Clinical and electroencephalographic correlates of acute encephalopathy

A novel nomogram for predicting the prognosis of critically ill patients with EEG patterns exhibiting stimulus-induced rhythmic, periodic, or ictal discharges

OBJECTIVES

To explore the factors associated with poor prognosis in critically ill patients with Electroencephalogram (EEG) patterns exhibiting stimulus-induced rhythmic, periodic, or ictal discharges (SIRPIDs), and to construct a prognostic prediction model.

METHODS

This study included a total of 53 critically ill patients with EEG patterns exhibiting SIRPIDs who were admitted to the First Affiliated Hospital of Chongqing Medical University from May 2023 to March 2024. Patients were divided into two groups based on their Modified Rankin Scale (mRS) scores at discharge: good prognosis group (0-3 points) and poor prognosis group (4-6 points). Retrospective analyses were performed on the clinical and EEG parameters of patients in both groups. Logistic regression analysis was applied to identify the risk factors related to poor prognosis in critically ill patients with EEG patterns exhibiting SIRPIDs; a risk prediction model for poor prognosis was constructed, along with an individualized predictive nomogram model, and the predictive performance and consistency of the model were evaluated.

RESULTS

Multivariate logistic regression analysis revealed that APACHE II score (OR=1.217, 95 %CI=1.030∼1.438), slow frequency bands or no obvious brain electrical activity (OR=8.720, 95 %CI=1.220∼62.313), and no sleep waveforms (OR=9.813, 95 %CI=1.371∼70.223) were independent risk factors for poor prognosis in patients. A regression model established based on multivariate logistic regression analysis had an area under the curve of 0.902. The model's accuracy was 90.60 %, with a sensitivity of 92.86 % and a specificity of 89.70 %. The nomogram model, after internal validation, showed a concordance index of 0.904.

CONCLUSIONS

A high APACHE II score, EEG patterns with slow frequency bands or no obvious brain electrical activity, and no sleep waveforms were independent risk factors for poor prognosis in patients with SIRPIDs. The nomogram model constructed based on these factors had a favorably high level of accuracy in predicting the risk of poor prognosis and held certain reference and application value for clinical neurofunctional assessment and prognostic determination.

Incidence of seizures in ICU patients with diffuse encephalopathy and its predictors

Encephalopathy is a diffuse brain dysfunction that results from systemic disorder. Patients with diffuse encephalopathy are at risk of developing clinical and electrographic seizures. The aim of this study is to assess the prevalence of electrographic seizures in a setting of encephalopathy and the clinical and electroencephalogram predictors. We retrospectively reviewed all continuous electroencephalograms done between 2019 and 2022. Continuous electroencephalograms with diffuse encephalopathy were included in the study. A total of 128 patients with diffuse encephalopathy were included in this study. Patients' ages ranged from 18 to 96 years old with a mean age of 55.3 ± 19.2 years old. Nine out of 128 patients had seizures with an incidence of 7%. Sixty-six point six percent were nonconvulsive electrographic seizures. Fourteen point three percent of the female patients with diffuse encephalopathy had seizures as compared to none of the male patients (P = .002). Also, 12% of patients with a history of epilepsy experienced seizures versus 5.8% of patients without this history (P = .049). Among electrographic features, 25% of patients with delta background had seizures versus 2.3% of the other patients (P = .048). Likewise, 90% of patients with periodic discharges developed seizures in comparison with none of the patients without (P = .001). Seizures are seen in 7% of patients with diffuse encephalopathy. Female gender, past history of epilepsy, delta background and periodic discharges are significant predictors of seizure development in patients with diffuse encephalopathy.

Early Electroencephalographic Features Predicting Cerebral Physiology and Functional Outcomes After Pediatric Traumatic Brain Injury

BACKGROUND

We investigated whether early electroencephalographic features predicted intracranial pressure (ICP), cerebrovascular pressure reactivity, brain tissue oxygenation, and functional outcomes in patients with pediatric traumatic brain injury (TBI).

METHODS

This was a retrospective analysis of a prospective data set of 63 patients with pediatric TBI. Electroencephalographic features were collected in the first 24 h of recording to predict values of ICP, pressure reactivity index (PRx), and brain tissue oxygenation (PbtO2) through the initial 7 days of critical care monitoring, in addition to Glasgow Outcome Scale Extended-Pediatric Revision (GOSE-Peds) scores at 12 months. Electroencephalographic features were averaged over all surface electrodes and included seizures, interictal epileptiform discharges, suppression percentage, complexity, the alpha/delta power ratio, and both absolute asymmetry indices and power in beta (13-20 Hz), alpha (8-13 Hz), theta (4-7 Hz) and delta (0-4 Hz) bands. Demographic data and injury severity scores, such as the Glasgow Coma Scale (GCS) and Pediatric Risk of Mortality III (PRISM III) scores, at presentation were also assessed. Univariate and multiple linear regression with guided stepwise variable selection was used to find combinations of risk factors that best explain variability in ICP, PRx, PbtO2, and GOSE-Peds values, and best fit models were applied to pediatric age strata. We hypothesized that suppression percentage and the alpha/delta power ratio in the first 24 h of recording predict ICP, PRx, PbtO2, and GOSE-Peds values.

