Early detection of vasospasm after acute subarachnoid hemorrhage using continuous EEG ICU monitoring

Prolonged Monitoring of Brain Electrical Activity in the Intensive Care Unit

Electroencephalography (EEG) has been used to assess brain electrical activity for over a century. More recently, technological advancements allowed EEG to be a widely available and powerful tool in the intensive care unit (ICU), where patients at risk for cerebral dysfunction and brain injury can be monitored in a continuous, real-time manner. In the last 2 decades, several organizations established guidelines for continuous EEG monitoring in the ICU, defining critical care EEG terminology and technical standards for technicians, machines, and electroencephalographers. This article provides an overview of the current role of continuous EEG monitoring in the ICU.

Association of hyperosmolar therapy with cerebral oxygen extraction after cardiac arrest

BACKGROUND

Elevated jugular bulb venous oxygen saturation (SjvO2) after cardiac arrest may be due to diffusion-limited oxygen extraction secondary to perivascular edema. Treatment with hyperosmolar solution (HTS) may decrease this edema and thus the barrier to oxygen diffusion. Alternatively, SjvO2 may rise when cerebral metabolic rate declines due to irreversible cellular injury, which would not be affected by HTS. Electroencephalography (EEG) may differentiate between these etiologies of elevated SjvO2. We hypothesized SjvO2 would be lower after treatment with HTS and EEG could identify treatment responders.

METHODS

We conducted a retrospective observational cohort study including comatose survivors of cardiac arrest who had at least one elevated SjvO2 (>75%) and were EEG-monitored. We quantified the change in consecutive SjvO2 values within a sample pair using a multivariable mixed-effects regression, treating HTS as a fixed effect, adjusting for mean arterial pressure, partial pressure of arterial oxygen, and partial pressure of carbon dioxide. We classified pretreatment EEG patterns as benign or indicative of potential metabolic failure and tested for an interaction of EEG pattern with HTS.

RESULTS

Our primary adjusted analysis showed an independent association of HTS treatment with change in SjvO2 (β -2.2; 95% confidence interval [CI], -4.0 to -0.3%). In our interaction model, the effect of treatment differed by EEG pattern (β for interaction term -10.9%, 95% CI -17.9 to -3.9%). HTS was associated with a significant change in SjvO2 among those with benign pre-treatment EEG patterns (-12.4%, 95% CI -18.4 to -6.4%) but was not associated with a change in SjvO2 in those with ominous pre-treatment EEG patterns (-1.6%, 95% CI -3.6 to 0.4%).

CONCLUSIONS

HTS was independently associated with decreased SjvO2 in patients resuscitated from cardiac arrest, and this effect was limited to patients with benign pretreatment EEG patterns. Our results suggest diffusion-limited oxygen extraction secondary to modifiable perivascular edema as the etiology of elevated SjvO2, and EEG pattern may be useful to identify treatment responders.

Utility of Quantitative EEG in Neurological Emergencies and ICU Clinical Practice

The electroencephalogram (EEG) is a cornerstone tool for the diagnosis, management, and prognosis of selected patient populations. EEGs offer significant advantages such as high temporal resolution, real-time cortical function assessment, and bedside usability. The quantitative EEG (qEEG) added the possibility of long recordings being processed in a compressive manner, making EEG revision more efficient for experienced users, and more friendly for new ones. Recent advancements in commercially available software, such as Persyst, have significantly expanded and facilitated the use of qEEGs, marking the beginning of a new era in its application. As a result, there has been a notable increase in the practical, real-world utilization of qEEGs in recent years. This paper aims to provide an overview of the current applications of qEEGs in daily neurological emergencies and ICU practice, and some elementary principles of qEEGs using Persyst software in clinical settings. This article illustrates basic qEEG patterns encountered in critical care and adopts the new terminology proposed for spectrogram reporting.

Utility and rationale for continuous EEG monitoring: a primer for the general intensivist

This review offers a comprehensive guide for general intensivists on the utility of continuous EEG (cEEG) monitoring for critically ill patients. Beyond the primary role of EEG in detecting seizures, this review explores its utility in neuroprognostication, monitoring neurological deterioration, assessing treatment responses, and aiding rehabilitation in patients with encephalopathy, coma, or other consciousness disorders. Most seizures and status epilepticus (SE) events in the intensive care unit (ICU) setting are nonconvulsive or subtle, making cEEG essential for identifying these otherwise silent events. Imaging and invasive approaches can add to the diagnosis of seizures for specific populations, given that scalp electrodes may fail to identify seizures that may be detected by depth electrodes or electroradiologic findings. When cEEG identifies SE, the risk of secondary neuronal injury related to the time-intensity "burden" often prompts treatment with anti-seizure medications. Similarly, treatment may be administered for seizure-spectrum activity, such as periodic discharges or lateralized rhythmic delta slowing on the ictal-interictal continuum (IIC), even when frank seizures are not evident on the scalp. In this setting, cEEG is utilized empirically to monitor treatment response. Separately, cEEG has other versatile uses for neurotelemetry, including identifying the level of sedation or consciousness. Specific conditions such as sepsis, traumatic brain injury, subarachnoid hemorrhage, and cardiac arrest may each be associated with a unique application of cEEG; for example, predicting impending events of delayed cerebral ischemia, a feared complication in the first two weeks after subarachnoid hemorrhage. After brief training, non-neurophysiologists can learn to interpret quantitative EEG trends that summarize elements of EEG activity, enhancing clinical responsiveness in collaboration with clinical neurophysiologists. Intensivists and other healthcare professionals also play crucial roles in facilitating timely cEEG setup, preventing electrode-related skin injuries, and maintaining patient mobility during monitoring.

Future of neurocritical care: Integrating neurophysics, multimodal monitoring, and machine learning

Multimodal monitoring (MMM) in the intensive care unit (ICU) has become increasingly sophisticated with the integration of neurophysical principles. However, the challenge remains to select and interpret the most appropriate combination of neuromonitoring modalities to optimize patient outcomes. This manuscript reviewed current neuromonitoring tools, focusing on intracranial pressure, cerebral electrical activity, metabolism, and invasive and noninvasive autoregulation monitoring. In addition, the integration of advanced machine learning and data science tools within the ICU were discussed. Invasive monitoring includes analysis of intracranial pressure waveforms, jugular venous oximetry, monitoring of brain tissue oxygenation, thermal diffusion flowmetry, electrocorticography, depth electroencephalography, and cerebral microdialysis. Noninvasive measures include transcranial Doppler, tympanic membrane displacement, near-infrared spectroscopy, optic nerve sheath diameter, positron emission tomography, and systemic hemodynamic monitoring including heart rate variability analysis. The neurophysical basis and clinical relevance of each method within the ICU setting were examined. Machine learning algorithms have shown promise by helping to analyze and interpret data in real time from continuous MMM tools, helping clinicians make more accurate and timely decisions. These algorithms can integrate diverse data streams to generate predictive models for patient outcomes and optimize treatment strategies. MMM, grounded in neurophysics, offers a more nuanced understanding of cerebral physiology and disease in the ICU. Although each modality has its strengths and limitations, its integrated use, especially in combination with machine learning algorithms, can offer invaluable information for individualized patient care.

Multimodal neuromonitoring in the pediatric intensive care unit

Neuromonitoring is used to assess the central nervous system in the intensive care unit. The purpose of neuromonitoring is to detect neurologic deterioration and intervene to prevent irreversible nervous system dysfunction. Neuromonitoring starts with the standard neurologic examination, which may lag behind the pathophysiologic changes. Additional modalities including continuous electroencephalography (CEEG), multiple physiologic parameters, and structural neuroimaging may detect changes earlier. Multimodal neuromonitoring now refers to an integrated combination and display of non-invasive and invasive modalities, permitting tailored treatment for the individual patient. This chapter reviews the non-invasive and invasive modalities used in pediatric neurocritical care.

