Continuous EEG is associated with favorable hospitalization outcomes for critically ill patients

Emergent Management of Status Epilepticus

OBJECTIVE

Status epilepticus is a neurologic emergency that can be life- threatening. The key to effective management is recognition and prompt initiation of treatment. Management of status epilepticus requires a patient-specific-approach framework, consisting of four axes: (1) semiology, (2) etiology, (3) EEG correlate, and (4) age. This article provides a comprehensive overview of status epilepticus, highlighting the current treatment approaches and strategies for management and control.

LATEST DEVELOPMENTS

Administering appropriate doses of antiseizure medication in a timely manner is vital for halting seizure activity. Benzodiazepines are the first-line treatment, as demonstrated by three randomized controlled trials in the hospital and prehospital settings. Benzodiazepines can be administered through IV, intramuscular, rectal, or intranasal routes. If seizures persist, second-line treatments such as phenytoin and fosphenytoin, valproate, or levetiracetam are warranted. The recently published Established Status Epilepticus Treatment Trial found that all three of these drugs are similarly effective in achieving seizure cessation in approximately half of patients. For cases of refractory and super-refractory status epilepticus, IV anesthetics, including ketamine and γ-aminobutyric acid-mediated (GABA-ergic) medications, are necessary. There is an increasing body of evidence supporting the use of ketamine, not only in the early phases of stage 3 status epilepticus but also as a second-line treatment option.

ESSENTIAL POINTS

As with other neurologic emergencies, "time is brain" when treating status epilepticus. Antiseizure medication should be initiated quickly to achieve seizure cessation. There is a need to explore newer generations of antiseizure medications and nonpharmacologic modalities to treat status epilepticus.

Continuous Electroencephalogram Use and Hospital Outcomes in Critically Ill Children

PURPOSE

To examine the association between CEEG use and discharge status, length of hospitalization, and health care cost in a critically ill pediatric population.

METHODS

Four thousand three hundred forty-eight critically ill children were identified from a US nationwide administrative health claims database; 212 (4.9%) of whom underwent CEEG during admissions (January 1, 2015-june 30, 2020). Discharge status, length of hospitalization, and health care cost were compared between patients with and without CEEG use. Multiple logistic regression analyzed the association between CEEG use and these outcomes, controlling for age and underlying neurologic diagnosis. Prespecified subgroups analysis was performed for children with seizures/status epilepticus, with altered mental status and with cardiac arrest.

RESULTS

Compared with critically ill children without CEEG, those who underwent CEEG were likely to have shorter hospital stays than the median (OR = 0.66; 95% CI = 0.49-0.88; P = 0.004), and also total hospitalization costs were less likely to exceed the median (OR = 0.59; 95% CI = 0.45-0.79; P < 0.001). There was no difference in odds of favorable discharge status between those with and without CEEG (OR = 0.69; 95% CI = 0.41-1.08; P = 0.125). In the subgroup of children with seizures/status epilepticus, those with CEEG were less likely to have unfavorable discharge status, compared with those without CEEG (OR = 0.51; 95% CI = 0.27-0.89; P = 0.026).

CONCLUSIONS

Among critically ill children, CEEG was associated with shorter stay and lower costs of hospitalization but was not associated with change of favorable discharge status except the subgroup with seizures/status epilepticus.

Recent advances in clinical electroencephalography

PURPOSE OF REVIEW

Clinical electroencephalography (EEG) is a conservative medical field. This explains likely the significant gap between clinical practice and new research developments. This narrative review discusses possible causes of this discrepancy and how to circumvent them. More specifically, we summarize recent advances in three applications of clinical EEG: source imaging (ESI), high-frequency oscillations (HFOs) and EEG in critically ill patients.

RECENT FINDINGS

Recently published studies on ESI provide further evidence for the accuracy and clinical utility of this method in the multimodal presurgical evaluation of patients with drug-resistant focal epilepsy, and opened new possibilities for further improvement of the accuracy. HFOs have received much attention as a novel biomarker in epilepsy. However, recent studies questioned their clinical utility at the level of individual patients. We discuss the impediments, show up possible solutions and highlight the perspectives of future research in this field. EEG in the ICU has been one of the major driving forces in the development of clinical EEG. We review the achievements and the limitations in this field.

SUMMARY

This review will promote clinical implementation of recent advances in EEG, in the fields of ESI, HFOs and EEG in the intensive care.

Estimate of Patients With Missed Seizures Because of Delay in Conventional EEG

PURPOSE

There is frequent delay between ordering and placement of conventional EEG. Here we estimate how many patients had seizures during this delay.

METHODS

Two hundred fifty consecutive adult patients who underwent conventional EEG monitoring at the University of Wisconsin Hospital were retrospectively chart reviewed for demographics, time of EEG order, clinical and other EEG-related information. Patients were stratified by use of anti-seizure medications before EEG and into low-risk, medium-risk, and high-risk groups based on 2HELPS2B score (0, 1, or >1). Monte Carlo simulations (500 trials) were performed to estimate seizures during delay.

RESULTS

The median delay from EEG order to performing EEG was 2.00 hours (range of 0.5-8.00 hours) in the total cohort. For EEGs ordered after-hours, it was 2.00 hours (range 0.5-8.00 hours), and during business hours, it was 2.00 hours (range 0.5-6.00 hours). The place of EEG, intensive care unit, emergency department, and general floor, did not show significant difference (P = 0.84). Anti-seizure medication did not affect time to first seizure in the low-risk (P = 0.37), medium-risk (P = 0.44), or high-risk (P = 0.12) groups. The estimated % of patients who had a seizure in the delay period for low-risk group (2HELPS2B = 0) was 0.8%, for the medium-risk group (2HELPS2B = 1) was 10.3%, and for the high-risk group (2HELPS2B > 1) was 17.6%, and overall risk was 7.2%.

CONCLUSIONS

The University of Wisconsin Hospital with 24-hour in-house EEG technologists has a median delay of 2 hours from order to start of EEG, shorter than published reports from other centers. Nonetheless, seizures were likely missed in about 7.2% of patients.

Residual Seizure Rate of Intermittent Inpatient EEG Compared to a Continuous EEG Model

BACKGROUND

Subclinical seizures are common in hospitalized patients and require electroencephalography (EEG) for detection and intervention. At our institution, continuous EEG (cEEG) is not available, but intermittent EEGs are subject to constant live interpretation. As part of quality improvement (QI), we sought to estimate the residual missed seizure rate at a typical quaternary Canadian health care center without cEEG.

METHODS

We calculated residual risk percentages using the clinically validated 2HELPS2B score to risk-stratify EEGs before deriving a risk percentage using a MATLAB calculator which modeled the risk decay curve for each recording. We generated a range of estimated residual seizure rates depending on whether a pre-cEEG screening EEG was simulated, EEGs showing seizures were included, or repeat EEGs on the same patient were excluded.

RESULTS

Over a 4-month QI period, 499 inpatient EEGs were scored as low (n = 125), medium (n = 123), and high (n = 251) seizure risk according to 2HELPS2B criteria. Median recording duration was 1:00:06 (interquartile range, IQR 30:40-2:21:10). The model with highest residual seizure rate included recordings with confirmed electrographic seizures (median 20.83%, IQR 20.6-26.6%), while the model with lowest residual seizure rate was in seizure-free recordings (median 10.59%, IQR 4%-20.6%). These rates were significantly higher than the benchmark 5% miss-rate threshold set by 2HELPS2B (p<0.0001).

CONCLUSIONS

We estimate that intermittent inpatient EEG misses 2-4 times more subclinical seizures than the 2HELPS2B-determined acceptable 5% seizure miss-rate threshold for cEEG. Future research is needed to determine the impact of potentially missed seizures on clinical care.

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.