RESULTS

Best subset model selection identified that increased suppression percentage and PRISM III scores predicted increased ICP (R2 = 79%, Akaike information criterion [AIC] = 332.30, root mean square error [RMSE] = 6.62), with suppression percentages < 5% (slope =  - 5687.0, p = 0.0001) and ≥ 45% (slope = 9825.9, p = 0.0000) being predictive of dose of intracranial hypertension. When accounting for age and GCS score, increased suppression percentage predicted increased PRx values, suggestive of inefficient cerebrovascular pressure reactivity (R2 = 53%, AIC = 3.93, RMSE = 0.23), with suppression percentages ≥ 5% (p = 0.0033) and ≥ 45% (p = 0.0027) being predictive of median PRx values ≥ 0.3. Lower GCS scores, the presence of seizures, and increased suppression percentages each were independently associated with higher GOSE-Peds scores (R2 = 52%, AIC = 194.04, RMSE = 1.58), suggestive of unfavorable outcomes, with suppression percentages ≥ 5% (p = 0.0005) and ≥ 45% (p = 0.0000) being predictive of GOSE-Peds scores ≥ 5. At the univariate level, no electroencephalographic or clinical feature was associated with differences in PbtO2 values.

CONCLUSIONS

Increased electroencephalographic suppression percentage on the initial day of monitoring may identify patients with pediatric TBI at risk of increased ICP, inefficient cerebrovascular pressure reactivity, and unfavorable outcomes.

Quantitative EEG signatures of delirium and coma in mechanically ventilated ICU patients

OBJECTIVE

To identify quantitative electroencephalography (EEG)-based indicators of delirium or coma in mechanically ventilated patients.

METHODS

We prospectively enrolled 28 mechanically ventilated intensive care unit (ICU) patients to undergo 24-hour continuous EEG, 25 of whom completed the study. We assessed patients twice daily using the Richmond Agitation-Sedation Scale (RASS) and Confusion Assessment Method for the ICU (CAM-ICU). We evaluated the spectral profile, regional connectivity and complexity of 5-minute EEG segments after each assessment. We used penalized regression to select EEG metrics associated with delirium or coma, and compared mixed-effects models predicting delirium with and without the selected EEG metrics.

RESULTS

Delta variability, high-beta variability, relative theta power, and relative alpha power contributed independently to EEG-based identification of delirium or coma. A model with these metrics achieved better prediction of delirium or coma than a model with clinical variables alone (Akaike Information Criterion: 36 vs 43, p = 0.006 by likelihood ratio test). The area under the receiver operating characteristic curve for an ad hoc hypothetical delirium score using these metrics was 0.94 (95%CI 0.83-0.99).

CONCLUSIONS

We identified four EEG metrics that, in combination, provided excellent discrimination between delirious/comatose and non-delirious mechanically ventilated ICU patients.

SIGNIFICANCE

Our findings give insight to neurophysiologic changes underlying delirium and provide a basis for pragmatic, EEG-based delirium monitoring technology.

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.

Retrospective Analysis of EEG in Patients With COVID-19: EEG Recording in Acute and Follow-up Phases

Background. Interest in electroencephalographic (EEG) coronavirus disease 2019 (COVID-19) findings has been growing, especially in the search for a specific-features EEG of encephalopathy. Methods. We made a retrospective analysis of 29 EEGs recorded in 15 patients with COVID-19 and neurological symptoms. We classified the EEGs as "Acute EEG" and "follow-up EEG." We did a statistical analysis between voltage and respiratory status of the patient, stay or not in the intensive care unit (ICU), days of stay in the ICU, sedative drugs, pharmacological treatment, type of symptoms predominating, and outcome. Results. We found EEG abnormalities in all patients studied. We observed the amplitude of background <20 µV at 93% of "acute EEG," versus only 21.4% of "follow-up EEG." The average voltage went from 12.33 ± 5.09 µV in the acute EEGs to 32.8 ± 20.13 µV in the follow-up EEGs. A total of 60% of acute EEGs showed an intermittent focal rhythmic. We have not found a statistically significant association between voltage of acute EEG and nonneurological clinical status (including respiratory) that may interfere with the EEG findings. Conclusions. Nonspecific diffuse slowing EEG pattern in COVID-19 is the most common finding reported, but we found in addition to that, as a distinctive finding, low voltage EEG, that could explain the low prevalence of epileptic activity published in these patients. A metabolic/hypoxic mechanism seems unlikely on the basis of our EEG findings. This pattern in other etiologies is reminiscent of severe encephalopathy states associated with poor prognosis. However, an unreactive low voltage pattern in COVID-19 patients is not necessarily related to poor prognosis.