Electrophysiological monitoring of neurological functions at the acute phase of brain injury: An overview of current knowledge and future perspectives in the adult population

The continuous monitoring of physiological parameters is now considered as a standard of care in intensive care units (ICU). While multiple techniques are available to guide hemodynamic or respiratory management, the monitoring of neurological function in unconscious patients is usually limited to discontinuous bedside neurological examination or morphological brain imaging. However, cortical activity is accessible at the bedside with electroencephalography (EEG), electrocorticography (ECoG) or evoked potentials. The analysis of the unprocessed signal requires a trained neurophysiologist and could be time consuming. During the past decades, advances in neurophysiological signal acquisition make it possible to calculate quantified EEG parameters in real-time. New monitors also provide ICU friendly display for a dynamic and live assessment of neurological function changes. In this review, we will describe the technical aspects of EEG, ECoG and evoked potentials required for a good signal quality before interpretation. We will discuss how to use those electrophysiological techniques in the ICU to assess neurological function in comatose patients at the acute phase of brain injuries such as traumatic brain injuries, haemorrhagic or ischemic stroke. We will discuss, which quantitative EEG or evoked potentials monitoring parameters can be used at the bedside to guide sedation, evaluate neurological function during awaking and look for new neurological (encephalic or brainstem) injuries. We will present the state of the art and discuss some analyses, which may develop shortly.

Effects of New-Generation Antiepileptic Drug Prophylaxis on Delayed Neurovascular Events After Aneurysmal Subarachnoid Hemorrhage

Neuroelectric disruptions such as seizures and cortical spreading depolarization may contribute to the development of delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (SAH). However, effects of antiepileptic drug prophylaxis on outcomes remain controversial in SAH. The authors investigated if prophylactic administration of new-generation antiepileptic drugs levetiracetam and perampanel was beneficial against delayed neurovascular events after SAH. This was a retrospective single-center cohort study of 121 consecutive SAH patients including 56 patients of admission World Federation of Neurological Surgeons grades IV - V who underwent aneurysmal obliteration within 72 h post-SAH from 2013 to 2021. Prophylactic antiepileptic drugs differed depending on the study terms: none (2013 - 2015), levetiracetam for patients at high risks of seizures (2016 - 2019), and perampanel for all patients (2020 - 2021). The 3rd term had the lowest occurrence of delayed cerebral microinfarction on diffusion-weighted magnetic resonance imaging, which was related to less development of DCI. Other outcome measures were similar among the 3 terms including incidences of angiographic vasospasm, computed tomography-detectable delayed cerebral infarction, seizures, and 3-month good outcomes (modified Rankin Scale 0 - 2). The present study suggests that prophylactic administration of levetiracetam and perampanel was not associated with worse outcomes and that perampanel may have the potential to reduce DCI by preventing microcirculatory disturbances after SAH. Further studies are warranted to investigate anti-DCI effects of a selective α-amino-3-hydroxy-5-methyl-4-isoxazole propionate receptor antagonist perampanel in SAH patients in a large-scale prospective study.

"Drum Tower Hospital" strategy for acute type A aortic dissection with coma

OVERVIEW

Acute type A aortic dissection (ATAAD) with persistent coma is a life-threatening condition associated with high mortality and poor neurological outcomes. The optimal timing for surgical intervention in these patients remains uncertain, and many patients are not eligible for surgery due to their poor prognosis.

DESCRIPTION

In this case, a 53-year-old man with hypertension presented to the emergency department in a coma that had lasted for 9 hours. The patient was diagnosed with ATAAD and underwent the "Drum Tower Hospital" strategy, which involved preoperative assessments, including computed tomography angiography (CTA) and quantitative electroencephalogram (qEEG) monitoring. Surgical interventions, such as emergency stenting and aortic replacement, were performed to restore blood flow and repair the aorta. Postoperative monitoring, including qEEG, showed improvements in brain function. Despite the patient experiencing hemiplegia and a neurological deficit, the "Drum Tower Hospital" strategy, guided by comprehensive brain assessments, showed promise in managing ATAAD with coma. However, further research is needed to establish effective treatment strategies for these patients. Overall, ATAAD with persistent coma is a critical condition with limited treatment options. The "Drum Tower Hospital" strategy, supported by multimodal brain assessment, offers a potential approach to improve outcomes in these patients.

Electroencephalography as a Biomarker of Prognosis in Acute Brain Injury

Electroencephalography (EEG) is a noninvasive tool that allows the monitoring of cerebral brain function in critically ill patients, aiding with diagnosis, management, and prognostication. Specific EEG features have shown utility in the prediction of outcomes in critically ill patients with status epilepticus, acute brain injury (ischemic stroke, intracranial hemorrhage, subarachnoid hemorrhage, and traumatic brain injury), anoxic brain injury, and toxic-metabolic encephalopathy. Studies have also found an association between particular EEG patterns and long-term functional and cognitive outcomes as well as prediction of recovery of consciousness following acute brain injury. This review summarizes these findings and demonstrates the value of utilizing EEG findings in the determination of prognosis.

Pathophysiology, Management, and Therapeutics in Subarachnoid Hemorrhage and Delayed Cerebral Ischemia: An Overview

Subarachnoid hemorrhage (SAH) is a type of hemorrhagic stroke resulting from the rupture of an arterial vessel within the brain. Unlike other stroke types, SAH affects both young adults (mid-40s) and the geriatric population. Patients with SAH often experience significant neurological deficits, leading to a substantial societal burden in terms of lost potential years of life. This review provides a comprehensive overview of SAH, examining its development across different stages (early, intermediate, and late) and highlighting the pathophysiological and pathohistological processes specific to each phase. The clinical management of SAH is also explored, focusing on tailored treatments and interventions to address the unique pathological changes that occur during each stage. Additionally, the paper reviews current treatment modalities and pharmacological interventions based on the evolving guidelines provided by the American Heart Association (AHA). Recent advances in our understanding of SAH will facilitate clinicians' improved management of SAH to reduce the incidence of delayed cerebral ischemia in patients.

2023 Guideline for the Management of Patients With Aneurysmal Subarachnoid Hemorrhage: A Guideline From the American Heart Association/American Stroke Association

AIM

The "2023 Guideline for the Management of Patients With Aneurysmal Subarachnoid Hemorrhage" replaces the 2012 "Guidelines for the Management of Aneurysmal Subarachnoid Hemorrhage." The 2023 guideline is intended to provide patient-centric recommendations for clinicians to prevent, diagnose, and manage patients with aneurysmal subarachnoid hemorrhage.

METHODS

A comprehensive search for literature published since the 2012 guideline, derived from research principally involving human subjects, published in English, and indexed in MEDLINE, PubMed, Cochrane Library, and other selected databases relevant to this guideline, was conducted between March 2022 and June 2022. In addition, the guideline writing group reviewed documents on related subject matter previously published by the American Heart Association. Newer studies published between July 2022 and November 2022 that affected recommendation content, Class of Recommendation, or Level of Evidence were included if appropriate. Structure: Aneurysmal subarachnoid hemorrhage is a significant global public health threat and a severely morbid and often deadly condition. The 2023 aneurysmal subarachnoid hemorrhage guideline provides recommendations based on current evidence for the treatment of these patients. The recommendations present an evidence-based approach to preventing, diagnosing, and managing patients with aneurysmal subarachnoid hemorrhage, with the intent to improve quality of care and align with patients' and their families' and caregivers' interests. Many recommendations from the previous aneurysmal subarachnoid hemorrhage guidelines have been updated with new evidence, and new recommendations have been created when supported by published data.

Precision Medicine in Neurocritical Care for Cerebrovascular Disease Cases

Scientific advances have informed many aspects of acute stroke care but have also highlighted the complexity and heterogeneity of cerebrovascular diseases. While practice guidelines are essential in supporting the clinical decision-making process, they may not capture the nuances of individual cases. Personalized stroke care in ICU has traditionally relied on integrating clinical examinations, neuroimaging studies, and physiologic monitoring to develop a treatment plan tailored to the individual patient. However, to realize the potential of precision medicine in stroke, we need advances and evidence in several critical areas, including data capture, clinical phenotyping, serum biomarker development, neuromonitoring, and physiology-based treatment targets. Mathematical tools are being developed to analyze the multitude of data and provide clinicians with real-time information and personalized treatment targets for the critical care management of patients with cerebrovascular diseases. This review summarizes research advances in these areas and outlines principles for translating precision medicine into clinical practice.

Neuromonitoring in Children with Cerebrovascular Disorders

BACKGROUND

Cerebrovascular disorders are an important cause of morbidity and mortality in children. The acute care of a child with an ischemic or hemorrhagic stroke or cerebral sinus venous thrombosis focuses on stabilizing the patient, determining the cause of the insult, and preventing secondary injury. Here, we review the use of both invasive and noninvasive neuromonitoring modalities in the care of pediatric patients with arterial ischemic stroke, nontraumatic intracranial hemorrhage, and cerebral sinus venous thrombosis.