Identifying inpatient hospitalizations with continuous electroencephalogram monitoring from administrative data

BACKGROUND

Continuous electroencephalography (cEEG) is increasingly utilized in hospitalized patients to detect and treat seizures. Epidemiologic and observational studies using administrative datasets can provide insights into the comparative and cost effectiveness of cEEG utilization. Defining patient cohorts that underwent acute inpatient cEEG from administrative datasets is limited by the lack of validated codes differentiating elective epilepsy monitoring unit (EMU) admissions from acute inpatient hospitalization with cEEG utilization. Our aim was to develop hospital administrative data-based models to identify acute inpatient admissions with cEEG monitoring and distinguish them from EMU admissions.

METHODS

This was a single center retrospective cohort study of adult (≥ 18 years old) inpatient admissions with a cEEG procedure (EMU or acute inpatient) between January 2016-April 2022. The gold standard for acute inpatient cEEG vs. EMU was obtained from the local EEG recording platform. An extreme gradient boosting model was trained to classify admissions as acute inpatient cEEG vs. EMU using administrative data including demographics, diagnostic and procedure codes, and medications.

RESULTS

There were 9,523 patients in our cohort with 10,783 hospital admissions (8.5% EMU, 91.5% acute inpatient cEEG); with average age of 59 (SD 18.2) years; 46.2% were female. The model achieved an area under the receiver operating curve of 0.92 (95% CI [0.91-0.94]) and area under the precision-recall curve of 0.99 [0.98-0.99] for classification of acute inpatient cEEG.

CONCLUSIONS

Our model has the potential to identify cEEG monitoring admissions in larger cohorts and can serve as a tool to enable large-scale, administrative data-based studies of EEG utilization.

Continuous versus Routine Electroencephalography in the Intensive Care Unit: A Review of Current Evidence

BACKGROUND

Electroencephalography (EEG) has long been used to detect seizures in patients with disorders of consciousness. In recent years, there has been a drastically increased adoption of continuous EEG (cEEG) in the intensive care units (ICUs). Given the resources necessary to record and interpret cEEG, this is still not available in every center and widespread recommendations to use continuous instead of routine EEG (typically lasting 20 min) are still a matter of some debate. Considering recent literature and personal experience, this review offers a rationale and practical advice to address this question.

SUMMARY

Despite the development of increasingly performant imaging techniques and several validated biomarkers, EEG remains central to clinicians in the intensive care unit and has been experiencing expanding popularity for at least 2 decades. Not only does EEG allow seizure or status epilepticus detection, which in the ICU often present without clinical movements, but it is also paramount for the prognostic evaluation of comatose patients, especially after cardiac arrest, and for detecting delayed ischemia after subarachnoid hemorrhage. At the end of the last Century, improvements of technical and digital aspects regarding recording and storage of EEG tracings have progressively led to the era of cEEG and automated quantitative analysis.

KEY MESSAGES

As compared to repeated rEEG, cEEG in comatose patients does not seem to improve clinical prognosis to a relevant extent, despite allowing a more performant of detection ictal events and consequent therapeutic modifications. The choice between cEEG and rEEG must therefore always be patient-tailored.

Real-World Continuous EEG Utilization and Outcomes in Hospitalized Patients With Acute Cerebrovascular Diseases

PURPOSE

Continuous electroencephalography (cEEG) is recommended for hospitalized patients with cerebrovascular diseases and suspected seizures or unexplained neurologic decline. We sought to (1) identify areas of practice variation in cEEG utilization, (2) determine predictors of cEEG utilization, (3) evaluate whether cEEG utilization is associated with outcomes in patients with cerebrovascular diseases.

METHODS

This cohort study of the Premier Healthcare Database (2014-2020), included hospitalized patients age >18 years with cerebrovascular diseases (identified by ICD codes). Continuous electroencephalography was identified by International Classification of Diseases (ICD)/Current Procedural Terminology (CPT) codes. Multivariable lasso logistic regression was used to identify predictors of cEEG utilization and in-hospital mortality. Propensity score-matched analysis was performed to determine the relation between cEEG use and mortality.

RESULTS

1,179,471 admissions were included; 16,777 (1.4%) underwent cEEG. Total number of cEEGs increased by 364% over 5 years (average 32%/year). On multivariable analysis, top five predictors of cEEG use included seizure diagnosis, hospitals with >500 beds, regions Northeast and South, and anesthetic use. Top predictors of mortality included use of mechanical ventilation, vasopressors, anesthetics, antiseizure medications, and age. Propensity analysis showed that cEEG was associated with lower in-hospital mortality (Average Treatment Effect -0.015 [95% confidence interval -0.028 to -0.003], Odds ratio 0.746 [95% confidence interval, 0.618-0.900]).

CONCLUSIONS

There has been a national increase in cEEG utilization for hospitalized patients with cerebrovascular diseases, with practice variation. cEEG utilization was associated with lower in-hospital mortality. Larger comparative studies of cEEG-guided treatments are indicated to inform best practices, guide policy changes for increased access, and create guidelines on triaging and transferring patients to centers with cEEG capability.

Nonconvulsive Status Epilepticus: A Review for Emergency Clinicians

BACKGROUND

Status epilepticus is associated with significant morbidity and mortality and is divided into convulsive status epilepticus and nonconvulsive status epilepticus (NCSE).

OBJECTIVE

This review provides a focused evaluation of NCSE for emergency clinicians.

DISCUSSION

NCSE is a form of status epilepticus presenting with prolonged seizure activity. This disease is underdiagnosed, as it presents with nonspecific signs and symptoms, most commonly change in mental status without overt convulsive motor activity. Causes include epilepsy, cerebral pathology or injury, any systemic insult such as infection, and drugs or toxins. Mortality is primarily related to the underlying condition. Patients most commonly present with altered mental status, but other signs and symptoms include abnormal ocular movements and automatisms such as lip smacking or subtle motor twitches in the face or extremities. The diagnosis is divided into electrographic and electroclinical, and although electroencephalogram (EEG) is recommended for definitive diagnosis, emergency clinicians should consider this disease in patients with prolonged postictal state after a seizure with no improvement in mental status, altered mental status with acute cerebral pathology (e.g., stroke, hypoxic brain injury), and unexplained altered mental status. Assessment includes laboratory evaluation and neuroimaging with EEG. Management includes treating life-threatening conditions, including compromise of the airway, hypoglycemia, hyponatremia, and hypo- or hyperthermia, followed by rapid cessation of the seizure activity with benzodiazepines and other antiseizure medications.

CONCLUSIONS

An understanding of the presentation and management of NCSE can assist emergency clinicians in the care of 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.

Predictors of referral for long-term EEG monitoring for Medicare beneficiaries with drug-resistant epilepsy

OBJECTIVE

For people with drug-resistant epilepsy, the use of epilepsy surgery is low despite favorable odds of seizure freedom. To better understand surgery utilization, we explored factors associated with inpatient long-term EEG monitoring (LTM), the first step of the presurgical pathway.

METHODS

Using 2001-2018 Medicare files, we identified patients with incident drug-resistant epilepsy using validated criteria of ≥2 distinct antiseizure medication (ASM) prescriptions and ≥1 drug-resistant epilepsy encounter among patients with ≥2 years pre- and ≥1 year post-diagnosis Medicare enrollment. We used multilevel logistic regression to evaluate associations between LTM and patient, provider, and geographic factors. We then analyzed neurologist-diagnosed patients to further evaluate provider/environmental characteristics.