Critical care EEG standardized nomenclature in clinical practice: Strengths, limitations, and outlook on the example of prognostication after cardiac arrest

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Optimal use of the ACNS nomenclature implies integration of clinical information.

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Knowledge of pathophysiological mechanisms of EEG patterns may help interpretation.

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Standardized therapeutic procedures for critical care patients are needed.

We discuss the achievements of the ACNS critical care EEG nomenclature proposed in 2013 and, from a clinical angle, outline some limitations regarding translation into treatment implications. While the recently proposed updated 2021 version of the nomenclature will probable improve some uncertainty areas, a refined understanding of the mechanisms at the origin of the EEG patterns, and a multimodal integration of the nomenclature to the clinical context may help improving the rationale supporting therapeutic procedures. We illustrate these aspects on prognostication after cardiac arrest.

Delirium disorder: Unity in diversity

OBJECTIVE

The first objective of this review is to explore the factors that have led to and maintain the division between delirium and acute encephalopathy. The second is to explore the value of harmonizing them through the model of delirium disorder.

METHOD

This narrative review outlines major distinctions between delirium and acute encephalopathy. It also compares them with the model of delirium disorder, which seeks not only to integrate them but also to offer a broader palette of treatment targets.

RESULTS

Delirium implies an underlying acute encephalopathy, whereas acute encephalopathy presents as a spectrum from subsyndromal delirium to coma. Key factors that differentiate these two models include tradition, nuances of the models themselves, linguistic connotations, evoked responses from clinicians, implications of preventability and responsibility, cultural perceptions of non-pharmacological vs pharmacological interventions and economic incentives. A validated set of pathophysiological subtypes may ultimately help link the delirium-spectrum phenotype with various acute encephalopathies.

CONCLUSIONS

Developing a coherent clinical and scientific approach to this set of conditions demands that we first develop a coherent understanding of the conditions themselves and how they relate to one another. Such an approach must embrace the tension between a convergent phenotype and its diverse biological underpinnings.

Increased delta power as a scalp marker of epileptic activity: a simultaneous scalp and intracranial electroencephalography study

BACKGROUND AND PURPOSE

The purpose was to evaluate whether intracranial interictal epileptiform discharges (IEDs) that are not visible on the scalp are associated with changes in the frequency spectrum on scalp electroencephalograms (EEGs).

METHODS

Simultaneous scalp high-density EEG and intracranial EEG recordings were recorded in nine patients undergoing pre-surgical invasive recordings for pharmaco-resistant temporal lobe epilepsy. Epochs with hippocampal IED visible on intracranial EEG (ic-IED) but not on scalp EEG were selected, as well as control epochs without ic-IED. Welch's power spectral density was computed for each scalp electrode and for each subject; the power spectral density was further averaged across the canonical frequency bands and compared between the two conditions with and without ic-IED. For each patient the peak frequency in the delta band (the significantly strongest frequency band in all patients) was determined during periods of ic-IED. The five electrodes showing strongest power at the peak frequency were also determined.

RESULTS

It was found that intracranial IEDs are associated with an increase in delta power on scalp EEGs, in particular at a frequency ≥1.4 Hz. Electrodes showing slow frequency power changes associated with IEDs were consistent with the hemispheric lateralization of IEDs. Electrodes with maximum power of slow activity were not limited to temporal regions but also involved frontal (bilateral or unilateral) regions.

CONCLUSIONS

In patients with a clinical picture suggestive of temporal lobe epilepsy, the presence of delta slowing ≥1.4 Hz in anterior temporal regions can represent a scalp marker of hippocampal IEDs. To our best knowledge this is the first study that demonstrates the co-occurrence of ic-IED and increased delta power.

Status Triphasicus Versus Status Epilepticus?

SUMMARY

Generalized periodic patterns with triphasic wave morphology, long referred to as triphasic waves [TWs], had been associated with metabolic encephalopathies, although other neurologic and systemic causes have since been identified. In a recent classification of periodic patterns, TWs were formally grouped with the generalized periodic discharges, which are often associated with ictal activity. The interpretation of generalized periodic patterns with TWs as nonictal can have significant implications in the management of comatose patients in nonconvulsive status epilepticus. Electrographic characteristics that help distinguish nonictal periodic patterns with TWs from generalized periodic discharge ictal patterns include (1) TWs in long runs of periodic bilaterally synchronous and symmetric discharges, maximal in frontocentral or posterior head regions with and without a frontal-to-occipital lag or posterior-to-anterior lag, respectively; (2) recurrent spontaneous and/or low-dose benzodiazepine-induced attenuation and/or suppression of the periodic pattern and replacement with a diffuse slow wave activity throughout a prolonged EEG recording; and (3) stimulation-induced activation and/or increase in frequency and/or organization of TWs. We coined the term of status triphasicus to describe the electrographic periodic pattern of TWs with these three distinct characteristics. In this article, we discuss the advantages and limitations of keeping the status triphasicus pattern as a distinct electrographic entity different from periodic ictal generalized periodic discharge patterns. We discuss the circumstances in which a status triphasicus pattern can be associated with ictal activity and propose a simple pragmatic classification of status triphasicus that encompasses the different clinical scenarios it can be associated with.

