Evaluating the utility of Rapid Response EEG in emergency care

Evaluating the Impact of Point-of-Care Electroencephalography on Length of Stay in the Intensive Care Unit: Subanalysis of the SAFER-EEG Trial

BACKGROUND

Electroencephalography (EEG) is needed to diagnose nonconvulsive seizures. Prolonged nonconvulsive seizures are associated with neuronal injuries and deleterious clinical outcomes. However, it is uncertain whether the rapid identification of these seizures using point-of-care EEG (POC-EEG) can have a positive impact on clinical outcomes.

METHODS

In a retrospective subanalysis of the recently completed multicenter Seizure Assessment and Forecasting with Efficient Rapid-EEG (SAFER-EEG) trial, we compared intensive care unit (ICU) length of stay (LOS), unfavorable functional outcome (modified Rankin Scale score ≥ 4), and time to EEG between adult patients receiving a US Food and Drug Administration-cleared POC-EEG (Ceribell, Inc.) and those receiving conventional EEG (conv-EEG). Patient records from January 2018 to June 2022 at three different academic centers were reviewed, focusing on EEG timing and clinical outcomes. Propensity score matching was applied using key clinical covariates to control for confounders. Medians and interquartile ranges (IQRs) were calculated for descriptive statistics. Nonparametric tests (Mann-Whitney U-test) were used for the continuous variables, and the χ2 test was used for the proportions.

RESULTS

A total of 283 ICU patients (62 conv-EEG, 221 POC-EEG) were included. The two populations were matched using demographic and clinical characteristics. We found that the ICU LOS was significantly shorter in the POC-EEG cohort compared to the conv-EEG cohort (3.9 [IQR 1.9-8.8] vs. 8.0 [IQR 3.0-16.0] days, p = 0.003). Moreover, modified Rankin Scale functional outcomes were also different between the two EEG cohorts (p = 0.047).

CONCLUSIONS

This study reveals a significant association between early POC-EEG detection of nonconvulsive seizures and decreased ICU LOS. The POC-EEG differed from conv-EEG, demonstrating better functional outcomes compared with the latter in a matched analysis. These findings corroborate previous research advocating the benefit of early diagnosis of nonconvulsive seizure. The causal relationship between the type of EEG and metrics of interest, such as ICU LOS and functional/clinical outcomes, needs to be confirmed in future prospective randomized studies.

Precision emergency medicine

BACKGROUND

Precision health is a burgeoning scientific discipline that aims to incorporate individual variability in biological, behavioral, and social factors to develop personalized health solutions. To date, emergency medicine has not deeply engaged in the precision health movement. However, rapid advances in health technology, data science, and medical informatics offer new opportunities for emergency medicine to realize the promises of precision health.

METHODS

In this article, we conceptualize precision emergency medicine as an emerging paradigm and identify key drivers of its implementation into current and future clinical practice. We acknowledge important obstacles to the specialty-wide adoption of precision emergency medicine and offer solutions that conceive a successful path forward.

RESULTS

Precision emergency medicine is defined as the use of information and technology to deliver acute care effectively, efficiently, and authentically to individual patients and their communities. Key drivers and opportunities include leveraging human data, capitalizing on technology and digital tools, providing deliberate access to care, advancing population health, and reimagining provider education and roles. Overcoming challenges in equity, privacy, and cost is essential for success. We close with a call to action to proactively incorporate precision health into the clinical practice of emergency medicine, the training of future emergency physicians, and the research agenda of the specialty.

CONCLUSIONS

Precision emergency medicine leverages new technology and data-driven artificial intelligence to advance diagnostic testing, individualize patient care plans and therapeutics, and strategically refine the convergence of the health system and the community.