RESULTS

Of 12 044 patients with incident drug-resistant epilepsy diagnosis identified, 2% underwent surgery. Most (68%) were diagnosed by a neurologist. In total, 19% underwent LTM near/after drug-resistant epilepsy diagnosis; another 4% only underwent LTM much prior to diagnosis. Patient factors most strongly predicting LTM were age <65 (adjusted odds ratio 1.5 [95% confidence interval 1.3-1.8]), focal epilepsy (1.6 [1.4-1.9]), psychogenic non-epileptic spells diagnosis (1.6 [1.1-2.5]) prior hospitalization (1.7, [1.5-2]), and epilepsy center proximity (1.6 [1.3-1.9]). Additional predictors included female gender, Medicare/Medicaid non-dual eligibility, certain comorbidities, physician specialties, regional neurologist density, and prior LTM. Among neurologist-diagnosed patients, neurologist <10 years from graduation, near an epilepsy center, or epilepsy-specialized increased LTM likelihood (1.5 [1.3-1.9], 2.1 [1.8-2.5], 2.6 [2.1-3.1], respectively). In this model, 37% of variation in LTM completion near/after diagnosis was explained by individual neurologist practice and/or environment rather than measurable patient factors (intraclass correlation coefficient 0.37).

SIGNIFICANCE

A small proportion of Medicare beneficiaries with drug-resistant epilepsy completed LTM, a proxy for epilepsy surgery referral. While some patient factors and access measures predicted LTM, non-patient factors explained a sizable proportion of variance in LTM completion. To increase surgery utilization, these data suggest initiatives targeting better support of neurologist referral.

Implementation and impact of a point of care electroencephalography platform in a community hospital: a cohort study

Objective

To determine the clinical and financial feasibility of implementing a poc-EEG system in a community hospital.

Design

Data from a prospective cohort displaying abnormal mentation concerning for NCSE or rhythmic movements due to potential underlying seizure necessitating EEG was collected and compared to a control group containing patient data from 2020.

Setting

A teaching community hospital with limited EEG support.

Patients

The study group consisted of patients requiring emergent EEG during hours when conventional EEG was unavailable. Control group is made up of patients who were emergently transferred for EEG during the historical period.

Interventions

Application and interpretation of Ceribell®, a poc-EEG system.

Measurement and main results

88 patients were eligible with indications for poc-EEG including hyperkinetic movements post-cardiac arrest (19%), abnormal mentation after possible seizure (46%), and unresponsive patients with concern for NCSE (35%). 21% had seizure burden on poc-EEG and 4.5% had seizure activity on follow-up EEG. A mean of 1.1 patients per month required transfer to a tertiary care center for continuous EEG. For the control period, a total of 22 patients or a mean of 2 patients per month were transferred for emergent EEG. Annually, we observed a decrease in the number of transferred patients in the post-implementation period by 10.8 (95% CI: -2.17-23.64, p = 0.1). Financial analysis of the control found the hospital system incurred a loss of $3,463.11 per patient transferred for an annual loss of $83,114.64. In the study group, this would compute to an annual loss of $45,713.05 for an overall decrease in amount lost of $37,401.59. We compared amount lost per patient between historical controls and study patients. Implementation of poc-EEG resulted in an overall decrease in annual amount lost of $37,401.59 by avoidance of transfer fees. We calculated the amount gained per patient in the study group to be $13,936.44. To cover the cost of the poc-EEG system, 8.59 patients would need to avoid transfer annually.

Conclusion

A poc-EEG system can be safely implemented in a community hospital leading to an absolute decrease in transfers to tertiary hospital. This decrease in patient transfers can cover the cost of implementing the poc-EEG system. The additional benefits from transfer avoidance include clinical benefits such as rapid appropriate treatment of seizures and avoidance of unnecessary treatment as well as negating transfer risk and keeping the patient at their local hospital.

Clinical and Electroencephalographic Predictors of Seizures and Status Epilepticus in 12,450 Critically Ill Adults: A Retrospective Cohort Study

OBJECTIVES

Status epilepticus (SE) is associated with significantly higher morbidity and mortality than isolated seizures. Our objective was to identify clinical diagnoses and rhythmic and periodic electroencephalogram patterns (RPPs) associated with SE and seizures.

DESIGN

Retrospective cohort study.

SETTING

Tertiary-care hospitals.

SUBJECTS

Twelve thousand four hundred fifty adult hospitalized patients undergoing continuous electroencephalogram (cEEG) monitoring in selected participating sites in the Critical Care EEG Monitoring Research Consortium database (February 2013 to June 2021).

INTERVENTIONS

Not applicable.

MEASUREMENTS AND MAIN RESULTS

We defined an ordinal outcome in the first 72 hours of cEEG: no seizures, isolated seizures without SE, or SE (with or without isolated seizures). Composite groups included isolated seizures or SE (AnySz) and no seizure or isolated seizures. In this cohort (mean age: 60 ± 17 yr), 1,226 patients (9.8%) had AnySz and 439 patients (3.5%) had SE. In a multivariate model, factors independently associated with SE were cardiac arrest (9.2% with SE; adjusted odds ratio, 8.8 [6.3-12.1]), clinical seizures before cEEG (5.7%; 3.3 [2.5-4.3]), brain neoplasms (3.2%; 1.6 [1.0-2.6]), lateralized periodic discharges (LPDs) (15.4%; 7.3 [5.7-9.4]), brief potentially ictal rhythmic discharges (BIRDs) (22.5%; 3.8 [2.6-5.5]), and generalized periodic discharges (GPDs) (7.2%; 2.4 [1.7-3.3]). All above variables and lateralized rhythmic delta activity (LRDA) were also associated with AnySz. Factors disproportionately increasing odds of SE over isolated seizures were cardiac arrest (7.3 [4.4-12.1]), clinical seizures (1.7 [1.3-2.4]), GPDs (2.3 [1.4-3.5]), and LPDs (1.4 [1.0-1.9]). LRDA had lower odds of SE compared with isolated seizures (0.5 [0.3-0.9]). RPP modifiers did not improve SE prediction beyond RPPs presence/absence ( p = 0.8).

CONCLUSIONS

Using the largest existing cEEG database, we identified specific predictors of SE (cardiac arrest, clinical seizures prior to cEEG, brain neoplasms, LPDs, GPDs, and BIRDs) and seizures (all previous and LRDA). These findings could be used to tailor cEEG monitoring for critically ill patients.

Identifying inpatient hospitalizations with continuous electroencephalogram monitoring from administrative data

Background

Continuous electroencephalography (cEEG) is increasingly utilized in hospitalized patients to detect and treat seizures. Epidemiologic and observational studies using administrative datasets can provide insights into the comparative and cost effectiveness of cEEG utilization. Defining patient cohorts that underwent acute inpatient cEEG from administrative datasets is limited by the lack of validated codes differentiating elective epilepsy monitoring unit (EMU) admissions from acute inpatient hospitalization with cEEG utilization. Our aim was to develop hospital administrative data-based models to identify acute inpatient admissions with cEEG monitoring and distinguish them from EMU admissions.

Methods

This was a single center retrospective cohort study of adult (≥ 18 years old) inpatient admissions with a cEEG procedure (EMU or acute inpatient) between January 2016-April 2022. The gold standard for acute inpatient cEEG vs. EMU was obtained from the local EEG recording platform. An extreme gradient boosting model was trained to classify admissions as acute inpatient cEEG vs. EMU using administrative data including demographics, diagnostic and procedure codes, and medications.

Results

There were 9,523 patients in our cohort with 10,783 hospital admissions (8.5% EMU, 91.5% acute inpatient cEEG); with average age of 59 (SD 18.2) years; 46.2% were female. The model achieved an area under the receiver operating curve of 0.92 (95% CI [0.91-0.94]) and area under the precision-recall curve of 0.99 [0.98-0.99] for classification of acute inpatient cEEG.

Conclusions

Our model has the potential to identify cEEG monitoring admissions in larger cohorts and can serve as a tool to enable large-scale, administrative data-based studies of EEG utilization.

