Predictive value of acute EEG measurements for seizures and epilepsy after stroke using a dry cap electrode EEG system — Study design and proof of concept

Doerrfuss, Jakob I.; Kilic, Tayfun; Weber, Joachim E.; Holtkamp, Martin

doi:10.1016/j.yebeh.2019.106486

Cited by 10 publications

(6 citation statements)

References 32 publications

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“…The development and distribution of dry cap EEG systems, which allow for an easier and faster application, could help facilitate EEG measurements in a larger number of stroke patients. 60,61 The rising implementation of tele-EEG networks could allow for centralized expert analysis of EEG data from stroke patients in peripheral clinics. However, the application of these methods in post-stroke patients has yet to be studied.…”

Section: Discussionmentioning

confidence: 99%

Quantitative and Qualitative EEG as a Prediction Tool for Outcome and Complications in Acute Stroke Patients

et al. 2019

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Currently, the relevance of EEG measurements in acute stroke patients is considered low in clinical practice. However, recent studies on the predictive value of EEG measurements after stroke for various outcomes may increase the role of EEG in patients with stroke. We aimed to review the current literature on the utility of EEG measurements after stroke as a tool to predict outcome and complications, focusing on studies in which the EEG measurement was performed in the acute phase after the event and in which long-term outcome measures were reported. In our literature review, we identified 4 different outcome measures (functional outcome, mortality, development of post-stroke cognitive decline, and development of post-stroke epilepsy) where studies on the utility of acute EEG measurements exist. There is a large body of evidence for the prediction of functional outcome, in which a multitude of associated quantitative and qualitative EEG parameters are described. In contrast, only few studies focus on mortality as outcome parameter. We found studies of high methodical quality on the prediction of post-stroke cognitive decline, though the number of patients in these studies often was small. The role of EEG as a prediction tool for seizures and epilepsy after stroke could increase after a recently published study, especially if its result can be incorporated into already existing post-stroke epilepsy prediction tools. In summary, EEG is useful for the prediction of functional outcome, mortality, development of post-stroke cognitive decline and epilepsy, even though there is a discrepancy between the large amount of studies on EEG in acute stroke patients and its underuse in clinical practice.

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Section: Discussionmentioning

confidence: 99%

Quantitative and Qualitative EEG as a Prediction Tool for Outcome and Complications in Acute Stroke Patients

et al. 2019

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“…Through active amplification of the voltage of the electrode using a built-in gain amplifier, reliable EEG recording is possible, even with high impedances. The pilot phase of this study has shown the feasibility of this approach [33]. Continuous improvement of comfort as well as the function and the anti-interference ability of EEG recording tools, and shortening of the recording time are needed to make EEG more applicable in clinical usage.…”

Section: Epileptic Seizure Prediction Using Machine Learning Methodsmentioning

confidence: 98%

Research progress on the prediction of post-stroke epilepsy

Zou

Chen

2020

Acta Epileptologica

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Epilepsy is a common neurological disease that not only causes difficulties in the work and life activities of patients, but also brings complex social problems. Cerebrovascular disease is currently the main cause of epilepsy in the elderly. With the increased survival rate of patients after stroke, the incidence of epilepsy after stroke has also increased. Effective prediction of epilepsy after stroke is extremely crucial for the prognosis of patients, the initiation of antiepileptic therapy and the reduction of epileptic seizures. In this review, we summarize and compare the current models for the prediction of epilepsy after stroke, including the SeLECT prediction model, Post-Stroke Epilepsy Risk Scale (PoSERS), CAVE score, electroencephalogram (EEG) prediction model, and Scandinavian Stroke Scale (SSS) score, in order to provide reference for clinical practice and future research. Prediction models can be selected based on the clinical classification of cerebrovascular events. The SeLECT score prognostic model is a better choice for ischemic stroke, especially for the exclusive prediction of mild post stroke epilepsy. The CAVE score model is suitable for intra-cerebral hemorrhage patients. It is simple and offers high correlation between the risk factors and epilepsy. The PoSERS score simultaneously predicts ischemic and hemorrhagic stroke, and is superior to other methods in specificity as well as positive and negative prediction rate. The SSS score, which only measures stroke severity, is not strictly considered as a mature predictor, but it can be used as a first step screening tool. A growing number of large studies are under the way to identify risk factors of poststroke epilepsy (PSE) and to improve the inclusion of predictive indicators. New and advanced findings by EEG recordings may further improve the prediction of PSE.

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“…For nearly 20 years, the digitalization of the EEG has been available. Recently, inpatient tele-EEG has been advanced by templated electrodes, dry electrode setups, 21 several iterations of cap designs, and rapid-response systems for nonexpert placement 22 23 24 25 26 27 as partial solutions to the shortage of on-site neurodiagnostic technologists (NDTs). Unfortunately, there are inherent limitations of these alternatives to the traditional 10 to 20 EEG setup placed by NDTs that can impact their utility, including being of limited montage, containing more artifacts, and inflexibility to varying anatomies or postsurgical conditions.…”

Section: Technologymentioning

confidence: 99%

The Past, Present, and Future of Tele-EEG

Murphey¹,

Anderson²

2022

Semin Neurol

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Tele-electroencephalogram (EEG) has become more pervasive over the last 20 years due to advances in technology, both independent of and driven by personnel shortages. The professionalization of EEG services has both limited growth and controlled the quality of tele-EEG. Growing data on the conditions that benefit from brain monitoring have informed increased critical care EEG and ambulatory EEG utilization. Guidelines that marshal responsible use of still-limited resources and changes in broadband and billing practices have also shaped the tele-EEG landscape. It is helpful to characterize the drivers of tele-EEG to navigate barriers to sustainable growth and to build dynamic systems that anticipate challenges in any of the domains that expand access and enhance quality of these diagnostic services. We explore the historical factors and current trends in tele-EEG in the United States in this review.

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Predictive value of acute EEG measurements for seizures and epilepsy after stroke using a dry cap electrode EEG system — Study design and proof of concept

Cited by 10 publications

References 32 publications

Quantitative and Qualitative EEG as a Prediction Tool for Outcome and Complications in Acute Stroke Patients

Quantitative and Qualitative EEG as a Prediction Tool for Outcome and Complications in Acute Stroke Patients

Research progress on the prediction of post-stroke epilepsy

The Past, Present, and Future of Tele-EEG

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