An EEG Voyage in Search of Triphasic Waves-The Sirens and Corsairs on the Encephalopathy/EEG Horizon: A Survey of Triphasic Waves

SUMMARY

Generalized periodic discharges with triphasic wave (TW) morphology, long referred to as TWs, are typical of many toxic, metabolic, infectious, and cerebral structural problems, often in concert. Identifying TWs has been challenging for the electroencephalographer and clinician, as has been their cause, significance, prognosis, and treatment. This review highlights the many different patterns of TWs with commentary on their various causes and etiologies, characteristics, different morbidities, differentiation from nonconvulsive status epilepticus, and their prognosis. The articles in this Journal of Clinical Neurophysiology special issue on TWs will review the many challenges the clinician face when TWs are sighted.

Triphasic Waves Are Generated by Widespread Bilateral Cortical Networks

PURPOSE

Triphasic waves (TWs) have been observed in the EEG recorded in patients with various types of encephalopathy, yet their genesis and significance is still debated. The aim of this study was to elucidate the localization of the cortical generators of TWs using EEG source imaging.

METHODS

In 20 consecutive patients who had encephalopathy with TWs, EEG source imaging of the first negative and the positive phases of the TW was performed. Three different approaches were used: equivalent current dipoles, a distributed source model, and a recently described spatial filtration method for visualizing EEG in source space.

RESULTS

Equivalent current dipole models failed to provide valid solutions. The distributed source model and the spatial filtration method suggested that TWs were generated by large, bilateral cortical networks, invariably involving the anterior frontal and the temporo-polar areas.

CONCLUSIONS

Source imaging localized TWs to anterior frontal and temporo-frontal structures. Involvement of these regions is consistent with the typical pathophysiological changes of altered consciousness and cognitive changes observed in patients with TW encephalopathy.

Source Imaging of Triphasic Waves and Other Encephalopathies

PURPOSE

Triphasic waves (TWs) are defined as high-amplitude positive waveforms with preceding and after-going negative waves, typically seen in medically ill patients. TWs manifest in similar clinical presentations as other EEG encephalopathies; however, electrographically, they appear different. To better understand the difference, the authors used two different source localization software programs to find a reproducible and unique signature for TW.

METHODS

EEGs performed at Johns Hopkins Hospital and Duke University Hospital were retrospectively analyzed. EEG samples of TW, Delta, Theta-Delta, and Frontal Intermittent Rhythmic Delta Activity were selected. The authors did source localization via Commercial Curry 8 and open-source Brainstorm software. A minimum of 10 stereotypical waveforms per subject were selected. The authors used the Boundary Element Method for the head model, which was derived from the Montreal Neurological Institute averaged imaging data set. Dipole and current density analyses were performed.

RESULTS

Twenty-eight patients were selected (10 TW, 4 Frontal Intermittent Rhythmic Delta Activity, 6 Theta-Delta, and 8 Delta). The findings suggest the activation of anterior frontal and midline structures for TW. Frontal Intermittent Rhythmic Delta Activity had a similar localization but without a moving dipole. In comparison, the Delta and Delta-Theta appeared to have a more diffuse origin.

CONCLUSIONS

Source analysis of TW via two different software suggests the anterior midline location of TW with anterior to posterior propagation. These findings correlate with the previous hypotheses of TW origin. Retrospective analysis, low number of recording electrodes, and difficult analysis of slow waves limit the interpretation of these results. Nonetheless, this article opens the prospect of future studies in this field.

Neurophysiological findings and their prognostic value in critical COVID-19 patients: An observational study

OBJECTIVE

To describe EEG patterns of critical Coronavirus Disease 2019 (COVID-19) patients with suspicion of encephalopathy and test their association with clinical outcome.

METHODS

EEG after discontinuation of sedation in all patients, and somesthesic evoked potentials and brainstem auditive evoked potentials when EEG did not show reactivity, were performed. Clinical outcome was assessed at day 7 and 14 after neurophysiological explorations.

RESULTS

33 patients were included for analysis. We found slowed background activity in 85% of cases, unreactive activity in 42% of cases, low-voltage activity in 21% of cases and rhythmic or periodic delta waves in 61% of cases. EEG epileptic events were never recorded. Clinical outcome at day 14 was associated with unreactive background activity and tended to be associated with rhythmic or periodic delta waves and with low-voltage activity. Results of multimodal evoked potentials were in favor of a preservation of central nervous system somatosensory and auditory functions.