Economic review of point-of-care EEG

Aims: Point-of-care electroencephalogram (POC-EEG) is an acute care bedside screening tool for the identification of nonconvulsive seizures (NCS) and nonconvulsive status epilepticus (NCSE). The objective of this narrative review is to describe the economic themes related to POC-EEG in the United States (US).Materials and methods: We examined peer-reviewed, published manuscripts on the economic findings of POC-EEG for bedside use in US hospitals, which included those found through targeted searches on PubMed and Google Scholar. Conference abstracts, gray literature offerings, frank advertisements, white papers, and studies conducted outside the US were excluded.Results: Twelve manuscripts were identified and reviewed; results were then grouped into four categories of economic evidence. First, POC-EEG usage was associated with clinical management amendments and antiseizure medication reductions. Second, POC-EEG was correlated with fewer unnecessary transfers to other facilities for monitoring and reduced hospital length of stay (LOS). Third, when identifying NCS or NCSE onsite, POC-EEG was associated with greater reimbursement in Medical Severity-Diagnosis Related Group coding. Fourth, POC-EEG may lower labor costs via decreasing after-hours requests to EEG technologists for conventional EEG (convEEG).Limitations: We conducted a narrative review, not a systematic review. The studies were observational and utilized one rapid circumferential headband system, which limited generalizability of the findings and indicated publication bias. Some sample sizes were small and hospital characteristics may not represent all US hospitals. POC-EEG studies in pediatric populations were also lacking. Ultimately, further research is justified.Conclusions: POC-EEG is a rapid screening tool for NCS and NCSE in critical care and emergency medicine with potential financial benefits through refining clinical management, reducing unnecessary patient transfers and hospital LOS, improving reimbursement, and mitigating burdens on healthcare staff and hospitals. Since POC-EEG has limitations (i.e. no video component and reduced montage), the studies asserted that it did not replace convEEG.

Electroencephalography Quality and Application Times in a Pediatric Emergency Department Setting: A Feasibility Study

BACKGROUND

Status epilepticus is the most common neurological emergency presenting to pediatric emergency departments. Nonconvulsive status epilepticus can be extremely challenging to diagnose, however, requiring electroencephalographic (EEG) confirmation for definitive diagnosis. We aimed to determine the feasibility of achieving a good-quality pediatric EEG recording within 20 minutes of presentation to the emergency department.

METHODS

Single-center prospective feasibility study in Cork University Hospital, Ireland, between July 2021 and June 2022. Two-channel continuous EEG was recorded from children (1) aged <16 years and (2) with Glasgow Coma Scale <11 or a reduction in baseline Glasgow Coma Scale in the case of a child with a neurodisability.

RESULTS

Twenty patients were included. The median age at presentation was 65.8 months (interquartile range, 23.2 to 119.0); 50% had a background diagnosis of epilepsy. The most common reason for EEG monitoring was status epilepticus (85%) followed by suspected nonconvulsive status (10%) and reduced consciousness of unknown etiology (5%). The mean length of recording was 93.1 minutes (S.D. 47.4). The mean time to application was 41.3 minutes (S.D. 11.7). The mean percent of artifact in all recordings was 19.3% (S.D. 15.9). Thirteen (65%) EEGs had <25% artifact. Artifact was higher in cases in which active airway management was ongoing.

CONCLUSIONS

EEG monitoring can be achieved in a pediatric emergency department setting within one hour of presentation. Overall, artifact percentage was low outside of periods of airway manipulation. Future studies are required to determine its use in early seizure detection and its support role in clinical decision-making in these patients.

Automated Seizure Detection in Patients with Cardiac Arrest: A Retrospective Review of Ceribell™ Rapid-EEG Recordings

BACKGROUND

In patients with cardiac arrest who remain comatose after return of spontaneous circulation, seizures and other abnormalities on electroencephalogram (EEG) are common. Thus, guidelines recommend urgent initiation of EEG for the evaluation of seizures in this population. Point-of-care EEG systems, such as Ceribell™ Rapid Response EEG (Rapid-EEG), allow for prompt initiation of EEG monitoring, albeit through a reduced-channel montage. Rapid-EEG incorporates an automated seizure detection software (Clarity™) to measure seizure burden in real time and alert clinicians at the bedside when a high seizure burden, consistent with possible status epilepticus, is identified. External validation of Clarity is still needed. Our goal was to evaluate the real-world performance of Clarity for the detection of seizures and status epilepticus in a sample of patients with cardiac arrest.

METHODS

This study was a retrospective review of Rapid-EEG recordings from all the patients who were admitted to the medical intensive care unit at Kent Hospital (Warwick, RI) between 6/1/2021 and 3/18/2022 for management after cardiac arrest and who underwent Rapid-EEG monitoring as part of their routine clinical care (n = 21). Board-certified epileptologists identified events that met criteria for seizures or status epilepticus, as per the 2021 American Clinical Neurophysiology Society's Standardized Critical Care EEG Terminology, and evaluated any seizure burden detections generated by Clarity.