Interrater Reliability of Expert Electroencephalographers Identifying Seizures and Rhythmic and Periodic Patterns in EEGs

BACKGROUND AND OBJECTIVES

The validity of brain monitoring using electroencephalography (EEG), particularly to guide care in patients with acute or critical illness, requires that experts can reliably identify seizures and other potentially harmful rhythmic and periodic brain activity, collectively referred to as "ictal-interictal-injury continuum" (IIIC). Previous interrater reliability (IRR) studies are limited by small samples and selection bias. This study was conducted to assess the reliability of experts in identifying IIIC.

METHODS

This prospective analysis included 30 experts with subspecialty clinical neurophysiology training from 18 institutions. Experts independently scored varying numbers of ten-second EEG segments as "seizure (SZ)," "lateralized periodic discharges (LPDs)," "generalized periodic discharges (GPDs)," "lateralized rhythmic delta activity (LRDA)," "generalized rhythmic delta activity (GRDA)," or "other." EEGs were performed for clinical indications at Massachusetts General Hospital between 2006 and 2020. Primary outcome measures were pairwise IRR (average percent agreement [PA] between pairs of experts) and majority IRR (average PA with group consensus) for each class and beyond chance agreement (κ). Secondary outcomes were calibration of expert scoring to group consensus, and latent trait analysis to investigate contributions of bias and noise to scoring variability.

RESULTS

Among 2,711 EEGs, 49% were from women, and the median (IQR) age was 55 (41) years. In total, experts scored 50,697 EEG segments; the median [range] number scored by each expert was 6,287.5 [1,002, 45,267]. Overall pairwise IRR was moderate (PA 52%, κ 42%), and majority IRR was substantial (PA 65%, κ 61%). Noise-bias analysis demonstrated that a single underlying receiver operating curve can account for most variation in experts' false-positive vs true-positive characteristics (median [range] of variance explained ([Formula: see text]): 95 [93, 98]%) and for most variation in experts' precision vs sensitivity characteristics ([Formula: see text]: 75 [59, 89]%). Thus, variation between experts is mostly attributable not to differences in expertise but rather to variation in decision thresholds.

DISCUSSION

Our results provide precise estimates of expert reliability from a large and diverse sample and a parsimonious theory to explain the origin of disagreements between experts. The results also establish a standard for how well an automated IIIC classifier must perform to match experts.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that an independent expert review reliably identifies ictal-interictal injury continuum patterns on EEG compared with expert consensus.

Hospital EEG Capability and Associations With Interhospital Transfer in Status Epilepticus

Background and Objectives

EEG is widely recommended for status epilepticus (SE) management. However, EEG access and use across the United States is poorly characterized. We aimed to evaluate changes in inpatient EEG access over time and whether availability of EEG is associated with interhospital transfers for patients hospitalized with SE.

Methods

We performed a cross-sectional study using data available in the National Inpatient Sample data set from 2012 to 2018. We identified hospitals that used continuous or routine EEG during at least 1 seizure-related hospitalization in a given year using ICD-9 and ICD-10 procedure codes and defined these hospitals as EEG capable. We examined annual change in the proportion of hospitals that were EEG capable during the study period, compared characteristics of hospitals that were EEG capable with those that were not, and fit multivariable logistic regression models to determine whether hospital EEG capability was associated with likelihood of interhospital transfer.

Results

Among 4,550 hospitals in 2018, 1,241 (27.3%) were EEG capable. Of these, 1,188 hospitals (95.7%) were in urban settings. From 2012 to 2018, the proportion of hospitals that were EEG capable increased in urban settings (30.5%-41.1%, Mann-Kendall [M-K] test p < 0.001) and decreased in rural settings (4.0%-3.2%, M-K p = 0.026). Among 130,580 patients hospitalized with SE, 80,725 (61.8%) presented directly to an EEG-capable hospital. However, EEG use during hospitalization varied from 8% to 98%. Initial admission to a hospital without EEG capability was associated with 22% increased likelihood of interhospital transfer (adjusted RR 1.22, [95% CI, 1.09-1.37]; p < 0.01). Among those hospitalized at an EEG-capable hospital, patients admitted to hospitals in the lowest quintile of EEG volume were more than 2 times more likely to undergo interhospital transfer (adjusted RR 2.22, [95% CI 1.65-2.93]; p < 0.001).

Discussion

A minority of hospitals are EEG capable yet care for most patients with SE. Inpatient EEG use, however, varies widely among EEG-capable hospitals, and lack of inpatient EEG access is associated with interhospital transfer. Given the high incidence and cost of SE, there is a need to better understand the importance and use of EEG in this patient population to further organize inpatient epilepsy systems of care to optimize outcomes.

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.

What's new on septic encephalopathy? Ten things you need to know

Sepsis associated encephalopathy (SAE) is a frequent complication of sepsis and is associated with a higher risk of short-term mortality and long-term cognitive impairment. The EEG is a sensitive complement of the clinical examination that can also detect and quantify encephalopathy and identify features with prognostic value, such as lack of reactivity. Moreover, despite their effect on outcome is still debated, the EEG is the only tool to detect non-convulsive seizures which can occur in a septic setting. Understanding the pathophysiology of SAE is fundamental to define potential therapeutic targets. Neuroinflammation plays an important role in the development of SAE and many blood and imaging biomarkers have recently shown a promising ability to distinguish SAE form non-SAE patient. In recent years, some interesting mediators of inflammation were successfully targeted in animal models, with a significant reduction in the neuroinflammation and in sepsis-induced cognitive decline. However, the complexity of the host response to sepsis currently limits the use of immunomodulation therapies in humans. Alteration in regulatory systems of cerebral blood flow, namely cerebral autoregulation (CA) and neurovascular coupling, contribute to SAE development. Nowadays, clinicians have access to different tools to assess them at the bedside and CA-based blood pressure protocols should be implemented to optimize cerebral perfusion. Its inauspicious consequences, its complex physiopathology and the lack of efficacious treatment make of SAE a highly active research subject.

Indications for continuous electroencephalographic (cEEG) monitoring: What do they tell us?

OBJECTIVE

While studies have explored clinical and EEG predictors of seizures on continuous EEG (cEEG), the role of cEEG indications as predictors of seizures has not been studied. Our study aims to fill this knowledge gap.

METHODS

We used the prospective cEEG database at Cleveland Clinic for the 2016 calendar year. Patients ≥ 18 years who underwent cEEG for the indication of altered mental status (AMS) and seizure-like events (SLE: motor or patient-reported events) were included. Baseline characteristics and EEG findings were compared between the two groups. Multivariable regression was used to compare the two groups and identify seizure detection risk factors.

RESULTS

Of 2227 patients (mean age 59.4 years) who met the inclusion criteria, 882 (50% females) underwent cEEG for AMS and 1345(51% females) for SLE. SLE patients were younger(OR: 0.988, CI: 0.98-0.99, p < 0.001), had longer monitoring(OR:1.04, CI:1.00-1.07, p = 0.033), were more likely to have epilepsy-related-breakthrough seizures(OR:25.9, CI:0.5.89-115, p < 0.001), psychogenic non-epileptic spells (OR:6.85, CI:1.60-29.3, p = 0.008), were more awake (p < 0.001) and more likely to be on anti-seizure medications(OR:1.60, CI:1.29-1.98, p < 0.001). On multivariable analysis, SLE was an independent predictor of seizure detection (OR: 2.60, CI: 1.77-3.88, p < 0.001).

SIGNIFICANCE

Our findings highlight the differences in patients undergoing cEEG for AMS vs. SLE. SLE as a cEEG indication represents an independent predictor of seizures on cEEG and, therefore, deserves special attention. Future multicenter studies are needed to validate our findings.