CONCLUSIONS

Among critical COVID-19 patients with abnormal arousal at discontinuation of sedation, EEG patterns consistent with encephalopathy are found and are predictive for short term clinical outcome.

SIGNIFICANCE

The abnormal EEG with presence of periodic discharges and lack of reactivity could be related to encephalopathy linked to COVID-19.

Challenges of Delirium Management in Patients with Traumatic Brain Injury: From Pathophysiology to Clinical Practice

Traumatic brain injury (TBI) can initiate a very complex disease of the central nervous system (CNS), starting with the primary pathology of the inciting trauma and subsequent inflammatory and CNS tissue response. Delirium has long been regarded as an almost inevitable consequence of moderate to severe TBI, but more recently has been recognized as an organ dysfunction syndrome with potentially mitigating interventions. The diagnosis of delirium is independently associated with prolonged hospitalization, increased mortality and worse cognitive outcome across critically ill populations. Investigation of the unique problems and management challenges of TBI patients is needed to reduce the burden of delirium in this population. In this narrative review, possible etiologic mechanisms behind post-traumatic delirium are discussed, including primary injury to structures mediating arousal and attention and secondary injury due to progressive inflammatory destruction of the brain parenchyma. Other potential etiologic contributors include dysregulation of neurotransmission due to intravenous sedatives, seizures, organ failure, sleep cycle disruption or other delirium risk factors. Delirium screening can be accomplished in TBI patients and the presence of delirium portends worse outcomes. There is evidence that multi-component care bundles including an analgesia-prioritized sedation algorithm, regular spontaneous awakening and breathing trials, protocolized delirium assessment, early mobility and family engagement can reduce the burden of ICU delirium. The aim of this review is to summarize the approach to delirium in TBI patients with an emphasis on pathogenesis and management. Emerging CNS-active drug therapies that show promise in preclinical studies are highlighted.

Automated diagnosis of encephalitis in pediatric patients using EEG rhythms and slow biphasic complexes

Slow biphasic complexes (SBC) have been identified in the EEG of patients suffering for inflammatory brain diseases. Their amplitude, location and frequency of appearance were found to correlate with the severity of encephalitis. Other characteristics of SBCs and of EEG traces of patients could reflect the grade of pathology. Here, EEG rhythms are investigated together with SBCs for a better characterization of encephalitis. EEGs have been acquired from pediatric patients: ten controls and ten encephalitic patients. They were split by neurologists into five classes of different severity of the pathology. The relative power of EEG rhythms was found to change significantly in EEGs labeled with different severity scores. Moreover, a significant variation was found in the last seconds before the appearance of an SBC. This information and quantitative indexes characterizing the SBCs were used to build a binary classification decision tree able to identify the classes of severity. True classification rate of the best model was 76.1% (73.5% with leave-one-out test). Moreover, the classification errors were among classes with similar severity scores (precision higher than 80% was achieved considering three instead of five classes). Our classification method may be a promising supporting tool for clinicians to diagnose, assess and make the follow-up of patients with encephalitis.

Quantified EEG for the Characterization of Epileptic Seizures versus Periodic Activity in Critically Ill Patients

Epileptic seizures (ES) are frequent in critically ill patients and their detection and treatment are mandatory. However, sometimes it is quite difficult to discriminate between ES and non-epileptic bursts of periodic activity (BPA). Our aim was to characterize ES and BPA by means of quantified electroencephalography (qEEG). Records containing either ES or BPA were visually identified and divided into 1 s windows that were 10% overlapped. Differential channels were grouped by frontal, parieto-occipital and temporal lobes. For every channel and window, the power spectrum was calculated and the area for delta (0–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), and beta (13–30 Hz) bands and spectral entropy (Se) were computed. Mean values of percentage changes normalized to previous basal activity and standardized mean difference (SMD) for every lobe were computed. We have observed that BPA are characterized by a selective increment of delta activity and decrease in Se along the scalp. Focal seizures (FS) always propagated and were similar to generalized seizures (GS). In both cases, although delta and theta bands increased, the faster bands (alpha and beta) showed the highest increments (more than 4 times) without modifications in Se. We have defined the numerical features of ES and BPA, which can facilitate its clinical identification.

Clinical neurophysiology of altered states of consciousness: Encephalopathy and coma

The neurophysiologist will commonly encounter patients with encephalopathy/delirium (altered consciousness with impaired cognition, usually with sleep-wake cycle alteration and lethargy) or coma (an eyes-closed state of unresponsiveness) in the hospital setting. Assessing the background frequency of the EEG, as well as the presence or absence of other features (reactivity, periodic discharges such as triphasic waves), can provide insight into the patient's underlying condition and in some cases may provide prognostic information. The literature of postanoxic arrest EEG patterns continues to expand. Other neurophysiologic tests, such as somatosensory evoked potentials, auditory mismatch negativity, and even EMG, may also play a role in assessing brain function; distinguishing among a locked-in state, minimally conscious state, persistent vegetative state, and waking/unresponsive states; and assessing the potential for recovery after brain injury.