METHODS

Narrative review of the literature on neuromonitoring in children with cerebrovascular disorders.

RESULTS

Neuroimaging, near-infrared spectroscopy, transcranial Doppler ultrasonography, continuous and quantitative electroencephalography, invasive intracranial pressure monitoring, and multimodal neuromonitoring may augment the acute care of children with cerebrovascular disorders. Neuromonitoring can play an essential role in the early identification of evolving injury in the aftermath of arterial ischemic stroke, intracranial hemorrhage, or sinus venous thrombosis, including recurrent infarction or infarct expansion, new or recurrent hemorrhage, vasospasm and delayed cerebral ischemia, status epilepticus, and intracranial hypertension, among others, and this, is turn, can facilitate real-time adjustments to treatment plans.

CONCLUSIONS

Our understanding of pediatric cerebrovascular disorders has increased dramatically over the past several years, in part due to advances in the neuromonitoring modalities that allow us to better understand these conditions. We are now poised, as a field, to take advantage of advances in neuromonitoring capabilities to determine how best to manage and treat acute cerebrovascular disorders in children.

A predictive model for consciousness recovery of comatose patients after acute brain injury

Background

Predicting the consciousness recovery for comatose patients with acute brain injury is an important issue. Although some efforts have been made in the study of prognostic assessment methods, it is still unclear which factors can be used to establish model to directly predict the probability of consciousness recovery.

Objectives

We aimed to establish a model using clinical and neuroelectrophysiological indicators to predict consciousness recovery of comatose patients after acute brain injury.

Methods

The clinical data of patients with acute brain injury admitted to the neurosurgical intensive care unit of Xiangya Hospital of Central South University from May 2019 to May 2022, who underwent electroencephalogram (EEG) and auditory mismatch negativity (MMN) examinations within 28 days after coma onset, were collected. The prognosis was assessed by Glasgow Outcome Scale (GOS) at 3 months after coma onset. The least absolute shrinkage and selection operator (LASSO) regression analysis was applied to select the most relevant predictors. We combined Glasgow coma scale (GCS), EEG, and absolute amplitude of MMN at Fz to develop a predictive model using binary logistic regression and then presented by a nomogram. The predictive efficiency of the model was evaluated with AUC and verified by calibration curve. The decision curve analysis (DCA) was used to evaluate the clinical utility of the prediction model.

Results

A total of 116 patients were enrolled for analysis, of which 60 had favorable prognosis (GOS ≥ 3). Five predictors, including GCS (OR = 13.400, P < 0.001), absolute amplitude of MMN at Fz site (FzMMNA, OR = 1.855, P = 0.038), EEG background activity (OR = 4.309, P = 0.023), EEG reactivity (OR = 4.154, P = 0.030), and sleep spindles (OR = 4.316, P = 0.031), were selected in the model by LASSO and binary logistic regression analysis. This model showed favorable predictive power, with an AUC of 0.939 (95% CI: 0.899-0.979), and calibration. The threshold probability of net benefit was between 5% and 92% in the DCA.

Conclusion

This predictive model for consciousness recovery in patients with acute brain injury is based on a nomogram incorporating GCS, EEG background activity, EEG reactivity, sleep spindles, and FzMMNA, which can be conveniently obtained during hospitalization. It provides a basis for care givers to make subsequent medical decisions.

Theta-Alpha Variability on Admission EEG Is Associated With Outcome in Pediatric Cerebral Malaria

PURPOSE

Pediatric cerebral malaria has high rates of mortality and neurologic morbidity. Although several biomarkers, including EEG, are associated with survival or morbidity, many are resource intensive or require skilled interpretation for clinical use. Automation of quantitative interpretation of EEG may be preferable in resource-limited settings, where trained interpreters are rare. As currently used quantitative EEG factors do not adequately describe the spectrum of variability seen in studies from children with cerebral malaria, the authors developed and validated a new quantitative EEG variable, theta-alpha variability (TAV).

METHODS

The authors developed TAV, a new quantitative variable, as a composite of multiple automated EEG outputs. EEG records from 194 children (6 months to 14 years old) with cerebral malaria were analyzed. Independent EEG interpreters performed standard quantitative and qualitative analyses, with the addition of the newly created variable. The associations of TAV with other quantitative EEG factors, a qualitative assessment of variability, and outcomes were assessed.

RESULTS

Theta-alpha variability was not highly correlated with alpha, theta, or delta power and was not associated with qualitative measures of variability. Children whose EEGs had higher values of TAV had a lower risk of death (odds ratio = 0.934, 95% confidence interval = 0.902-0.966) or neurologic sequelae (odds ratio = 0.960, 95% confidence interval = 0.932-0.990) compared with those with lower values. Receiver operating characteristic analysis in predicting death at a TAV threshold of 0.244 yielded a sensitivity of 74% and specificity of 70% for an area under the receiver operating characteristic curve of 0.755.

CONCLUSIONS

Theta-alpha variability is independently associated with outcome in pediatric cerebral malaria and can predict death with high sensitivity and specificity. Automated determination of this newly created EEG factor holds promise as a potential method to increase the clinical utility of EEG in resource-limited settings by allowing interventions to be targeted to those at higher risk of death or disability.

Bispectral index monitoring to detect delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage

PURPOSE

Evaluate the bispectral index (BIS) monitoring to detect delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH).

MATERIALS AND METHODS

A single-center prospective study in patients with aSAH. BIS monitoring was recorded during 25-120 min in two periods, within the initial 72 h (BIS1) and between days 4 and 6 (BIS2) from admission. The median for each exported BIS parameter was analyzed. Transcranial Doppler (TCD) sonography was simultaneously performed with BIS1 (TCD1) and BIS2 (TCD2) monitoring. A multivariate logistic regression model was built to identify the variables associated with DCI.

RESULTS

Sixty-four patients were included and 16 (25%) developed DCI. During BIS2 monitoring, significant differences were found in BIS value (left, p = 0.01; right, p = 0.009), 95% spectral edge frequency (left and right, p = 0.04), and total power (left and right, p = 0.04). In multivariable analysis, vasospasm on TCD2 (OR 42.8 [95% CI 3.1-573]; p = 0.005), a median BIS2 value <85 in one or both sides (OR 6.2 [95% CI 1.28-30]; p = 0.023), and age (OR 1.08 [95% CI 1.00-1.17]; p = 0.04) were associated with the development of DCI.

CONCLUSIONS

BIS value is the most useful BIS parameter for detecting DCI after aSAH. Pending further validation, BIS monitoring might be even more accurate than TCD.

Automated EEG-based prediction of delayed cerebral ischemia after subarachnoid hemorrhage

OBJECTIVE

Delayed cerebral ischemia (DCI) is a leading complication of aneurysmal subarachnoid hemorrhage (SAH) and electroencephalography (EEG) is increasingly used to evaluate DCI risk. Our goal is to develop an automated DCI prediction algorithm integrating multiple EEG features over time.

METHODS

We assess 113 moderate to severe grade SAH patients to develop a machine learning model that predicts DCI risk using multiple EEG features.

RESULTS

Multiple EEG features discriminate between DCI and non-DCI patients when aligned either to SAH time or to DCI onset. DCI and non-DCI patients have significant differences in alpha-delta ratio (0.08 vs 0.05, p < 0.05) and percent alpha variability (0.06 vs 0.04, p < 0.05), Shannon entropy (p < 0.05) and epileptiform discharge burden (205 vs 91 discharges per hour, p < 0.05) based on whole brain and vascular territory averaging. Our model improves predictions by emphasizing the most informative features at a given time with an area under the receiver-operator curve of 0.73, by day 5 after SAH and good calibration between 48-72 hours (calibration error 0.13).

CONCLUSIONS

Our proposed model obtains good performance in DCI prediction.

SIGNIFICANCE

We leverage machine learning to enable rapid, automated, multi-featured EEG assessment and has the potential to increase the utility of EEG for DCI prediction.

