épilepsie non convulsives dans une situation d'urgence. Contexte: Le jeu d'électrodes StatNet est un système qui peut être utilisé par des individus ayant subi un entraînement minimal, qui ne sont pas des techniciens en électroencéphalographie (EEG). Les principaux objectifs de cette étude étaient d'évaluer la qualité et la fiabilité d'enregistrements StatNet par rapport à des enregistrements EEG conventionnels. Méthode: Dix-neuf patients soupçonnés d'être atteints de mal épileptique ont été recrutés dans un contexte d'urgence dans un hôpital universitaire. Ils ont été inclus dans l'étude sur une période de 10 mois. Chaque patient a subi un EEG StatNet effectué par un collègue ayant reçu une formation en épilepsie et un EEG conventionnel effectué par des techniciens diplômés. Nous avons comparé les enregistrements à l'aveugle, quant au délai entre le moment où l'EEG est prescrit et le moment où il est installé, le début de l'enregistrement, la quantité d'artéfacts et la détection d'anomalies. Nous avons utilisé le test non paramétrique de « t » à deux échantillons de Mann-Whitney pour les comparaisons et le score kappa pour évaluer la fiabilité. Résultats: L'âge moyen des patients était de 61 ± 16,3 ans (écart de 25 à 93 ans). La ...
Background and ObjectiveTo evaluate the diagnostic accuracy of the ambulatory EEG (aEEG) at detecting interictal epileptiform discharges (IEDs)/seizures compared with routine EEG (rEEG) and repetitive/second rEEG in patients with a first single unprovoked seizure (FSUS). We also evaluated the association between IED/seizures on aEEG and seizure recurrence within 1 year of follow-up.MethodsWe prospectively evaluated 100 consecutive patients with FSUS at the provincial Single Seizure Clinic. They underwent 3 sequential EEG modalities: first rEEG, second rEEG, and aEEG. Clinical epilepsy diagnosis was ascertained based on the 2014 International League Against Epilepsy definition by a neurologist/epileptologist at the clinic. An EEG-certified epileptologist/neurologist interpreted all 3 EEGs. All patients were followed up for 52 weeks until they had either second unprovoked seizure or maintained single seizure status. Accuracy measures (sensitivity, specificity, negative and positive predictive values, and likelihood ratios), receiver operating characteristic (ROC) analysis, and area under the curve (AUC) were used to evaluate the diagnostic accuracy of each EEG modality. Life tables and the Cox proportional hazard model were used to estimate the probability and association of seizure recurrence.ResultsAmbulatory EEG captured IED/seizures with a sensitivity of 72%, compared with 11% for the first rEEG and 22% for the second rEEG. The diagnostic performance of the aEEG was statistically better (AUC: 0.85) compared with the first rEEG (AUC: 0.56) and second rEEG (AUC: 0.60). There were no statistically significant differences between the 3 EEG modalities regarding specificity and positive predictive value. Finally, IED/seizure on the aEEG was associated with more than 3 times the hazard of seizure recurrence.DiscussionThe overall diagnostic accuracy of aEEG at capturing IED/seizures in people presenting with FSUS was higher than the first and second rEEGs. We also found that IED/seizures on the aEEG were associated with an increased risk of seizure recurrence.Classification of EvidenceThis study provides Class I evidence supporting that, in adults with First Single Unprovoked Seizure (FSUS), 24-h ambulatory EEG has increased sensitivity when compared with routine and repeated EEG.
Background: The DX-Seizure study aims to evaluate the diagnostic accuracy (sensitivity, specificity, positive predictive value, negative predictive value, and likelihood ratio) of the ambulatory EEG in comparison with the first routine EEG, and a second routine EEG right before the ambulatory EEG, on adult patients with first single unprovoked seizure (FSUS) and define the utility of ambulatory EEG in forecasting seizure recurrence in these patients after 1-year follow-up. Methods: The DX-Seizure study is a prospective cohort of 113 adult patients (≥18-yearold) presenting with FSUS to the Single Seizure Clinic for evaluation. These patients will be assessed by a neurologist/epileptologist with the first routine EEG (referral EEG) and undergo a second routine EEG and ambulatory EEG. The three EEG (first routine EEG as gold standard) will be compared and evaluated their diagnostic accuracy (sensitivity, specificity, positive predictive value, negative predictive value, and likelihood ratios) with respect of epileptiform activity and other abnormalities. One-year follow-up of each patient will be used to assess recurrence of seizures after a FSUS and the utility of the ambulatory EEG to forecast these recurrences. Discussion: To the best of our knowledge, this will be the first study to prospectively examine the use of ambulatory EEG for a FSUS in adults and its use for prediction of recurrence of seizures. The overarching goal is to improve diagnostic accuracy with the use of ambulatory EEG in patients with their FSUS. We anticipate that this will decrease incorrect or uncertain diagnoses with resulting psychological and financial cost to the patient. We also anticipate that an improved method to predicting the recurrence of seizures will reduce the chances of repeated seizures and their consequences.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.