Electroencephalography and delirium in the postoperative period

Delirium commonly manifests in the postoperative period as a clinical syndrome resulting from acute brain dysfunction or encephalopathy. Delirium is characterized by acute and often fluctuating changes in attention and cognition. Emergence delirium typically presents and resolves within minutes to hours after termination of general anaesthesia. Postoperative delirium hours to days after an invasive procedure can herald poor outcomes. Easily recognized when patients are hyperactive or agitated, delirium often evades diagnosis as it most frequently presents with hypoactivity and somnolence. EEG offers objective measurements to complement clinical assessment of this complex fluctuating disorder. Although EEG features of delirium in the postoperative period remain incompletely characterized, a shift of EEG power into low frequencies is a typical finding shared among encephalopathies that manifest with delirium. In aggregate, existing data suggest that serial or continuous EEG in the postoperative period facilitates monitoring of delirium development and severity and assists in detecting epileptic aetiologies. Future studies are needed to clarify the precise EEG features that can reliably predict or diagnose delirium in the postoperative period, and to provide mechanistic insights into this pathologically diverse neurological disorder.

Admission EEG findings in diverse paediatric cerebral malaria populations predict outcomes

BACKGROUND

Electroencephalography at hospital presentation may offer important insights regarding prognosis that can inform understanding of cerebral malaria (CM) pathophysiology and potentially guide patient selection and risk stratification for future clinical trials. Electroencephalogram (EEG) findings in children with CM in Uganda and Malawi were compared and associations between admission EEG findings and outcome across this diverse population were assessed. Demographic, clinical and admission EEG data from Ugandan and Malawian children admitted from 2009 to 2012 with CM were gathered, and survivors assessed for neurological abnormalities at discharge.

RESULTS

281 children were enrolled (Uganda n = 122, Malawi n = 159). The Malawian population was comprised only of retinopathy positive children (versus 72.5% retinopathy positive in Uganda) and were older (4.2 versus 3.7 years; p = 0.046), had a higher HIV prevalence (9.0 versus 2.8%; p = 0.042), and worse hyperlactataemia (7.4 versus 5.2 mmol/L; p < 0.001) on admission compared to the Ugandan children. EEG findings differed between the two groups in terms of average voltage and frequencies, reactivity, asymmetry, and the presence/absence of sleep architecture. In univariate analyses pooling EEG and outcomes data for both sites, higher average and maximum voltages, faster dominant frequencies, and retained reactivity were associated with survival (all p < 0.05). Focal slowing was associated with death (OR 2.93; 95% CI 1.77-7.30) and a lower average voltage was associated with neurological morbidity in survivors (p = 0.0032).

CONCLUSIONS

Despite substantial demographic and clinical heterogeneity between subjects in Malawi and Uganda as well as different EEG readers at each site, EEG findings on admission predicted mortality and morbidity. For CM clinical trials aimed at decreasing mortality or morbidity, EEG may be valuable for risk stratification and/or subject selection.

Impairment of GABAergic system contributes to epileptogenesis in glutaric acidemia type I

OBJECTIVES

Glutaric acidemia type I (GA-I) is an inherited neurometabolic disorder caused by deficiency of glutaryl-CoA dehydrogenase (GCDH) and characterized by increased levels of glutaric, 3-OH-glutaric, and glutaconic acids in the brain parenchyma. The increment of these organic acids inhibits glutamate decarboxylase (GAD) and consequently lowers the γ-aminobutyric acid (GABA) synthesis. Untreated patients exhibit severe neurologic deficits during development, including epilepsy, especially following an acute encephalopathy outbreak. In this work, we evaluated the role of the GABAergic system on epileptogenesis in GA-I using the Gcdh^-/- mice exposed to a high lysine diet (Gcdh^-/- -Lys).

METHODS

Spontaneous recurrent seizures (SRS), seizure susceptibility, and changes in brain oscillations were evaluated by video-electroencephalography (EEG). Cortical GABAergic synaptic transmission was evaluated using electrophysiologic and neurochemical approaches.

RESULTS

SRS were observed in 72% of Gcdh^-/- -Lys mice, whereas no seizures were detected in age-matched controls (Gcdh^+/+ or Gcdh^-/- receiving normal diet). The severity and number of PTZ-induced seizures were higher in Gcdh^-/- -Lys mice. EEG spectral analysis showed a significant decrease in theta and gamma oscillations and predominant delta waves in Gcdh^-/- -Lys mice, associated with increased EEG left index. Analysis of cortical synaptosomes revealed a significantly increased percentage of glutamate release and decreased GABA release in Gcdh^-/- -Lys mice that were associated with a decrease in cortical GAD immunocontent and activity and confirmed by reduced frequency of inhibitory events in cortical pyramidal cells.