Electroencephalogram in the intensive care unit: a focused look at acute brain injury

Over the past decades, electroencephalography (EEG) has become a widely applied and highly sophisticated brain monitoring tool in a variety of intensive care unit (ICU) settings. The most common indication for EEG monitoring currently is the management of refractory status epilepticus. In addition, a number of studies have associated frequent seizures, including nonconvulsive status epilepticus (NCSE), with worsening secondary brain injury and with worse outcomes. With the widespread utilization of EEG (spot and continuous EEG), rhythmic and periodic patterns that do not fulfill strict seizure criteria have been identified, epidemiologically quantified, and linked to pathophysiological events across a wide spectrum of critical and acute illnesses, including acute brain injury. Increasingly, EEG is not just qualitatively described, but also quantitatively analyzed together with other modalities to generate innovative measurements with possible clinical relevance. In this review, we discuss the current knowledge and emerging applications of EEG in the ICU, including seizure detection, ischemia monitoring, detection of cortical spreading depolarizations, assessment of consciousness and prognostication. We also review some technical aspects and challenges of using EEG in the ICU including the logistics of setting up ICU EEG monitoring in resource-limited settings.

Role of Quantitative EEG and EEG Reactivity in Traumatic Brain Injury

OBJECTIVE

This study aimed to explore the effectiveness of quantitative electroencephalogram (EEG) and EEG reactivity (EEG-R) to predict the prognosis of patients with severe traumatic brain injury.

METHODS

This was a prospective observational study on severe traumatic brain injury. Quantitative EEG monitoring was performed for 8 to 12 hours within 14 days of onset. The EEG-R was tested during the monitoring period. We then followed patients for 3 months to determine their level of consciousness. The Glasgow Outcome Scale (GOS) score was used. The score 3, 4, 5 of GOS were defined good prognosis, and score 1 and 2 as poor prognosis. Univariate and multivariate analyses were employed to assess the association of predictors with poor prognosis.

RESULTS

A total of 56 patients were included in the study. Thirty-two patients (57.1%) awoke (good prognosis) in 3 months after the onset. Twenty-four patients (42.9%) did not awake (poor prognosis), including 11 cases deaths. Univariate analysis showed that Glasgow coma scale (GCS) score, the amplitude-integrated EEG (aEEG), the relative band power (RBP), the relative alpha variability (RAV), the spectral entropy (SE), and EEG-R reached significant difference between the poor-prognosis and good-prognosis groups. However, age, gender, and pupillary light reflex did not correlate significantly with poor prognosis. Furthermore, multivariate logistic regression analysis showed that only RAV and EEG-R were significant independent predictors of poor prognosis, and the prognostic model containing these 2 variables yielded a predictive performance with an area under the curve of 0.882.

CONCLUSIONS

Quantitative EEG and EEG-R may be used to assess the prognosis of patients with severe traumatic brain injury early. RAV and EEG-R were the good predictive indicators of poor prognosis.

High epileptiform discharge burden predicts delayed cerebral ischemia after subarachnoid hemorrhage

OBJECTIVE

To investigate whether epileptiform discharge burden can identify those at risk for delayed cerebral ischemia (DCI) after subarachnoid hemorrhage (SAH).

METHODS

Retrospective analysis of 113 moderate to severe grade SAH patients who had continuous EEG (cEEG) recordings during their hospitalization. We calculated the burden of epileptiform discharges (ED), measured as number of ED per hour.

RESULTS

We find that many SAH patients have an increase in ED burden during the first 3-10 days following rupture, the major risk period for DCI. However, those who develop DCI have a significantly higher hourly burden from days 3.5-6 after SAH vs. those who do not. ED burden is higher in DCI patients when assessed in relation to the onset of DCI (area under the receiver operator curve 0.72). Finally, specific trends of ED burden over time, assessed by group-based trajectory analysis, also help stratify DCI risk.

CONCLUSIONS

These results suggest that ED burden is a useful parameter for identifying those at higher risk of developing DCI after SAH. The higher burden rate associated with DCI supports the theory of metabolic supply-demand mismatch which contributes to this complication.

SIGNIFICANCE

ED burden is a novel biomarker for predicting those at high risk of DCI.

The Past, Present, and Future of Tele-EEG

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.

The Utility of Quantitative EEG in Detecting Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage

SUMMARY

In this review, we discuss the utility of quantitative EEG parameters for the detection of delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage in the context of the complex pathophysiology of DCI and the limitations of current diagnostic methods. Because of the multifactorial pathophysiology of DCI, methodologies solely assessing blood vessel narrowing (vasospasm) are insufficient to detect all DCI. Quantitative EEG has facilitated the exploration of EEG as a diagnostic modality of DCI. Multiple quantitative EEG parameters such as alpha power, relative alpha variability, and alpha/delta ratio show reliable detection of DCI in multiple studies. Recent studies on epileptiform abnormalities suggest that their potential for the detection of DCI. Quantitative EEG is a promising, continuous, noninvasive, monitoring modality of DCI implementable in daily practice. Future work should validate these parameters in larger populations, facilitated by the development of automated detection algorithms and multimodal data integration.

Electroencephalography for detection of vasospasm and delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage: a retrospective analysis and systematic review

OBJECTIVE

Good functional outcomes after aneurysmal subarachnoid hemorrhage (aSAH) are often dependent on early detection and treatment of cerebral vasospasm (CVS) and delayed cerebral ischemia (DCI). There is growing evidence that continuous monitoring with cranial electroencephalography (cEEG) can predict CVS and DCI. Therefore, the authors sought to assess the value of continuous cEEG monitoring for the detection of CVS and DCI in aSAH.

METHODS

The cerebrovascular database of a quaternary center was reviewed for patients with aSAH and cEEG monitoring between January 1, 2017, and July 31, 2019. Demographic data, cardiovascular risk factors, Glasgow Coma Scale score at admission, aneurysm characteristics, and outcomes were abstracted from the medical record. Patient data were retrospectively analyzed for DCI and angiographically assessed CVS. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and odds ratio for cEEG, transcranial Doppler ultrasonography (TCDS), CTA, and DSA in detecting DCI and angiographic CVS were calculated. A systematic literature review was conducted in accordance with PRISMA guidelines querying the PubMed, Cochrane Controlled Trials Register, Web of Science, and Embase databases.

RESULTS

A total of 77 patients (mean age 60 years [SD 15 years]; female sex, n = 54) were included in the study. Continuous cEEG monitoring detected DCI and angiographically assessed CVS with specificities of 82.9% (95% CI 66.4%–93.4%) and 94.4% (95% CI 72.7%–99.9%), respectively. The sensitivities were 11.1% (95% CI 3.1%–26.1%) for DCI (n = 71) and 18.8% (95% CI 7.2%–36.4%) for angiographically assessed CVS (n = 50). Furthermore, TCDS detected angiographically determined CVS with a sensitivity of 87.5% (95% CI 71.0%–96.5%) and specificity of 25.0% (95% CI 7.3%–52.4%). In patients with DCI, TCDS detected vasospasm with a sensitivity of 85.7% (95% CI 69.7%–95.2%) and a specificity of 18.8% (95% CI 7.2%–36.4%). DSA detected vasospasm with a sensitivity of 73.9% (95% CI 51.6%–89.8%) and a specificity of 47.8% (95% CI 26.8%–69.4%).

CONCLUSIONS

The study results suggest that continuous cEEG monitoring is highly specific in detecting DCI as well as angiographically assessed CVS. More prospective studies with predetermined thresholds and endpoints are needed to assess the predictive role of cEEG in aSAH.

Combining Transcranial Doppler and EEG Data to Predict Delayed Cerebral Ischemia After Subarachnoid Hemorrhage

BACKGROUND AND OBJECTIVES

Delayed cerebral ischemia (DCI) is the leading complication of subarachnoid hemorrhage (SAH). Because DCI was traditionally thought to be caused by large vessel vasospasm, transcranial Doppler ultrasounds (TCDs) have been the standard of care. Continuous EEG has emerged as a promising complementary monitoring modality and predicts increased DCI risk. Our objective was to determine whether combining EEG and TCD data improves prediction of DCI after SAH. We hypothesize that integrating these diagnostic modalities improves DCI prediction.

METHODS

We retrospectively assessed patients with moderate to severe SAH (2011-2015; Fisher 3-4 or Hunt-Hess 4-5) who had both prospective TCD and EEG acquisition during hospitalization. Middle cerebral artery (MCA) peak systolic velocities (PSVs) and the presence or absence of epileptiform abnormalities (EAs), defined as seizures, epileptiform discharges, and rhythmic/periodic activity, were recorded daily. Logistic regressions were used to identify significant covariates of EAs and TCD to predict DCI. Group-based trajectory modeling (GBTM) was used to account for changes over time by identifying distinct group trajectories of MCA PSV and EAs associated with DCI risk.