Quantitative artifact reduction and pharmacologic paralysis improve detection of EEG epileptiform activity in critically ill patients

OBJECTIVE

Epileptiform activity is common in critically ill patients, but movement-related artifacts-including electromyography (EMG) and myoclonus-can obscure EEG, limiting detection of epileptiform activity. We sought to determine the ability of pharmacologic paralysis and quantitative artifact reduction (AR) to improve epileptiform discharge detection.

METHODS

Retrospective analysis of patients who underwent continuous EEG monitoring with pharmacologic paralysis. Four reviewers read each patient's EEG pre- and post- both paralysis and AR, and indicated the presence of epileptiform discharges. We compared the interrater reliability (IRR) of identifying discharges at baseline, post-AR, and post-paralysis, and compared the performance of AR and paralysis according to artifact type.

RESULTS

IRR of identifying epileptiform discharges at baseline was slight (N = 30; κ = 0.10) with a trend toward increase post-AR (κ = 0.26, p = 0.053) and a significant increase post-paralysis (κ = 0.51, p = 0.001). AR was as effective as paralysis at improving IRR of identifying discharges in those with high EMG artifact (N = 15; post-AR κ = 0.63, p = 0.009; post-paralysis κ = 0.62, p = 0.006) but not with primarily myoclonus artifact (N = 15).

CONCLUSIONS

Paralysis improves detection of epileptiform activity in critically ill patients when movement-related artifact obscures EEG features. AR improves detection as much as paralysis when EMG artifact is high, but is ineffective when the primary source of artifact is myoclonus.

SIGNIFICANCE

In the appropriate setting, both AR and paralysis facilitate identification of epileptiform activity in critically ill patients.

Electrographic Seizures in the Critically Ill

Identifying and treating critically ill patients with seizures can be challenging. In this article, the authors review the available data on patient populations at risk, seizure prognostication with tools such as 2HELPS2B, electrographic seizures and the various ictal-interictal continuum patterns with their latest definitions and associated risks, ancillary testing such as imaging studies, serum biomarkers, and invasive multimodal monitoring. They also illustrate 5 different patient scenarios, their treatment and outcomes, and propose recommendations for targeted treatment of electrographic seizures in critically ill patients.

Impact of the COVID-19 Pandemic on Continuous EEG Utilization

PURPOSE

The coronavirus disease 2019 (COVID-19) has significantly impacted healthcare delivery and utilization. The aim of this article was to assess the impact of the COVID-19 pandemic on in-hospital continuous electroencephalography (cEEG) utilization and identify areas for process improvement.

METHODS

A 38-question web-based survey was distributed to site principal investigators of the Critical Care EEG Monitoring Research Consortium, and institutional contacts for the Neurodiagnostic Credentialing and Accreditation Board. The survey addressed the following aspects of cEEG utilization: (1) general center characteristics, (2) cEEG utilization and review, (3) staffing and workflow, and (4) health impact on EEG technologists.

RESULTS

The survey was open from June 12, 2020 to June 30, 2020 and distributed to 174 centers with 79 responses (45.4%). Forty centers were located in COVID-19 hotspots. Fifty-seven centers (72.1%) reported cEEG volume reduction. Centers in the Northeast were most likely to report cEEG volume reduction (odds ratio [OR] 7.19 [1.53-33.83]; P = 0.012). Additionally, centers reporting decrease in outside hospital transfers reported cEEG volume reduction; OR 21.67 [4.57-102.81]; P ≤ 0.0001. Twenty-six centers (32.91%) reported reduction in EEG technologist coverage. Eighteen centers had personal protective equipment shortages for EEG technologists. Technologists at these centers were more likely to quarantine for suspected or confirmed COVID-19; OR 3.14 [1.01-9.63]; P = 0.058.

CONCLUSIONS

There has been a widespread reduction in cEEG volume during the pandemic. Given the anticipated duration of the pandemic and the importance of cEEG in managing hospitalized patients, methods to optimize use need to be prioritized to provide optimal care. Because the survey provides a cross-sectional assessment, follow-up studies can determine the long-term impact of the pandemic on cEEG utilization.

Repetitive Electroencephalography as Biomarker for the Prediction of Survival in Patients with Post-Hypoxic Encephalopathy

Predicting survival in patients with post-hypoxic encephalopathy (HE) after cardiopulmonary resuscitation is a challenging aspect of modern neurocritical care. Here, continuous electroencephalography (cEEG) has been established as the gold standard for neurophysiological outcome prediction. Unfortunately, cEEG is not comprehensively available, especially in rural regions and developing countries. The objective of this monocentric study was to investigate the predictive properties of repetitive EEGs (rEEGs) with respect to 12-month survival based on data for 199 adult patients with HE, using log-rank and multivariate Cox regression analysis (MCRA). A total number of 59 patients (29.6%) received more than one EEG during the first 14 days of acute neurocritical care. These patients were analyzed for the presence of and changes in specific EEG patterns that have been shown to be associated with favorable or poor outcomes in HE. Based on MCRA, an initially normal amplitude with secondary low-voltage EEG remained as the only significant predictor for an unfavorable outcome, whereas all other relevant parameters identified by univariate analysis remained non-significant in the model. In conclusion, rEEG during early neurocritical care may help to assess the prognosis of HE patients if cEEG is not available.

Epileptiform Abnormalities in Acute Ischemic Stroke: Impact on Clinical Management and Outcomes

PURPOSE

Studies examining seizures (Szs) and epileptiform abnormalities (EAs) using continuous EEG in acute ischemic stroke (AIS) are limited. Therefore, we aimed to describe the prevalence of Sz and EA in AIS, its impact on anti-Sz drug management, and association with discharge outcomes.

METHODS

The study included 132 patients with AIS who underwent continuous EEG monitoring >6 hours. Continuous EEG was reviewed for background, Sz and EA (lateralized periodic discharges [LPD], generalized periodic discharges, lateralized rhythmic delta activity, and sporadic epileptiform discharges). Relevant clinical, demographic, and imaging factors were abstracted to identify risk factors for Sz and EA. Outcomes included all-cause mortality, functional outcome at discharge (good outcome as modified Rankin scale of 0-2 and poor outcome as modified Rankin scale of 3-6) and changes to anti-Sz drugs (escalation or de-escalation).

RESULTS

The frequency of Sz was 7.6%, and EA was 37.9%. Patients with Sz or EA were more likely to have cortical involvement (84.6% vs. 67.5% P = 0.028). Among the EAs, the presence of LPD was associated with an increased risk of Sz (25.9% in LPD vs. 2.9% without LPD, P = 0.001). Overall, 21.2% patients had anti-Sz drug changes because of continuous EEG findings, 16.7% escalation and 4.5% de-escalation. The presence of EA or Sz was not associated with in-hospital mortality or discharge functional outcomes.

CONCLUSIONS

Despite the high incidence of EA, the rate of Sz in AIS is relatively lower and is associated with the presence of LPDs. These continuous EEG findings resulted in anti-Sz drug changes in one-fifth of the cohort. Epileptiform abnormality and Sz did not affect mortality or discharge functional outcomes.

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.

Use of Continuous EEG Monitoring and Short-Term Outcomes in Critically Ill Children

This study aimed to compare short-term outcomes at pediatric intensive care unit (PICU) discharge in critically ill children with and without continuous electroencephalography (cEEG) monitoring. We retrospectively compared 234 patients who underwent cEEG with 2294 patients without cEEG. Propensity score matching was used to compare patients with seizures and status epilepticus between cEEG and historical cohorts. The EEG cohort had higher in-hospital mortality, worse Pediatric Cerebral Performance Category (PCPC) scores, and greater PCPC decline at discharge. In patients with status epilepticus, the PCPC decline was higher in the cEEG cohort. PCPC decline at PICU discharge was associated with cEEG monitoring in patients with status epilepticus.