RESULTS

In this study, 4 of 21 patients with cardiac arrest (19.0%) who underwent Rapid-EEG monitoring had multiple electrographic seizures, and 2 of those patients (9.5%) had electrographic status epilepticus within the first 24 h of the study. None of these ictal abnormalities were detected by the Clarity seizure detection system. Clarity showed 0% seizure burden throughout the entirety of all four Rapid-EEG recordings, including the EEG pages that showed definite seizures or status epilepticus.

CONCLUSIONS

The presence of frequent electrographic seizures and/or status epilepticus can go undetected by Clarity. Timely and careful review of all raw Rapid-EEG recordings by a qualified human EEG reader is necessary to guide clinical care, regardless of Clarity seizure burden measurements.

Point-of-care electroencephalography enables rapid evaluation and management of non-convulsive seizures and status epilepticus in the emergency department

Objectives

To describe our institutional experience with point-of-care electroencephalography (pocEEG) and its impact on the evaluation/management of suspected non-convulsive seizures in the emergency department (ED).

Methods

We retrospectively identified 157 adults who underwent pocEEG monitoring in our community hospital ED in 1 year. We calculated the time to obtain pocEEG in the ED (door-to-EEG time) and examined the impact of pocEEG findings (categorized as seizure, highly epileptiform patterns, slowing, or normal activity) on antiseizure medication treatment.

Results

PocEEG revealed seizures (14%, n = 22), highly epileptiform patterns (22%, n = 34), slowing (44%, n = 69), and normal activity (20%, n = 32). The median door-to-EEG time (from initial ED evaluation to pocEEG monitoring) was only 1.2 hours (interquartile range 0.1-2.1) even though 55% of studies were performed after-hours (5 pm-9 am). Most patients were admitted (54% to the intensive care unit, 41% to floor). Antiseizure medication treatment occurred pre-pocEEG in 93 patients (59%) and post-pocEEG in 88 patients (56%). By reviewing the relationship between pocEEG monitoring and antiseizure medication management, we found a significant association between pocEEG findings and changes in management (P < 0.001). Treatment escalation occurred more frequently in patients with epileptiform activity (seizures or highly epileptiform patterns, 52%) than patients with non-epileptiform activity (normal or slow, 25%, P < 0.001), and avoidance of treatment escalation occurred more frequently in patients with normal or slow activity (27%) than patients with seizures or highly epileptiform patterns (2%, P < 0.001).

Conclusion

Our study, the largest to date describing the real-world use of pocEEG in emergency medicine, found that rapid EEG acquisition in the ED was feasible in a community hospital and significantly affected the management of suspected non-convulsive seizures.

Critical care EEG monitoring: improving access and unravelling potentially epileptic patterns

PURPOSE OF REVIEW

The major advances in critical care EEG have been the development of rapid response EEG, major revision of the American Clinical Neurophysiology Society's (ACNS) standardized critical care EEG terminology, and the commencement of treatment trials on rhythmic and periodic patterns (RPPs) that do not qualify as seizures.

RECENT FINDINGS

Rapid response EEG (rEEG) has proven an important supplement to full montage continuous EEG monitoring (cEEG). This EEG can be applied in a few minutes and provides excellent ability to exclude seizures, selecting those where conversion to cEEG would have the greatest diagnostic yield. Once cEEG has been commenced, the durations required to adequately exclude seizures have been refined. The ACNS provided major revision and expansion to the standardized critical care EEG terminology, which paved the way for determining with great accuracy the RPPs that are associated with seizures and that are capable of causing neurologic symptoms and/or secondary neuronal injury. The current limitations to multicenter treatment trials of these patterns have been highlighted.

SUMMARY

Novel methods of EEG in critical care have been expanding access to all patients where clinically indicated. Standardized EEG terminology has provided the framework to determine what patterns in which presenting causes warrant treatment vs. those that do not.