RESULTS

We assessed 107 patients; DCI developed in 56 (51.9%). Univariate predictors of DCI are presence of high-MCA velocity (PSV ≥200 cm/s, sensitivity 27%, specificity 89%) and EAs (sensitivity 66%, specificity 62%) on or before day 3. Two univariate GBTM trajectories of EAs predicted DCI (sensitivity 64%, specificity 62.75%). Logistic regression and GBTM models using both TCD and EEG monitoring performed better. The best logistic regression and GBTM models used both TCD and EEG data, Hunt-Hess score at admission, and aneurysm treatment as predictors of DCI (logistic regression: sensitivity 90%, specificity 70%; GBTM: sensitivity 89%, specificity 67%).

DISCUSSION

EEG and TCD biomarkers combined provide the best prediction of DCI. The conjunction of clinical variables with the timing of EAs and high MCA velocities improved model performance. These results suggest that TCD and cEEG are promising complementary monitoring modalities for DCI prediction. Our model has potential to serve as a decision support tool in SAH management.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that combined TCD and EEG monitoring can identify delayed cerebral ischemia after SAH.

Quantitative Electroencephalography (EEG) Predicting Acute Neurologic Deterioration in the Pediatric Intensive Care Unit: A Case Series

Introduction: Continuous neurologic assessment in the pediatric intensive care unit is challenging. Current electroencephalography (EEG) guidelines support monitoring status epilepticus, vasospasm detection, and cardiac arrest prognostication, but the scope of brain dysfunction in critically ill patients is larger. We explore quantitative EEG in pediatric intensive care unit patients with neurologic emergencies to identify quantitative EEG changes preceding clinical detection. Methods: From 2017 to 2020, we identified pediatric intensive care unit patients at a single quaternary children's hospital with EEG recording near or during acute neurologic deterioration. Quantitative EEG analysis was performed using Persyst P14 (Persyst Development Corporation). Included features were fast Fourier transform, asymmetry, and rhythmicity spectrograms, "from-baseline" patient-specific versions of the above features, and quantitative suppression ratio. Timing of quantitative EEG changes was determined by expert review and prespecified quantitative EEG alert thresholds. Clinical detection of neurologic deterioration was defined pre hoc and determined through electronic medical record documentation of examination change or intervention. Results: Ten patients were identified, age 23 months to 27 years, and 50% were female. Of 10 patients, 6 died, 1 had new morbidity, and 3 had good recovery; the most common cause of death was cerebral edema and herniation. The fastest changes were on "from-baseline" fast Fourier transform spectrograms, whereas persistent changes on asymmetry spectrograms and suppression ratio were most associated with morbidity and mortality. Median time from first quantitative EEG change to clinical detection was 332 minutes (interquartile range: 201-456 minutes). Conclusion: Quantitative EEG is potentially useful in earlier detection of neurologic deterioration in critically ill pediatric intensive care unit patients. Further work is required to quantify the predictive value, measure improvement in outcome, and automate the process.

Quantitative Electroencephalography for Early Detection of Elevated Intracranial Pressure in Critically Ill Children: Case Series and Proposed Protocol

OBJECTIVE

To describe quantitative EEG (electroencephalography) suppression ratio in children with increased intracranial pressure comparing acute suppression ratio changes to imaging and/or examination findings.

METHODS

We retrospectively reviewed the suppression ratio from patients with neuroimaging and /or examination findings of increased intracranial pressure while on continuous EEG. The time of the first change in the suppression ratio was compared to the time of the first image and/or examination change confirming increased intracranial pressure.

RESULTS

Thirteen patients with a median age of 3.1 years(interquartile range 1.8-6.3) had a rise in the suppression ratio with median time from identification to acute neuroimaging or examination of increased intracranial pressure of 3.12 hours (interquartile range 2.2-33.5) after the first increase in the suppression ratio.

CONCLUSIONS

Acute suppression ratio increase is seen prior to imaging and/or examination findings of increased intracranial pressure. With further study, the suppression ratio can be targeted with intracranial pressure-lowering agents to prevent morbidity and mortality associated with increased intracranial pressure.

Multimodality Monitoring for Delayed Cerebral Ischemia in Subarachnoid Hemorrhage: A Mini Review

Aneurysmal subarachnoid hemorrhage is a disease with high mortality and morbidity due in large part to delayed effects of the hemorrhage, including vasospasm, and delayed cerebral ischemia. These two are now recognized as overlapping yet distinct entities, and supportive therapies for delayed cerebral ischemia are predicated on identifying DCI as quickly as possible. The purpose of this overview is to highlight diagnostic tools that are being used in the identification of DCI in the neurocritical care settings.

Overview of Acute Ischemic Stroke Evaluation and Management

Stroke is a major contributor to death and disability worldwide. Prior to modern therapy, post-stroke mortality was approximately 10% in the acute period, with nearly one-half of the patients developing moderate-to-severe disability. The most fundamental aspect of acute stroke management is "time is brain". In acute ischemic stroke, the primary therapeutic goal of reperfusion therapy, including intravenous recombinant tissue plasminogen activator (IV TPA) and/or endovascular thrombectomy, is the rapid restoration of cerebral blood flow to the salvageable ischemic brain tissue at risk for cerebral infarction. Several landmark endovascular thrombectomy trials were found to be of benefit in select patients with acute stroke caused by occlusion of the proximal anterior circulation, which has led to a paradigm shift in the management of acute ischemic strokes. In this modern era of acute stroke care, more patients will survive with varying degrees of disability post-stroke. A comprehensive stroke rehabilitation program is critical to optimize post-stroke outcomes. Understanding the natural history of stroke recovery, and adapting a multidisciplinary approach, will lead to improved chances for successful rehabilitation. In this article, we provide an overview on the evaluation and the current advances in the management of acute ischemic stroke, starting in the prehospital setting and in the emergency department, followed by post-acute stroke hospital management and rehabilitation.

Seizures, Status Epilepticus, and Continuous EEG in the Intensive Care Unit

PURPOSE OF REVIEW

This article discusses the evolving definitions of seizures and status epilepticus in the critical care environment and the role of critical care EEG in both diagnosing seizure activity and serving as a predictive biomarker of clinical trajectory.

RECENT FINDINGS

Initial screening EEG has been validated as a tool to predict which patients are at risk of future seizures. However, accepted definitions of seizures and nonconvulsive status epilepticus encourage a treatment trial when the diagnosis on EEG is indeterminate because of periodic or rhythmic patterns or uncertain clinical correlation. Similarly, recent data have demonstrated the diagnostic utility of intracranial EEG in increasing the yield of seizure detection. EEG has additionally been validated as a diagnostic biomarker of covert consciousness, a predictive biomarker of cerebral ischemia and impending neurologic deterioration, and a prognostic biomarker of coma recovery and status epilepticus resolution. A recent randomized trial concluded that patients allocated to continuous EEG had no difference in mortality than those undergoing intermittent EEG but could not demonstrate whether this lack of difference was because of studying heterogeneous conditions, examining a monitoring tool rather than a therapeutic approach, or examining an outcome measure (mortality) perhaps more strongly associated with early withdrawal of life-sustaining therapy than to a sustained response to pharmacotherapy.

SUMMARY

Seizures and status epilepticus are events of synchronous hypermetabolic activity that are either discrete and intermittent or, alternatively, continuous. Seizures and status epilepticus represent the far end of a continuum of ictal-interictal patterns that include lateralized rhythmic delta activity and periodic discharges, which not only predict future seizures but may be further classified as status epilepticus on the basis of intracranial EEG monitoring or a diagnostic trial of antiseizure medication therapy. In particularly challenging cases, neuroimaging or multimodality neuromonitoring may be a useful adjunct documenting metabolic crisis. Specialized uses of EEG as a prognostic biomarker have emerged in traumatic brain injury for predicting language function and covert consciousness, cardiac arrest for predicting coma recovery, and subarachnoid hemorrhage for predicting neurologic deterioration due to delayed cerebral ischemia.