SIGNIFICANCE

Using an experimental model with a phenotype similar to that of GA-I in humans-the Gcdh^-/- mice under high lysine diet (Gcdh^-/- -Lys)-we provide evidence that a reduction in cortical inhibition of Gcdh^-/- -Lys mice, probably induced by GAD dysfunction, leads to hyperexcitability and increased slow oscillations associated with neurologic abnormalities in GA-I. Our findings offer a new perspective on the pathophysiology of brain damage in GA-I.

Electroencephalographic patterns of lithium poisoning: a study of the effect/concentration relationships in the rat

OBJECTIVES

Lithium overdose may result in encephalopathy and electroencephalographic abnormalities. Three poisoning patterns have been identified based on the ingested dose, previous treatment duration and renal function. Whether the severity of lithium-induced encephalopathy depends on the poisoning pattern has not been established. We designed a rat study to investigate lithium-induced encephalopathy and correlate its severity to plasma, erythrocyte, cerebrospinal fluid and brain lithium concentrations previously determined in rat models mimicking human poisoning patterns.

METHODS

Lithium-induced encephalopathy was assessed and scored using continuous electroencephalography.

RESULTS

We demonstrated that lithium overdose was consistently responsible for encephalopathy, the severity of which depended on the poisoning pattern. Acutely poisoned rats developed rapid-onset encephalopathy which reached a maximal grade of 2/5 at 6 h and disappeared at 24 h post-injection. Acute-on-chronically poisoned rats developed persistent and slightly fluctuating encephalopathy which reached a maximal grade of 3/5. Chronically poisoned rats developed rapid-onset but gradually increasing life-threatening encephalopathy which reached a maximal grade of 4/5. None of the acutely, 20% of the acute-on-chronically and 57% of the chronically lithium-poisoned rats developed seizures. The relationships between encephalopathy severity and lithium concentrations fitted a sigmoidal E_max model based on cerebrospinal fluid concentrations in acute poisoning and brain concentrations in acute-on-chronic poisoning. In chronic poisoning, worsening of encephalopathy paralleled the increase in plasma lithium concentrations.

CONCLUSIONS

The severity of lithium-induced encephalopathy is dependent on the poisoning pattern, which was previously shown to determine lithium accumulation in the brain. Our data support the proposition that electroencephalography is a sensitive tool for scoring lithium-related neurotoxicity.

Electroencephalographic reactivity testing in unconscious patients: a systematic review of methods and definitions

Electroencephalographic (EEG) reactivity testing is often presented as a clear-cut element of electrophysiological testing. Absence of EEG reactivity is generally considered an indicator of poor outcome, especially in patients after cardiac arrest. However, guidelines do not clearly describe how to test for reactivity and how to evaluate the results. In a quest for clear guidelines, we performed a systematic review aimed at identifying testing methods and definitions of EEG reactivity. We systematically searched the literature between 1970 and May 2016. Methodological quality of the studies was assessed using the QUality In Prognostic Studies tool. Quality of the descriptions of stimulus protocol and reactivity definition was rated on a four-category grading scale based on reproducibility. We found that protocols for EEG reactivity testing vary greatly and descriptions of protocols are almost never replicable. Furthermore, replicable definitions of presence or absence of EEG reactivity are never provided. In order to draw firm conclusions on EEG reactivity as a prognostic factor, future studies should include a precise stimulation protocol and reactivity definition to facilitate guideline formation.

Which EEG patterns in coma are nonconvulsive status epilepticus?

Nonconvulsive status epilepticus (NCSE) is common in patients with coma with a prevalence between 5% and 48%. Patients in deep coma may exhibit epileptiform EEG patterns, such as generalized periodic spikes, and there is an ongoing debate about the relationship of these patterns and NCSE. The purposes of this review are (i) to discuss the various EEG patterns found in coma, its fluctuations, and transitions and (ii) to propose modified criteria for NCSE in coma. Classical coma patterns such as diffuse polymorphic delta activity, spindle coma, alpha/theta coma, low output voltage, or burst suppression do not reflect NCSE. Any ictal patterns with a typical spatiotemporal evolution or epileptiform discharges faster than 2.5 Hz in a comatose patient reflect nonconvulsive seizures or NCSE and should be treated. Generalized periodic diacharges or lateralized periodic discharges (GPDs/LPDs) with a frequency of less than 2.5 Hz or rhythmic discharges (RDs) faster than 0.5 Hz are the borderland of NCSE in coma. In these cases, at least one of the additional criteria is needed to diagnose NCSE (a) subtle clinical ictal phenomena, (b) typical spatiotemporal evolution, or (c) response to antiepileptic drug treatment. There is currently no consensus about how long these patterns must be present to qualify for NCSE, and the distinction from nonconvulsive seizures in patients with critical illness or in comatose patients seems arbitrary. The Salzburg Consensus Criteria for NCSE [1] have been modified according to the Standardized Terminology of the American Clinical Neurophysiology Society [2] and validated in three different cohorts, with a sensitivity of 97.2%, a specificity of 95.9%, and a diagnostic accuracy of 96.3% in patients with clinical signs of NCSE. Their diagnostic utility in different cohorts with patients in deep coma has to be studied in the future. This article is part of a Special Issue entitled "Status Epilepticus".