Prehospital Electroencephalography to Detect Traumatic Brain Injury during Helicopter Transport: A Pilot Observational Cohort Study

OBJECTIVE

Early recognition of traumatic brain injury (TBI) is important to facilitate time-sensitive care. Electroencephalography (EEG) can identify TBI, but feasibility of EEG has not been evaluated in prehospital settings. We tested the feasibility of obtaining single-channel EEG during air medical transport after trauma. We measured association between quantitative EEG features, early blood biomarkers, and abnormalities on head computerized tomography (CT).

METHODS

We performed a pilot prospective, observational study enrolling consecutive patients transported by critical care air ambulance from the scene of trauma to a Level I trauma center. During transport, prehospital clinicians placed a sensor on the patient's forehead to record EEG. We reviewed EEG waveforms and selected 90 seconds of recording for quantitative analysis. EEG data processing included fast Fourier transform to summarize component frequency power in the delta (0-4 Hz), theta (4-8 Hz), and alpha (8-13 Hz) ranges. We collected blood samples on day 1 and day 3 post-injury and measured plasma levels of two brain injury biomarkers (ubiquitin C-terminal hydrolase L1 [UCH-L1] and glial fibrillary acidic protein [GFAP]). We compared predictors between individuals with and without CT-positive TBI findings.

RESULTS

Forty subjects were enrolled, with EEG recordings successfully obtained in 34 (85%). Reasons for failure included uncharged battery (n = 5) and user error (n = 1). Data were lost in three cases. Of 31 subjects with data, interpretable EEG signal was recorded in 26 (84%). Mean age was 48 (SD 16) years, 79% were male, and 50% suffered motor vehicle crashes. Eight subjects (24%) had CT-positive TBI. Subjects with and without CT-positive TBI had similar median delta power, alpha power, and theta power. UCH-L1 and GFAP plasma levels did not differ across groups. Delta power inversely correlated with UCH-L1 day 1 plasma concentration (r = -0.60, p = 0.03).

CONCLUSIONS

Prehospital EEG acquisition is feasible during air transport after trauma.

Adult Critical Care Electroencephalography Monitoring for Seizures: A Narrative Review

Electroencephalography (EEG) is an important and relatively inexpensive tool that allows intensivists to monitor cerebral activity of critically ill patients in real time. Seizure detection in patients with and without acute brain injury is the primary reason to obtain an EEG in the Intensive Care Unit (ICU). In response to the increased demand of EEG, advances in quantitative EEG (qEEG) created an approach to review large amounts of data instantly. Finally, rapid response EEG is now available to reduce the time to detect electrographic seizures in limited-resource settings. This review article provides a concise overview of the technical aspects of EEG monitoring for seizures, clinical indications for EEG, the various available modalities of EEG, common and challenging EEG patterns, and barriers to EEG monitoring in the ICU.

Improved access to rapid electroencephalography at a community hospital reduces inter-hospital transfers for suspected non-convulsive seizures

OBJECTIVE

Patients with suspected non-convulsive seizures are optimally evaluated with EEG. However, limited EEG infrastructure at community hospitals often necessitates transfer for long-term EEG monitoring (LTM). Novel point-of-care EEG systems could expedite management of nonconvulsive seizures and reduce unnecessary transfers. We aimed to describe the impact of rapid access to EEG using a novel EEG device with remote expert interpretation (tele-EEG) on rates of transfer for LTM.

METHODS

We retrospectively identified a cohort of patients who underwent Rapid-EEG (Ceribell Inc., Mountain View, CA) monitoring as part of a new standard-of-care at a community hospital. Rapid-EEGs were initially reviewed on-site by a community hospital neurologist before transitioning to tele-EEG review by epileptologists at an affiliated academic hospital. We compared the rate of transfer for LTM after Rapid-EEG/tele-EEG implementation to the expected rate if rapid access to EEG was unavailable.

RESULTS

Seventy-four patients underwent a total of 118 Rapid-EEG studies (10 with seizure, 18 with highly epileptiform patterns, 90 with slow/normal activity). Eighty-one studies (69%), including 9 of 10 studies that detected seizures, occurred after-hours when EEG was previously unavailable. Based on historical practice patterns, we estimated that Rapid-EEG potentially obviated transfer for LTM in 31 of 33 patients (94%); both completed transfers occurred before the transition to tele-EEG review.