Electroencephalography, Hospital Complications, and Longitudinal Outcomes After Subarachnoid Hemorrhage

BACKGROUND

Following non-traumatic subarachnoid hemorrhage (SAH), in-hospital delayed cerebral ischemia is predicted by two chief events on continuous EEG (cEEG): new or worsening epileptiform abnormalities (EAs) and deterioration of cEEG background frequencies. We evaluated the association between longitudinal outcomes and these cEEG biomarkers. We additionally evaluated the association between longitudinal outcomes and other in-hospital complications.

METHODS

Patients with nontraumatic SAH undergoing ≥ 3 days of cEEG monitoring were enrolled in a prospective study evaluating longitudinal outcomes. Modified Rankin Scale (mRS) was assessed at discharge, and at 3- and 6-month follow-up time points. Adjusting for baseline severity in a cumulative proportional odds model, we modeled the mRS ordinally and measured the association between mRS and two forms of in-hospital cEEG deterioration: (1) cEEG evidence of new or worsening epileptiform abnormalities and (2) cEEG evidence of new background deterioration. We compared the magnitude of these associations at each time point with the association between mRS and other in-hospital complications: (1) delayed cerebral ischemia (DCI), (2) hospital-acquired infections (HAI), and (3) hydrocephalus. In a secondary analysis, we employed a linear mixed effects model to examine the association of mRS over time (dichotomized as 0-3 vs. 4-6) with both biomarkers of cEEG deterioration and with other in-hospital complications.

RESULTS

In total, 175 mRS assessments were performed in 59 patients. New or worsening EAs developed in 23 (39%) patients, and new background deterioration developed in 24 (41%). Among cEEG biomarkers, new or worsening EAs were independently associated with mRS at discharge, 3, and 6 months, respectively (adjusted cumulative proportional odds 4.99, 95% CI 1.60-15.6; 3.28, 95% CI 1.14-9.5; and 2.71, 95% CI 0.95-7.76), but cEEG background deterioration lacked an association. Among hospital complications, DCI was associated with discharge, 3-, and 6-month outcomes (adjusted cumulative proportional odds 4.75, 95% CI 1.64-13.8; 3.4; 95% CI 1.24-9.01; and 2.45, 95% CI 0.94-6.6), but HAI and hydrocephalus lacked an association. The mixed effects model demonstrated that these associations were sustained over longitudinal assessments without an interaction with time.

CONCLUSION

Although new or worsening EAs and cEEG background deterioration have both been shown to predict DCI, only new or worsening EAs are associated with a sustained impairment in functional outcome. This novel finding raises the potential for identifying therapeutic targets that may also influence outcomes.

The association of bispectral index values and metrics of cerebral perfusion during cardiopulmonary bypass

STUDY OBJECTIVE

Low bispectral index (BIS) values have been associated with adverse postoperative outcomes. However, trials of optimizing BIS by titrating anesthetic administration have reported conflicting results. One potential explanation is that cerebral perfusion may also affect BIS, but the extent of this relationship is not clear. Therefore, we examined whether BIS would be associated with cerebral perfusion during cardiopulmonary bypass, when anesthetic concentration was constant.

DESIGN

Observational cohort study.

SETTING

Cardiac operating room.

PATIENTS

Seventy-nine patients with cardiopulmonary bypass surgery were included.

MEASUREMENTS

Continuous BIS, mean arterial blood pressure (MAP), cerebral blood flow velocity (CBFV), and regional cerebral oxygen saturation (rSO₂) were monitored, with analysis during a period of constant anesthetic. Mean flow index (Mx) was calculated as Pearson correlation between MAP and CBFV. The lower limit of autoregulation (LLA) was identified as the MAP value at which Mx increased >0.4 with decreasing blood pressure. Postoperative delirium was assessed using the 3D-Confusion Assessment Method.

RESULTS

Mean BIS was lower during periods of MAP < LLA compared with BIS when MAP>LLA (mean 49.35 ± 10.40 vs. 50.72 ± 10.04, p = 0.002, mean difference = 1.38 [standard error: 0.42]). There was a dose response effect, with the BIS proportionately decreasing as MAP decreased below LLA (β = 0.15, 95% CI for the average slope across all patients 0.07 to 0.23, p < 0.001). In contrast, BIS was relatively unchanged when MAP was above LLA (β = 0.03, 95% CI for the average slope across all patients -0.02 to 0.09, p = 0.22). Additionally, increasing CBFV and rSO₂ were associated with increasing BIS. Patients with postoperative delirium had lower mean BIS and higher percentage of time duration with BIS <45 compared to patients without delirium.

CONCLUSIONS

There was an association of BIS and metrics of cerebral perfusion during a period of constant anesthetic administration, but the absolute magnitude of change in BIS as MAP decreased below the LLA was small.

Neurocritical Care and Brain Monitoring

The goal of neurocritical care (NCC) is to improve the outcome of patients with neurologic insults. NCC includes the management of the primary brain injury and prevention of secondary brain injury; this is achieved with standardized clinical care for specific disorders along with neuromonitoring. Neuromonitoring uses multiple modalities, with certain modalities better suited to certain disorders. The term "multimodality monitoring" refers to using multiple modalities at the same time. This article reviews pediatric NCC, the various physiologic parameters used, especially continuous electroencephalographic monitoring.

Quantitative EEG Changes Correlate With Post-Clamp Ischemia During Carotid Endarterectomy

INTRODUCTION

EEG monitoring is a critical tool for identifying cerebral ischemia during carotid endarterectomy (CEA). Quantitative EEG can be used to supplement visual EEG review, but which measures best predict post-clamp ischemia is unclear.

PURPOSE

To determine which quantitative EEG parameters reliably detect intraoperative ischemia during CEA.

METHODS

The authors identified patients who underwent carotid endarterectomy at Columbia University Medical Center from 2007 to 2014 with intraoperative EEG monitoring. Two masked physicians reviewed these EEGs retrospectively and determined whether there was post-clamp ischemia, categorizing patients into (1) ischemic-change and (2) no-ischemic-change groups. The authors then studied the performance of a battery of quantitative EEG measures (alpha, beta, theta, and delta power bands, alpha-delta ratio, beta-delta ratio, amplitude-integrated EEG, and 90% spectral edge frequency) against physician review as the gold standard.

RESULTS

Of 118 patients, 15 were included in the ischemic-change group and 103 in the no-ischemic-change group. Ipsilateral post-clamp trough values of all the quantitative EEG measures assessed were significantly decreased for patients in the ischemic-change group. Decreases in alpha, beta, and theta power of 52.1%, 41.6%, and 36.4% or greater, respectively, were most predictive of post-clamp ischemia.

CONCLUSIONS

Quantitative EEG monitoring during carotid endarterectomy, in addition to visual EEG monitoring, may improve the detection of cerebral ischemia and thus result in fewer perioperative strokes.

Alpha power decrease in quantitative EEG detects development of cerebral infarction after subarachnoid hemorrhage early

OBJECTIVE

In subarachnoid hemorrhage (SAH), transcranial Doppler/color-coded-duplex sonography (TCD/TCCS) is used to detect delayed cerebral ischemia (DCI). In previous studies, quantitative electroencephalography (qEEG) also predicted imminent DCI. This study aimed to compare and analyse the ability of qEEG and TCD/TCCS to early identify patients who will develop later manifest cerebral infarction.

METHODS

We analysed cohorts of two previous qEEG studies. Continuous six-channel-EEG with artefact rejection and a detrending procedure was applied. Alpha power decline of ≥ 40% for ≥ 5 hours compared to a 6-hour-baseline was defined as significant EEG event. Median reduction and duration of alpha power decrease in each channel was determined. Vasospasm was diagnosed by TCD/TCCS, identifying the maximum frequency and days of vasospasm in each territory.

RESULTS

34 patients were included (17 male, mean age 56 ± 11 years, Hunt and Hess grade: I-V, cerebral infarction: 9). Maximum frequencies in TCD/TCCS and alpha power reduction in qEEG were correlated (r = 0.43; p = 0.015). Patients with and without infarction significantly differed in qEEG parameters (maximum alpha power decrease: 78% vs 64%, p = 0.019; summed hours of alpha power decline: 236 hours vs 39 hours, p = 0.006) but showed no significant differences in TCD/TCCS parameters.

CONCLUSIONS

There was a moderate correlation of TCD/TCCS frequencies and qEEG alpha power reduction but only qEEG differentiated between patients with and without cerebral infarction.