Acute brain failure in severe sepsis: a prospective study in the medical intensive care unit utilizing continuous EEG monitoring

PURPOSE

Investigate the prevalence, risk factors and impact of continuous EEG (cEEG) abnormalities on mortality through the 1-year follow-up period in patients with severe sepsis.

METHODS

Prospective, single-center, observational study of consecutive patients admitted with severe sepsis to the Medical ICU at an academic medical center.

RESULTS

A total of 98 patients with 100 episodes of severe sepsis were included; 49 patients (50%) were female, median age was 60 (IQR 52-74), the median non-neuro APACHE II score was 23.5 (IQR 18-28) and median non-neuro SOFA score was 8 (IQR 6-11). Twenty-five episodes had periodic discharges (PD), of which 11 had nonconvulsive seizures (NCS). No patient had NCS without PD. Prior neurological history was associated with a higher risk of PD or NCS (45 vs. 17%; CI 1.53-10.43), while the non-neuro APACHE II, non-neuro SOFA, severity of cardiovascular shock and presence of sedation during cEEG were associated with a lower risk of PD or NCS. Clinical seizures before cEEG were associated with a higher risk of nonconvulsive status epilepticus (24 vs. 6%; CI 1.42-19.94) while the non-neuro APACHE II and non-neuro SOFA scores were associated with a lower risk. Lack of EEG reactivity was present in 28% of episodes. In the survival analysis, a lack of EEG reactivity was associated with higher 1-year mortality [mean survival time 3.3 (95% CI 1.8-4.9) vs. 7.5 (6.4-8.7) months; p = 0.002] but the presence of PD or NCS was not [mean survival time 3.3 (95% CI 1.8-4.9) vs. 7.5 (6.4-8.7) months; p = 0.592]. Lack of reactivity was more frequent in patients on continuous sedation during cEEG. In patients with available 1-year data (34% of the episodes), 82% had good functional outcome (mRS ≤ 3, n = 27). There were no significant predictors of functional outcome, late cognition, and no patient with complete follow-up data developed late seizure or new epilepsy.

CONCLUSIONS

NCS and PD are common in patients with severe sepsis and altered mental status. They were less frequent among the most severely sick patients and were not associated with outcome in this study. Lack of EEG reactivity was more frequent in patients on continuous sedation and was associated with mortality up to 1 year after discharge. Larger studies are needed to confirm these findings in a broader population and to further evaluate long-term cognitive outcome, risk of late seizure and epilepsy.

Electroencephalography for diagnosis and prognosis of acute encephalitis

OBJECTIVES

To confirm the previously identified EEG characteristics for HSV encephalitis and to determine the diagnostic and predictive value of electroencephalography (EEG) features for etiology and outcome of acute encephalitis in adults. In addition, we sought to investigate their independence from possible clinical confounders.

METHODS

This study was performed in the Intensive Care Units of two academic tertiary care centers. From 1997 to 2011, all consecutive patients with acute encephalitis who received one or more EEGs were included. Examination of the diagnostic and predictive value of EEG patterns regarding etiology, clinical conditions, and survival was performed. The main outcome measure was in-hospital death.

RESULTS

Of 103 patients with encephalitis, EEGs were performed in 76 within a median of 1 day (inter quartile range 0.5-3) after admission. Mortality was 19.7%. Higher proportions of periodic discharges (PDs) (p=0.029) and focal slowing (p=0.017) were detected in Herpes Simplex virus (HSV) encephalitis as compared to non-HSV encephalitis, while clinical characteristics did not differ. Normal EEG remained the strongest association with a low relative risk for death in multivariable analyses (RR<0.001, p<0.001) adjusting for confounders as coma, global cerebral edema and mechanical ventilation. None of the patients with a normal EEG had a GCS of 15.

CONCLUSIONS

Normal EEG predicted survival independently from possible confounders, highlighting the prognostic value of EEG in evaluating patients with encephalitis. EEG revealed higher proportions of PDs along with focal slowing in HSV encephalitis as compared to other etiologies.

SIGNIFICANCE

EEG significantly adds to clinical, diagnostic and prognostic information in patients with acute encephalitis.