The State of Specialized Epilepsy Care in the States: Increased Access, New Tools, but the Same Dismal Underutilization of Epilepsy Surgery

United States Epilepsy Center Characteristics: A Data Analysis From the National Association of Epilepsy Centers

Ostendorf AP, Ahrens SM, Lado FA, et al. Neurology. 2022;98(5):e449-e458. doi:10.1212/WNL.0000000000013130.

Background and objectives:

Patients with drug-resistant epilepsy (DRE) may benefit from specialized testing and treatments to better control seizures and improve quality of life. Most evaluations and procedures for DRE in the United States are performed at epilepsy centers accredited by the National Association of Epilepsy Centers (NAEC). On an annual basis, the NAEC collects data from accredited epilepsy centers on hospital-based epilepsy monitoring unit (EMU) size and admissions, diagnostic testing, surgeries, and other services. This article highlights trends in epilepsy center services from 2012 through 2019.

Methods:

We analyzed data reported in 2012, 2016, and 2019 from all level 3 and level 4 NAEC accredited epilepsy centers. Data were described using frequency for categorical variables and median for continuous variables and were analyzed by center level and center population category. EMU beds, EMU admissions, epileptologists, and aggregate procedure volumes were also described using rates per population per year.

Results:

During the period studied, the number of NAEC accredited centers increased from 161 to 256, with the largest increases in adult- and pediatric-only centers. Growth in EMU admissions (41%), EMU beds (26%), and epileptologists (109%) per population occurred. Access to specialized testing and services broadly expanded. The largest growth in procedure volumes occurred in laser interstitial thermal therapy (LiTT) (61%), responsive neurostimulation (RNS) implantations (114%), and intracranial monitoring without resection (152%) over the study period. Corpus callosotomies and vagus nerve stimulator (VNS) implantations decreased (−12.8% and −2.4%, respectively), while growth in temporal lobectomies (5.9%), extratemporal resections (11.9%), and hemispherectomies/otomies (13.1%) lagged center growth (59%), leading to a decrease in median volumes of these procedures per center.

Discussion:

During the study period, the availability of specialty epilepsy care in the United States improved as the NAEC implemented its accreditation program. Surgical case complexity increased while aggregate surgical volume remained stable or declined across most procedure types, with a corresponding decline in cases per center. This article describes recent data trends and current state of resources and practice across NAEC member centers and identifies several future directions for driving systematic improvements in epilepsy care.

Exploring Trends in Neuromonitoring Use in a General Pediatric ICU: The Need for Standardized Guidance

Neuromonitoring has become more standardized in adult neurocritical care, but the utility of different neuromonitoring modalities in children remains debated. We aimed to describe the use of neuromonitoring in critically ill children with and without primary neurological diseases. We conducted a retrospective review of patients admitted to a 32-bed, non-cardiac PICU during a 12-month period. Neuro-imaging, electroencephalogram (EEG), cerebral oximetry (NIRS), automated pupillometry, transcranial doppler (TCD), intracranial pressure (ICP) monitoring, brain tissue oxygenation (PbtO2), primary diagnosis, and outcome were extracted. Neuromonitoring use by primary diagnosis and associations with outcome were observed. Of 1946 patients, 420 received neuro-imaging or neuromonitoring. Primary non-neurological diagnoses most frequently receiving neuromonitoring were respiratory, hematologic/oncologic, gastrointestinal/liver, and infectious/inflammatory. The most frequently used technologies among non-neurological diagnoses were neuro-imaging, EEG, pupillometry, and NIRS. In the multivariate analysis, pupillometry use was associated with mortality, and EEG, NIRS, and neuro-imaging use were associated with disability. Frequencies of TCD and PbtO2 use were too small for analysis. Neuromonitoring is prevalent among various diagnoses in the PICU, without clear benefit on outcomes when used in an ad hoc fashion. We need standard guidance around who, when, and how neuromonitoring should be applied to improve the care of critically ill children.

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.

Seizure Detection in Continuous Inpatient EEG: A Comparison of Human vs Automated Review

BACKGROUND AND OBJECTIVES

The aim of this work was to test the accuracy of Persyst commercially available automated seizure detection in critical care EEG by comparing automated seizure detections to human review in a manually reviewed cohort and on a large scale.

METHODS

Automated seizure detections (Persyst versions 12 and 13) were compared to human review in a pilot cohort of 229 seizures from 85 EEG records and then in an expanded cohort of 7,924 EEG records. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for individual seizures (pilot cohort) and for entire records (pilot and expanded cohorts). We assessed EEG features associated with the accuracy of automated seizure detections.

RESULTS

In the pilot cohort, accuracy of automated detection for individual seizures was modest (sensitivity 0.50, PPV 0.60). At the record level (did the recording contain seizures or not?), sensitivity was higher (pilot cohort 0.78, expanded cohort 0.91), PPV was low (pilot cohort 0.40, expanded cohort 0.08), and NPV was high (pilot cohort 0.88, expanded cohort 0.97). Different software versions (version 12 vs 13) performed similarly. Sensitivity was higher for records containing focal-onset seizures compared to generalized-onset seizures (0.93 vs 0.85, p = 0.012).

DISCUSSION

In critical care continuous EEG recordings, automated detection of individual seizures had rates of both false negatives and false positives that bring into question its utility as a seizure alarm in clinical practice. At the level of entire EEG records, the absence of automated detections accurately predicted EEG records without true seizures. The true value of Persyst automated seizure detection appears to lie in triaging of low-risk EEGs.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that an automated seizure detection program cannot accurately identify EEG records that contain seizures.

Continuous versus routine EEG in patients after cardiac arrest-Analysis of a randomized controlled trial (CERTA) - RESUS-D-22-00369

BACKGROUND

Electroencephalography (EEG) is essential to assess prognosis in patients after cardiac arrest (CA). Use of continuous EEG (cEEG) is increasing in critically-ill patients, but it is more resource-consuming than routine EEG (rEEG). Observational studies did not show a major impact of cEEG versus rEEG on outcome, but randomized studies are lacking.

METHODS

We analyzed data of the CERTA trial (NCT03129438), including comatose adults after CA undergoing cEEG (30-48 hours) or two rEEG (20-30 minutes each). We explored correlations between recording EEG type and mortality (primary outcome), or Cerebral Performance Categories (CPC, secondary outcome), assessed blindly at 6 months, using uni- and multivariable analyses (adjusting for other prognostic variables showing some imbalance across groups).

RESULTS

We analyzed 112 adults (52 underwent rEEG, 60 cEEG,); 31 (27.7%) were women; 68 (60.7%) patients died. In univariate analysis, mortality (rEEG 59%, cEEG 65%, p=0.318) and good outcome (CPC 1-2; rEEG 33%, cEEG 27%, p=0.247) were comparable across EEG groups. This did not change after multiple logistic regressions, adjusting for shockable rhythm, time to return of spontaneous circulation, serum neuron-specific enolase, EEG background reactivity, regarding mortality (rEEG vs cEEG: OR 1.60, 95% CI 0.43 - 5.83, p=0.477), and good outcome (OR 0.51, 95% CI 0.14 - 1.90, p=0.318).

CONCLUSION

This analysis suggests that cEEG or repeated rEEG are related to comparable outcomes of comatose patients after CA. Pending a prospective, large randomized trial, this finding does not support the routine use of cEEG for prognostication in this setting. Trial registration Continuous EEG Randomized Trial in Adults (CERTA); NCT03129438; July 25, 2019.

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.

