Diagnostic Accuracy of Ambulatory EEG vs Routine EEG in Patients With First Single Unprovoked Seizure.

Background and Objective: To 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. Methods: We 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. Results: Ambulatory 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. Discussion: The 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 Evidence: This 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.

Diagnostic Accuracy of the Ambulatory EEG vs. Routine EEG for First Single Unprovoked Seizures and Seizure Recurrence: The DX-Seizure Study.

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-year-old) 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.

Update on Minimal Standards for Electroencephalography in Canada: A Review by the Canadian Society of Clinical Neurophysiologists.

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.

Evaluating the single seizure clinic model: Findings from a Canadian Center.

INTRODUCTION: The effect of the single seizure clinic (SSC) model on patient diagnose, work-up, wait-times, and clinical care is poorly characterized and its efficacy unclear. The present study assesses patient characteristics and evaluates the impact of a single seizure clinic (SSC) model on wait-times and access to care. MATERIAL AND METHODS: A prospective study of all patients (n=200) referred to our SSC for first seizure evaluation. Demographic, clinical, and paraclinicial variables were systematically collected and analyzed against a historical cohort. Binary logistic regression analysis was performed to predict impact of dichotomized variables on diagnosis of epilepsy. Diagnostic concordance between SSC nurses and epileptologists was also assessed. RESULTS: Predominant referral sources were emergency department physicians and general practitioners. Mean wait-time for first assessment was significantly reduced by 70.5% employing the SSC model versus historical usual care. A diagnosis was established at first-contact in 80.5% of cases while 16.0% of patients required a second visit. Eighty-two patients (41.0%) were diagnosed with epilepsy. An abnormal EEG was found in 93.9% of patients diagnosed with epilepsy. Sixty-three patients were started on anti-epileptic drugs (63.5% lamotrigine, 7.0% levetiracetam, 5.0% phenytoin, and 5.0% topiramate). In 18% of cases driving restrictions were initiated by the SSC. The most common non-seizure diagnosis was syncope (24.0%). DISCUSSION: The SSC reduced wait-times for assessment and investigations, clarified diagnoses, affected management decisions with respect to further workup, pharmacotherapy, and driving. There was moderate correlation between SSC nurses and physicians (kappa=0.54; p<0.001) as physicians were significantly more likely to diagnose epilepsy. Key factors identified as predictors of epilepsy were: presence of abnormalities on electroencephalography and imaging studies, patients stratified as high or medium-risk for seizure recurrence, semiological characteristics such as amnesia and limb stiffening, and presence of tongue trauma, or incontinence. CONCLUSIONS: The SSC model reduces wait-times, streamlines assessments, and impacts clinical care decisions.

StatNet Electroencephalogram: A Fast and Reliable Option to Diagnose Nonconvulsive Status Epilepticus in Emergency Setting.

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.

Ambulatory EEG: a cost-effective alternative to inpatient video-EEG in adult patients.

INTRODUCTION: Ambulatory 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. METHODS: This 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. RESULTS: One 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. CONCLUSION: In 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.