SIGNIFICANCE

Rapid access to EEG led to the detection of seizures that would otherwise have been missed and reduced inter-hospital transfers for LTM. We estimate that the reduction in inter-hospital transportation costs alone would be in excess of $39,000 ($1,274 per patient). Point-of-care EEG systems may support a hub-and-spoke model for managing non-convulsive seizures (similar to that utilized in this study and analogous to existing acute stroke infrastructures), with increased EEG capacity at community hospitals and tele-EEG interpretation by specialists at academic hospitals that can accept transfers for LTM.

Noninvasive mobile EEG as a tool for seizure monitoring and management: A systematic review

In the last two decades new noninvasive mobile electroencephalography (EEG) solutions have been developed to overcome limitations of conventional clinical EEG and to improve monitoring of patients with long-term conditions. Despite the availability of mobile innovations, their adoption is still very limited. The aim of this study is to review the current state-of-the-art and highlight the main advantages of adopting noninvasive mobile EEG solutions in clinical trials and research studies of people with epilepsy or suspected seizures. Device characteristics are described, and their evaluation is presented. Two authors independently performed a literature review in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A combination of different digital libraries was used (Embase, MEDLINE, Global Health, PsycINFO and https://clinicaltrials.gov/). Twenty-three full-text, six conference abstracts, and eight webpages were included, where a total of 14 noninvasive mobile solutions were identified. Published studies demonstrated at different levels how EEG recorded via mobile EEG can be used for visual detection of EEG abnormalities and for the application of automatic-detection algorithms with acceptable specificity and sensitivity. When the quality of the signal was compared with scalp EEG, many similarities were found in the background activities and power spectrum. Several studies indicated that the experience of patients and health care providers using mobile EEG was positive in different settings. Ongoing trials are focused mostly on improving seizure-detection accuracy and also on testing and assessing feasibility and acceptability of noninvasive devices in the hospital and at home. This review supports the potential clinical value of noninvasive mobile EEG systems and their advantages in terms of time, technical support, cost, usability, and reliability when applied to seizure detection and management. On the other hand, the limitations of the studies confirmed that future research is needed to provide more evidence regarding feasibility and acceptability in different settings, as well as the data quality and detection accuracy of new noninvasive mobile EEG solutions.

Rapid Response EEG: Current State and Future Directions

PURPOSE OF REVIEW

To critically appraise the literature on the application, methods, and advances in emergency electroencephalography (EEG).

RECENT FINDINGS

The development of rapid EEG (rEEG) technologies and other reduced montage approaches, along with advances in machine learning over the past decade, has increased the rate and access to EEG acquisition. These achievements have made EEG in the emergency setting a practical diagnostic technique for detecting seizures, suspected nonconvulsive status epilepticus (NCSE), altered mental status, stroke, and in the setting of sedation. Growing evidence supports using EEG to expedite medical decision-making in the setting of suspected acute neurological injury. This review covers approaches to acquiring EEG in the emergency setting in the adult and pediatric populations. We also cover the clinical impact of this data, the time associated with emergency EEG, and the costs of acquiring EEG in these settings. Finally, we discuss the advances in artificial intelligence for rapid electrophysiological interpretation.

Wearable electroencephalography for ultra-long-term seizure monitoring: a systematic review and future prospects

INTRODUCTION

: Wearable electroencephalography (EEG) for objective seizure counting might transform the clinical management of epilepsy. Non-EEG modalities have been validated for the detection of convulsive seizures, but there is still an unmet need for the detection of non-convulsive seizures.

AREAS COVERED

: The main objective of this systematic review was to explore the current status on wearable surface- and subcutaneous EEG for long-term seizure monitoring in epilepsy. We included 17 studies and evaluated the progress on the field, including device specifications, intended populations, and main results on the published studies including diagnostic accuracy measures. Furthermore, we examine the hurdles for widespread clinical implementation. This systematic review and expert opinion both consults the PRISMA guidelines and reflects on the future perspectives of this emerging field.

EXPERT OPINION

: Wearable EEG for long-term seizure monitoring is an emerging field, with plenty of proposed devices and proof-of-concept clinical validation studies. The possible implications of these devices are immense including objective seizure counting and possibly forecasting. However, the true clinical value of the devices, including effects on patient important outcomes and clinical decision making is yet to be unveiled and large-scale clinical validation trials are called for.