Status epilepticus: review on diagnosis, monitoring and treatment

Status epilepticus (SE) is a frequent neurological emergency associated with high morbidity and mortality. According to the new ILAE 2015 definition, SE results either from the failure of the mechanisms responsible for seizure termination or initiation, leading to abnormally prolonged seizures. The definition has different time points for convulsive, focal and absence SE. Time is brain. There are changes in synaptic receptors leading to a more proconvulsant state and increased risk of brain lesion and sequelae with long duration. Management of SE must include three pillars: stop seizures, stabilize patients to avoid secondary lesions and treat underlying causes. Convulsive SE is defined after 5 minutes and is a major emergency. Benzodiazepines are the initial treatment, and should be given fast and an adequate dose. Phenytoin/fosphenytoin, levetiracetam and valproic acid are evidence choices for second line treatment. If SE persists, anesthetic drugs are probably the best option for third line treatment, despite lack of evidence. Midazolam is usually the best initial choice and barbiturates should be considered for refractory cases. Nonconvulsive status epilepticus has a similar initial approach, with benzodiazepines and second line intravenous (IV) agents, but after that, aggressiveness should be balanced considering risk of lesion due to seizures and medical complications caused by aggressive treatment. Usually, the best approach is the use of sequential IV antiepileptic drugs (oral/tube are options if IV options are not available). EEG monitoring is crucial for diagnosis of nonconvulsive SE, after initial control of convulsive SE and treatment control. Institutional protocols are advised to improve care.

Risk factors that predict delayed seizure detection on continuous electroencephalogram (cEEG) in a large sample size of critically ill patients

OBJECTIVE

Majority of seizures are detected within 24 hours on continuous EEG (cEEG). Some patients have delayed seizure detection after 24 hours. The purpose of this research was to identify risk factors that predict delayed seizure detection and to determine optimal cEEG duration for various patient subpopulations.

METHODS

We retrospectively identified all patients ≥18 years of age who underwent cEEG at Cleveland clinic during calendar year 2016. Clinical and EEG data for all patients and time to seizure detection for seizure patients were collected.

RESULTS

Twenty-four hundred and two patients met inclusion criteria. Of these, 316 (13.2%) had subclinical seizures. Sixty-five (20.6%) patients had delayed seizures detection after 24 hours. Seizure detection increased linearly till 36 hours of monitoring, and odds of seizure detection increased by 46% for every additional day of monitoring. Delayed seizure risk factors included stupor (13.2% after 48 hours, P = .031), lethargy (25.9%, P = .013), lateralized (LPDs) (27.7%, P = .029) or generalized periodic discharges (GPDs) (33.3%, P = .022), acute brain insults (25.5%, P = .036), brain bleeds (32.8%, P = .014), especially multiple concomitant bleeds (61.1%, P < .001), altered mental status (34.7%, P = .001) as primary cEEG indication, and use of antiseizure medications (27.8%, P < .001) at cEEG initiation.

SIGNIFICANCE

Given the linear seizure detection trend, 36 hours of standard monitoring appears more optimal than 24 hours especially for high-risk patients. For awake patients without epileptiform discharges, <24 hours of monitoring appears sufficient. Previous studies have shown that coma and LPDs predict delayed seizure detection. We found that stupor and lethargy were also associated with delayed seizure detection. LPDs and GPDs were associated with delayed seizures. Other delayed seizure risk factors included acute brain insults, brain bleeds especially multiple concomitant bleeds, altered mental status as primary cEEG indication, and use of ASMs at cEEG initiation. Longer cEEG (≥48 hours) is suggested for these high-risk patients.

Impact of ICD-9 to ICD-10 Coding Transition on Prevalence Trends in Neurology

Objective

To determine the effect of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) to International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) coding transition on the point prevalence and longitudinal trends of 16 neurologic diagnoses.

Methods

We used 2014-2017 data from the National Inpatient Sample to identify hospitalizations with one of 16 common neurologic diagnoses. We used published ICD-9-CM codes to identify hospitalizations from January 1, 2014, to September 30, 2015, and used the Agency for Healthcare Research and Quality's MapIt tool to convert them to equivalent ICD-10-CM codes for October 1, 2015-December 31, 2017. We compared the prevalence of each diagnosis before vs after the ICD coding transition using logistic regression and used interrupted time series regression to model the longitudinal change in disease prevalence across time.

Results

The average monthly prevalence of subarachnoid hemorrhage was stable before the coding transition (average monthly increase of 4.32 admissions, 99.7% confidence interval [CI]: -8.38 to 17.01) but increased after the coding transition (average monthly increase of 24.32 admissions, 99.7% CI: 15.71-32.93). Otherwise, there were no significant differences in the longitudinal rate of change in disease prevalence over time between ICD-9-CM and ICD-10-CM. Six of 16 neurologic diagnoses (37.5%) experienced significant changes in cross-sectional prevalence during the coding transition, most notably for status epilepticus (odds ratio 0.30, 99.7% CI: 0.26-0.34).

Conclusions

The transition from ICD-9-CM to ICD-10-CM coding affects prevalence estimates for status epilepticus and other neurologic disorders, a potential source of bias for future longitudinal neurologic studies. Studies should limit to 1 coding system or use interrupted time series models to adjust for changes in coding patterns until new neurology-specific ICD-9 to ICD-10 conversion maps can be developed.

Using electronic health data to explore effectiveness of ICU EEG and anti-seizure treatment

Objectives

The purpose of this study was to examine critical care continuous electroencephalography (cEEG) utilization and downstream anti‐seizure treatment patterns, their association with outcomes, and generate hypotheses for larger comparative effectiveness studies of cEEG‐guided interventions.

Methods

Single‐center retrospective study of critically ill patients (n = 14,523, age ≥18 years). Exposure defined as ≥24 h of cEEG and subsequent anti‐seizure medication (ASM) escalation, with or without concomitant anesthetic. Exposure window was the first 7 days of admission. Primary outcome was in‐hospital mortality. Multivariable analysis was performed using penalized logistic regression.

Results

One thousand and seventy‐three patients underwent ≥24 h of cEEG within 7 days of admission. After adjusting for disease severity, ≥24 h of cEEG followed by ASM escalation in patients not on anesthetics (n = 239) was associated with lower in‐hospital mortality (OR 0.76 [0.53–1.07]), though the finding did not reach significance. ASM escalation with concomitant anesthetic use (n = 484) showed higher odds for mortality (OR 1.41 [1.03–1.94]). In the seizures/status epilepticus subgroup, post cEEG ASM escalation without anesthetics showed lower odds for mortality (OR 0.43 [0.23–0.74]). Within the same subgroup, ASM escalation with concomitant anesthetic use showed higher odds for mortality (OR 1.34 [0.92–1.91]) though not significant.

Interpretation

Based on our findings we propose the following hypotheses for larger comparative effectiveness studies investigating the direct causal effect of cEEG‐guided treatment on outcomes: (1) cEEG‐guided ASM escalation may improve outcomes in critically ill patients with seizures; (2) cEEG‐guided treatment with combination of ASMs and anesthetics may not improve outcomes in all critically ill patients.

Cerebral and systemic hemodynamic effect of recurring seizures

The increase in neuronal activity induced by a single seizure is supported by a rise in the cerebral blood flow and tissue oxygenation, a mechanism called neurovascular coupling (NVC). Whether cerebral and systemic hemodynamics are able to match neuronal activity during recurring seizures is unclear, as data from rodent models are at odds with human studies. In order to clarify this issue, we used an invasive brain and systemic monitoring to study the effects of chemically induced non-convulsive seizures in sheep. Despite an increase in neuronal activity as seizures repeat (Spearman’s ρ coefficient 0.31, P < 0.001), ictal variations of cerebral blood flow remained stable while it progressively increased in the inter-ictal intervals (ρ = 0.06, P = 0.44 and ρ = 0.22; P = 0.008). We also observed a progressive reduction in the inter-ictal brain tissue oxygenation (ρ =  − 0.18; P = 0.04), suggesting that NVC was unable to compensate for the metabolic demand of these closely repeating seizures. At the systemic level, there was a progressive reduction in blood pressure and a progressive rise in cardiac output (ρ =  − 0.22; P = 0.01 and ρ = 0.22; P = 0.01, respectively), suggesting seizure-induced autonomic dysfunction.