SIGNIFICANCE

qEEG represents a non-invasive, continuous tool to identify patients at risk of cerebral infarction.

Machine Learning-Driven Metabolomic Evaluation of Cerebrospinal Fluid: Insights Into Poor Outcomes After Aneurysmal Subarachnoid Hemorrhage

BACKGROUND

Aneurysmal subarachnoid hemorrhage (aSAH) is associated with a high mortality and poor neurologic outcomes. The biologic underpinnings of the morbidity and mortality associated with aSAH remain poorly understood.

OBJECTIVE

To ascertain potential insights into pathological mechanisms of injury after aSAH using an approach of metabolomics coupled with machine learning methods.

METHODS

Using cerebrospinal fluid (CSF) samples from 81 aSAH enrolled in a retrospective cohort biorepository, samples collected during the peak of delayed cerebral ischemia were analyzed using liquid chromatography-tandem mass spectrometry. A total of 138 metabolites were measured and quantified in each sample. Data were analyzed using elastic net (EN) machine learning and orthogonal partial least squares-discriminant analysis (OPLS-DA) to identify the leading CSF metabolites associated with poor outcome, as determined by the modified Rankin Scale (mRS) at discharge and at 90 d. Repeated measures analysis determined the effect size for each metabolite on poor outcome.

RESULTS

EN machine learning and OPLS-DA analysis identified 8 and 10 metabolites, respectively, that predicted poor mRS (mRS 3-6) at discharge and at 90 d. Of these candidates, symmetric dimethylarginine (SDMA), dimethylguanidine valeric acid (DMGV), and ornithine were consistent markers, with an association with poor mRS at discharge (P = .0005, .002, and .0001, respectively) and at 90 d (P = .0036, .0001, and .004, respectively). SDMA also demonstrated a significantly elevated CSF concentration compared with nonaneurysmal subarachnoid hemorrhage controls (P = .0087).

CONCLUSION

SDMA, DMGV, and ornithine are vasoactive molecules linked to the nitric oxide pathway that predicts poor outcome after severe aSAH. Further study of dimethylarginine metabolites in brain injury after aSAH is warranted.

Low intracranial pressure variability is associated with delayed cerebral ischemia and unfavorable outcome in aneurysmal subarachnoid hemorrhage

Purpose

High intracranial pressure variability (ICPV) is associated with favorable outcome in traumatic brain injury, by mechanisms likely involving better cerebral blood flow regulation. However, less is known about ICPV in aneurysmal subarachnoid hemorrhage (aSAH). In this study, we investigated the explanatory variables for ICPV in aSAH and its association with delayed cerebral ischemia (DCI) and clinical outcome.

Methods

In this retrospective study, 242 aSAH patients, treated at the neurointensive care, Uppsala, Sweden, 2008–2018, with ICP monitoring the first ten days post-ictus were included. ICPV was evaluated on three time scales: (1) ICPV-1 m—ICP slow wave amplitude of wavelengths between 55 and 15 s, (2) ICPV-30 m—the deviation from the mean ICP averaged over 30 min, and (3) ICPV-4 h—the deviation from the mean ICP averaged over 4 h. The ICPV measures were analyzed in the early phase (day 1–3), in the early vasospasm phase (day 4–6.5), and the late vasospasm phase (day 6.5–10).

Results

High ICPV was associated with younger age, reduced intracranial pressure/volume reserve (high RAP), and high blood pressure variability in multiple linear regression analyses for all ICPV measures. DCI was associated with reduced ICPV in both vasospasm phases. High ICPV-1 m in the post-ictal early phase and the early vasospasm phase predicted favorable outcome in multiple logistic regressions, whereas ICPV-30 m and ICPV-4 h in the late vasospasm phase had a similar association.

Conclusions

Higher ICPV may reflect more optimal cerebral vessel activity, as reduced values are associated with an increased risk of DCI and unfavorable outcome after aSAH.

ICU-cEEG Monitoring

The neurological application of long-term electroencephalography (EEG) monitoring in the intensive care unit (ICU) has been implemented in many healthcare institutions. The use of EEG as a monitoring tool in the ICU affords many potential benefits. Uses include the identification of seizures, vasospasm following subarachnoid hemorrhage (SAH), the assessment of coma and the determination of brain death. Neurologic critical care is focused on recognition and treatment of secondary insults. Often treatment is withheld because these insults are not recognized early enough until an irreversible deficit manifest. Continuous EEG (cEEG) monitoring provides a unique potential to recognize these insults and offers an opportunity for early intervention. Why should we continuously monitor the brain with EEG in the ICU? Nonconvulsive seizures (NCS) are common in comatose patients. Nonconvulsive Status Epilepticus (NCSE) and NCS ¹ are damaging to brain tissue; thus, rapid control of seizures is essential to preserving brain function. With the increased use of cEEG in critical care areas, the purpose of this paper is to examine the use and benefits of EEG monitoring of ICU patients, review the indications for the use of cEEG and discuss technical issues and concerns when performing cEEG monitoring. This article has been divided into six distinct sections: (1) Seizures, NCS, and NCSE (2) Periodic Discharges ² and Patterns on the Ictal-interictal Continuum, (3) Cerebral Ischemia, SAH, and Delayed Cerebral Ischemia (DCI), (4) Encephalopathy and Coma (5) ECI and Brain Death, and (6) ICU-cEEG Monitoring Techniques.

Bibliometric Analysis of the Top 100 Most Cited Articles on Cerebral Vasospasm

OBJECTIVE

Bibliometric analysis reflects the scientific recognition and influential performance of a published article within its field. Our aim is to identify and analyze the top 100 most-cited articles on cerebral vasospasm.

METHODS

A title-specific search was carried out using the Scopus database. The top 100 cited articles including the keywords "Cerebral Vasospasm" AND "Vasospasm" were retrieved and stratified in a descending order: title, authors, institution, publishing journal, country of origin, year of publication, and topic of each article were studied.

RESULTS

The top 100 articles have an accumulative citation count of 20,972, with 209 average citations per article. Publication dates ranged from 1968 to 2012, with the most productive years between 1998 and 2005. Clinical studies are the most frequent category, followed by pathophysiology. The list includes 7 clinical trials, which received accumulative citations of 1525. The top cited article had received 2109 citations, with 52.7 citations per year. The top 100 articles were published across 14 countries, with most originating from the United States. The lead research institution was the University of Alberta. The most used journal was Journal of Neurosurgery.

CONCLUSIONS

Bibliometric analysis has garnered major interest in recent years. It shows the publication trends, knowledge evolution, and evidence-based practice throughout the years. The collection of highly cited articles may assist physicians in gaining a better understanding of the nature of cerebral vasospasm and optimize their clinical practice.

Clinical and advanced neurophysiology in the prognostic and diagnostic evaluation of disorders of consciousness: review of an IFCN-endorsed expert group

The analysis of spontaneous EEG activity and evoked potentialsis a cornerstone of the instrumental evaluation of patients with disorders of consciousness (DoC). Thepast few years have witnessed an unprecedented surge in EEG-related research applied to the prediction and detection of recovery of consciousness after severe brain injury,opening up the prospect that new concepts and tools may be available at the bedside. This paper provides a comprehensive, critical overview of bothconsolidated and investigational electrophysiological techniquesfor the prognostic and diagnostic assessment of DoC.We describe conventional clinical EEG approaches, then focus on evoked and event-related potentials, and finally we analyze the potential of novel research findings. In doing so, we (i) draw a distinction between acute, prolonged and chronic phases of DoC, (ii) attempt to relate both clinical and research findings to the underlying neuronal processes and (iii) discuss technical and conceptual caveats.The primary aim of this narrative review is to bridge the gap between standard and emerging electrophysiological measures for the detection and prediction of recovery of consciousness. The ultimate scope is to provide a reference and common ground for academic researchers active in the field of neurophysiology and clinicians engaged in intensive care unit and rehabilitation.