Atrial fibrillation in critically ill patients who received prolonged mechanical ventilation: a nationwide inpatient report

BACKGROUND/AIMS

To evaluate temporal trends of atrial fibrillation (AF) prevalence in critically ill patients who received prolonged mechanical ventilation (MV) in the United States.

METHODS

We used the 2008 to 2014 National Inpatient Sample to compute the weighted prevalence of AF among hospitalized adult patients on prolonged MV. We used multivariable-adjusted models to evaluate the association of AF with clinical factors, in-hospital mortality, hospitalization cost, and length of stay (LOS).

RESULTS

We identified 2,578,165 patients who received prolonged MV (21.27% of AF patients). The prevalence of AF increased from 14.63% in 2008 to 24.43% in 2014 (p for trend < 0.0001). Amongst different phenotypes of critically ill patients, the prevalence of AF increased in patients with severe sepsis, asthma exacerbation, congestive heart failure exacerbation, acute stroke, and cardiac arrest. Older age, male sex, white race, medicare access, higher income, urban teaching hospital setting, and Western region were associated with a higher prevalence of AF. AF in critical illness was a risk factor for in-hospital death (odds ratio, 1.13; 95% confidence interval, 1.11 to 1.15), but in-hospital mortality in critically ill patients with AF decreased from 11.6% to 8.3%. AF was linked to prolonged LOS (2%, p < 0.0001) and high hospitalization cost (4%, p < 0.0001). LOS (-1%, p < 0.0001) and hospitalization cost (-4%, p < 0.0001) decreased yearly.

CONCLUSION

The prevalence of comorbid AF is increasing, particularly in older patients. AF may lead to poorer prognosis, and high-quality intensive care is imperative for this population.

Diagnosis and Management of Status Epilepticus

Seizures are among the most common neurological presentations to the emergency room. They present on a spectrum of severity from isolated new-onset seizures to acute repetitive seizures and, in severe cases, status epilepticus. The latter is the most serious, as it is associated with high morbidity and mortality. Prompt recognition and treatment of both seizure activity and associated acute systemic complications are essential to improve the overall outcome of these patients. The purpose of this review is to provide the current viewpoint on the diagnostic evaluation and pharmacological management of patients presenting with status epilepticus, and the common associated systemic complications.

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.

Continuous Electroencephalogram and Antiseizure Medication Use in an International Pediatric Traumatic Brain Injury Population

BACKGROUND

Electrographic seizures are frequent and associated with worse outcomes following traumatic brain injury (TBI). Despite this, the use of continuous electroencephalogram (cEEG) remains low. Our study describes cEEG usage and treatment dosing antiseizure medications (ASMs) in an international pediatric TBI population, hypothesizing that children monitored with cEEG have an increased rate of treatment ASMs because of electrographic seizure detection, compared with children who are not monitored with cEEG.

METHODS

This subanalysis of the TBI cohort of the international PANGEA study included children, 7 days to 17 years of age, with acute neurological insults admitted to pediatric intensive care units. We analyzed demographics, injury severity, and therapies including prophylactic or treatment ASMs. We evaluated the relationships between cEEG use, seizure frequency, and receipt of treatment ASMs. [Formula: see text] or Fisher's exact test was used to analyze categorical variables, and the Kruskal-Wallis or Mann-Whitney U-test was used for continuous variables. Multivariable analysis for treatment ASM use was performed using logistic regression.

RESULTS

One hundred-twenty-three of 174 patients with TBI were included. Twenty-seven patients (21.9%) underwent cEEG at any point during pediatric intensive care unit admission. Preexisting seizure disorder (18.2% vs. 2.3%, p = 0.014) and neuromuscular blockade use (52.4% vs. 24.1%, p = 0.011) were more frequently observed in the group monitored on cEEG when compared with those that were not. Presenting median Glasgow Coma Scale score was worse in the cEEG group (7 vs. 9, p = 0.044). There was no significant difference in age, use of intracranial pressure monitoring, or hyperosmolar therapy between the cEEG monitored and nonmonitored groups. Patients who were monitored on cEEG were more likely to receive a treatment dose ASM than those without cEEG monitoring (66.7% vs. 28.1%, p = 0.0002). When compared with those without treatment ASM, the treatment ASM group had more electrographic seizures on their first electroencephalogram following injury (51.6% vs. 4%, p = 0.0001) and more clinical seizures (55.8% vs. 0%, p < 0.0001).

CONCLUSIONS

Children monitored with cEEG after TBI have an increased prescription of treatment ASMs and clinical and electrographic seizures. The increased rate of treatment ASMs in the cEEG group may indicate increased recognition of electrographic seizures.

Association of Standard Electroencephalography Findings With Mortality and Command Following in Mechanically Ventilated Patients Remaining Unresponsive After Sedation Interruption

CONTEXT

Delayed awakening after sedation interruption is frequent in critically ill patients receiving mechanical ventilation.

OBJECTIVES

We aimed to investigate the association of standard electroencephalography with mortality and command following in this setting.

DESIGN, SETTING, AND PATIENTS

In a single-center study, we retrospectively analyzed standard electroencephalography performed in consecutive mechanically ventilated patients remaining unresponsive (comatose/stuporous or unable to follow commands) after sedation interruption. Standard electroencephalography parameters (background activity, continuity, and reactivity) were reassessed by neurophysiologists, blinded to patients' outcome. Patients were categorized during follow-up into three groups based on their best examination as: 1) command following, 2) unresponsive, or 3) deceased. Cause-specific models were used to identify independent standard electroencephalography parameters associated with main outcomes, that is, mortality and command following. Follow-up was right-censored 30 days after standard electroencephalography.

MEASUREMENTS AND MAIN RESULTS

Main standard electroencephalography parameters recorded in 121 unresponsive patients (median time between sedation interruption and standard electroencephalography: 2 d [interquartile range, 1-4 d]) consisted of a background frequency greater than 4 Hz in 71 (59%), a discontinuous background in 19 (16%), and a preserved reactivity in 98/120 (82%) patients. At 30 days, 66 patients (55%) were command following, nine (7%) were unresponsive, and 46 (38%) had died. In a multivariate analysis adjusted for nonneurologic organ failure, a reactive standard electroencephalography with a background frequency greater than 4 Hz was independently associated with a reduced risk of death (cause-specific hazard ratio, 0.38; CI 95%, 0.16-0.9). By contrast, none of the standard electroencephalography parameters were independently associated with command following. Sensitivity analyses conducted after exclusion of 29 patients with hypoxic brain injury revealed similar findings.

CONCLUSIONS

In patients remaining unresponsive after sedation interruption, a pattern consisting of a reactive standard electroencephalography with a background frequency greater than 4 Hz was associated with decreased odds of death. None of the standard electroencephalography parameters were independently associated with command following.

Delayed awakening in neurocritical care

Delayed awakening is defined as a persistent disorder of arousal or consciousness 48 to 72h after sedation interruption in critically ill patients. Delayed awakening is either a component of coma or delirium. It results in longer hospital stays and increased mortality. It is therefore a diagnostic, therapeutic and prognostic emergency. In severe brain injured patients, delayed awakening may be related to the primary neurological injury or to secondary systemic insults related to organ failure associated with intensive care. In the present review, we propose diagnostic, therapeutic and prognostic algorithms for managing delayed awaking in neuro-ICU brain injured patients.