Soluble ST2 Is Associated With New Epileptiform Abnormalities Following Nontraumatic Subarachnoid Hemorrhage

Background and Purpose- We evaluated the association between 2 types of predictors of delayed cerebral ischemia after nontraumatic subarachnoid hemorrhage, including biomarkers of the innate immune response and neurophysiologic changes on continuous electroencephalography. Methods- We studied subarachnoid hemorrhage patients that had at least 72 hours of continuous electroencephalography and blood samples collected within the first 5 days of symptom onset. We measured inflammatory biomarkers previously associated with delayed cerebral ischemia and functional outcome, including soluble ST2 (sST2), IL-6 (interleukin-6), and CRP (C-reactive protein). Serial plasma samples and cerebrospinal fluid sST2 levels were available in a subgroup of patients. Neurophysiologic changes were categorized into new or worsening epileptiform abnormalities (EAs) or new background deterioration. The association of biomarkers with neurophysiologic changes were evaluated using the Wilcoxon rank-sum test. Plasma and cerebrospinal fluid sST2 were further examined longitudinally using repeated measures mixed-effects models. Results- Forty-six patients met inclusion criteria. Seventeen (37%) patients developed new or worsening EAs, 21 (46%) developed new background deterioration, and 8 (17%) developed neither. Early (day, 0-5) plasma sST2 levels were higher among patients with new or worsening EAs (median 115 ng/mL [interquartile range, 73.8-197]) versus those without (74.7 ng/mL [interquartile range, 44.8-102]; P=0.024). Plasma sST2 levels were similar between patients with or without new background deterioration. Repeated measures mixed-effects modeling that adjusted for admission risk factors showed that the association with new or worsening EAs remained independent for both plasma sST2 (β=0.41 [95% CI, 0.09-0.73]; P=0.01) and cerebrospinal fluid sST2 (β=0.97 [95% CI, 0.14-1.8]; P=0.021). IL-6 and CRP were not associated with new background deterioration or with new or worsening EAs. Conclusions- In patients admitted with subarachnoid hemorrhage, sST2 level was associated with new or worsening EAs but not new background deterioration. This association may identify a link between a specific innate immune response pathway and continuous electroencephalography abnormalities in the pathogenesis of secondary brain injury after subarachnoid hemorrhage.

Assessment of cerebral hemodynamics during neurosurgical procedures using laser speckle image analysis

Aneurysmal subarachnoid hemorrhage (aSAH) is a severe medical condition associated with a significant cause of mortality throughout the world. Cisterna magna injection model is accepted widely to mimic clinical aSAH and is performed on small animal models to study aSAH during neurosurgery. Coherent light scattered from the surface of the rat brain is used to infer information about the variations in blood flow during this condition. We obtained speckle images from the exposed cortex during the entire experiment using an external tissue imaging system. Contrast and fractal analyses are carried out for the recorded speckle pattern time series. Correlation analysis based on Hurst exponent for these images is found to be a more sensitive tool in studying aSAH as compared to routinely used laser speckle contrast analysis for assessing the changes in blood flow velocity. Additionally, our studies provide improved blood flow detection sensitivity with image Hurst exponent in combination with computed fractal dimension, during an event of aSAH.

Amplitude Instability of Somatosensory Evoked Potentials as an Indicator of Delayed Cerebral Ischemia in a Case of Subarachnoid Hemorrhage

We describe a 55-year-old male patient with a subarachnoid hemorrhage (SAH) as a result of left middle cerebral artery (MCA) aneurysm rupture, who underwent continuous electroencephalogram (EEG) and somatosensory evoked potential (cEEG-SEP) monitoring that showed an unusual SEP trend pattern. EEG was continuously recorded, and SEPs following stimulation of median nerves were recorded every 50 minutes, with the amplitude and latency of the cortical components automatically trended. An increase in intracranial pressure required a left decompressive craniectomy. cEEG-SEP monitoring was started on day 7, which showed a prolonged (24 hours) instability of SEPs in the left hemisphere. During this phase, left MCA vasospasm was demonstrated by transcranial Doppler (TCD), and computed tomography perfusion (CTP) showed a temporo-parieto-occipital ischemic penumbra. Following intravascular treatment, hypoperfusion and the amplitude of cortical SEPs improved. In our case, a prolonged phase of SEP amplitude instability during vasospasm in SAH correlated with a phase of ischemic penumbra, as demonstrated by CTP. In SAH, SEP instability during continuous monitoring is a pattern of alert that can allow treatments capable of avoiding irreversible neurological deterioration.

Quantitative EEG After Subarachnoid Hemorrhage Predicts Long-Term Functional Outcome

PURPOSE

Delayed cerebral ischemia is a major complication after subarachnoid hemorrhage. Our previous study showed that alpha power reduction in continuous quantitative EEG predicts delayed cerebral ischemia. In this prospective cohort, we aimed to determine the prognostic value of alpha power in quantitative EEG for the long-term outcome of patients with subarachnoid hemorrhage.

METHODS

Adult patients with nontraumatic subarachnoid hemorrhage were included if admitted early enough for EEG to start within 72 hours after symptom onset. Continuous six-channel EEG was applied. Unselected EEG signals underwent automated artifact rejection, power spectral analysis, and detrending. Alpha power decline of ≥40% for ≥5 hours was defined as critical EEG event based on previous findings. Six-month outcome was obtained using the modified Rankin scale.

RESULTS

Twenty-two patients were included (14 male; mean age, 59 years; Hunt and Hess grade I-IV; duration of EEG monitoring, median 14 days). Poor outcome (modified Rankin scale, 2-5) was noted in 11 of 16 patients (69%) with critical EEG events. All six patients (100%) without EEG events achieved an excellent outcome (modified Rankin scale 0, 1) (P = 0.0062; sensitivity 100%, specificity 54.5%). Vasospasm detected with transcranial Doppler/Duplex sonography appeared 1.5 days after EEG events and showed weaker association with outcome (P = 0.035; sensitivity 100%, specificity 45.5%). There was no significant association between EEG events and ischemic lesions on imaging (P = 0.1). Also, no association between ischemic lesions and outcome was seen (P = 0.64).

CONCLUSIONS

Stable alpha power in quantitative EEG reflects successful therapy and predicts good functional outcome after subarachnoid hemorrhage. Critical alpha power reduction indicates an increased risk of poor functional outcome.

Cross-Frequency Coupling Between Cerebral Blood Flow Velocity and EEG in Ischemic Stroke Patients With Large Vessel Occlusion

Background: Neurovascular coupling enables a rapid adaptation of cerebral blood flow (CBF) to support neuronal activities. Whether this mechanism is compromised during the acute phase after ischemic stroke remains unknown. In this study, we applied a phase-amplitude cross-frequency coupling (PAC) algorithm to investigate multimodal neuro signals including CBF velocity (CBFV), and electroencephalography (EEG). Methods: Acute ischemic stroke patients admitted to the Neurointensive Care Unit, Tiantan Hospital, Capital Medical University (Beijing, China) with continuous monitoring of 8-lead EEG (F3-C3, T3-P3, P3-O1, F4-C4, T4-P4, P4-O2), non-invasive arterial blood pressure (ABP), and bilateral CBFV of the middle cerebral arteries or posterior cerebral arteries were retrospectively analyzed. PAC was calculated between the phase of CBFV in frequency bands (0-0.05 and 0.05-0.15 Hz) and the EEG amplitude in five bands (δ, θ, α, β, γ). The global PAC was calculated as the sum of all PACs across the six EEG channels and five EEG bands for each patient. The hemispherical asymmetry of cross-frequency coupling (CFC) was calculated as the difference between left and right PAC. Results: Sixteen patients (3 males) met our inclusion criteria. Their age was 60.9 ± 7.9 years old. The mean ABP, mean left CBFV, and mean right CBFV were 90.2 ± 31.2 mmHg, 57.3 ± 20.6 cm/s, and 68.4 ± 20.9 cm/s, respectively. The PAC between CBFV and EEG was significantly higher in β and γ bands than in the other three bands. Occipital region (P3-O1 and P4-O2 channels) showed stronger PAC than the other regions. The deceased group tended to have smaller global PAC than the survival group (the area under the receiver operating characteristic curve [AUROC] was 0.81, p = 0.57). The unfavorable outcome group showed smaller global PAC than the favorable group (AUROC = 0.65, p = 0.23). The PAC asymmetry between the two brain hemispheres correlates with the degree of stenosis in stroke patients (p = 0.01). Conclusion: We showed that CBFV interacts with EEG in β and γ bands through a phase-amplitude CFC relationship, with the strongest PAC found in the occipital region and that the degree of hemispherical asymmetry of CFC correlates with the degree of stenosis.