Meta-analysis of EEG test performance shows wide variation among studies

A New Score for Sharp Discharges in the EEG Predicts Epilepsy

PURPOSE

A challenge in EEG interpretation is to correctly classify suspicious focal sharp activity as epileptiform or not. A predictive score was developed from morphologic features of the first focal sharp discharge, which can help in this decision.

METHODS

From a clinical standard EEG database, the authors identified 2,063 patients without a previous epilepsy diagnosis who had a focal sharp discharge in their EEG. Morphologic features (amplitude, area of slow wave, etc.) were extracted using an open source one-click algorithm in EEGLAB, masked to clinical classification. A score was developed from these features and validated with the clinical diagnosis of epilepsy over 2 to 6 years of follow-up. Independent external validation was performed in Kural long-term video-EEG monitoring dataset.

RESULTS

The score for the first focal sharp discharge had a moderate predictive performance for the clinical designation as the EEG being epileptiform (area under the receiver operating characteristics curve = 0.86). Best specificity was 91% and sensitivity 55%. The score also predicted a future epilepsy diagnosis (area under the receiver operating characteristics curve = 0.70). Best specificity was 86% and sensitivity 38%. Validation on the external dataset had an area under the receiver operating characteristics curve = 0.80. Clinical EEG identification of focal interictal epileptiform discharges had an area under the receiver operating characteristics curve = 0.73 for prediction of epilepsy. The score was based on amplitude, slope, difference from background, slow after-wave area, and age. Interrater reproducibility was high (ICC = 0.91).

CONCLUSIONS

The designation of the first focal sharp discharge as epileptiform depends on reproducible morphologic features. Characteristic features were amplitude, slope, slow after-wave area, and difference from background. The score was predictive of future epilepsy. Halford semiquantitative scale had similar diagnostic performance but lower reproducibility.

Recommendations for the medical work-up of first episode psychosis, including specific relevance to Indigenous Australians: A narrative review

AIMS

To collate existing literature for busy practicing psychiatrists about the medical work-up for first-episode psychosis (FEP). Therefore, (a) to review current guidelines for the medical work-up of first episode psychosis. (b) To examine whether any specific recommendations for Indigenous Australians exist. (c) To produce an easy reference table of evidence based investigations.

METHOD

A multi-part narrative review process was undertaken. Step 1 "Source identification and summary": identified key existing national and international guidelines and expert opinions related to the medical work-up of FEP and summarised these suggestions. Step 2 "Exploration of each investigation": examined each of the identified investigations for its importance. Step 3 "Relevance to Indigenous Australians": reviewed any particular relevance to the Indigenous Australian population. Step 4 "Clinician guide": involved presenting recommended investigations in a simple table.

RESULTS

Multiple guidelines were identified. There was clear consensus for many aspects. However, there were also differences in the approach for some investigations. Clinical reasoning for the proposed investigations was commonly absent. There were limited specific recommendations for Indigenous Australians. Evidence and importance was explored for each investigation and auseful table for the practicing psychiatrist was constructed. Investigations were stratified into those considered to be "universal," "low yield," or "unecessary."

CONCLUSION

A narrative review of multiple guidelines relating to the medical work-up of FEP identified many similarities and some differences to their approach. Little additional information exists for the Indigenous Australian context. A clinician friendly worksheet for everyday use may be helpful to busy clinicians.

When should we obtain a routine EEG while managing people with epilepsy?

More than eight decades after its discovery, routine electroencephalogram (EEG) remains a safe, noninvasive, inexpensive, bedside test of neurological function. Knowing when a routine EEG should be obtained while managing people with epilepsy is a critical aspect of optimal care. Despite advances in neuroimaging techniques that aid diagnosis of structural lesions in the central nervous system, EEG continues to provide critical diagnostic evidence with implications on treatment. A routine EEG performed after a first unprovoked seizure can support a clinical diagnosis of epilepsy and differentiate those without epilepsy, classify an epilepsy syndrome to impart prognosis, and characterize seizures for antiseizure management. Despite a current viral pandemic, EEG services continue, and the value of routine EEG is unchanged.

Experimental Therapeutic Strategies in Epilepsies Using Anti-Seizure Medications

Epilepsies are among the most common neurological problems. The disease burden in patients with epilepsy is significantly high, and epilepsy has a huge negative impact on patients' quality of life with epilepsy and their families. Anti-seizure medications are the mainstay treatment in patients with epilepsy, and around 70% of patients will ultimately control with a combination of at least two appropriately selected anti-seizure medications. However, in one-third of patients, seizures are resistant to drugs, and other measures will be needed. The primary goal in using experimental therapeutic medication strategies in patients with epilepsy is to prevent recurrent seizures and reduce the rate of traumatic events that may occur during seizures. So far, various treatments using medications have been offered for patients with epilepsies, which have been classified according to the type of epilepsy, the effectiveness of the medications, and the adverse effects. Medications such as Levetiracetam, valproic acid, and lamotrigine are at the forefront of these patients' treatment. Epilepsy surgery, neuro-stimulation, and the ketogenic diet are the main measures in patients with medication-resistant epilepsies. In this paper, we will review the therapeutic approach using anti-seizure medications in patients with epilepsy. However, it should be noted that some of these patients still do not respond to existing treatments; therefore, the limited ability of current therapies has fueled research efforts for the development of novel treatment strategies. Thus, it seems that in addition to surgical measures, we should look for more specific agents that have less adverse events and have a greater effect in stopping seizures.

Long-term outcome of 200 patients referred to a first seizure clinic

OBJECTIVES

To determine what proportion of our First Seizure referrals reflected true unprovoked first seizures or epilepsy, and to assess the long-term diagnostic accuracy of our First Seizure Clinic (FSC) by quantifying the risk of subsequent seizures in our FSC cohort.

METHODS

We prospectively collected data of 200 adult patients referred to the FSC between May 2014 and December 2015. We reviewed clinical notes, electroencephalography (EEG) data and performed telephone follow-up at 28-month post-diagnosis.

RESULTS

Of the 200 patients referred to the FSC, 181 attended. At the initial assessment, 39 of these patients were diagnosed with epilepsy, with most of these patients (59%) found to have a history of previous seizures. Fifty patients were diagnosed with a first seizure, of which 28% were labelled as provoked seizures. Sixty nine of the patients received another diagnosis and 23 were labelled as indeterminable. At 28 months follow-up, 11 (22%) of patients who received a diagnosis of first seizure subsequently received a diagnosis of epilepsy. In the remaining groups, only 5 (5%) patients were diagnosed with epilepsy (of these three were in the indeterminable group).

CONCLUSIONS

Our study shows that 50% of the patients referred to a FSC had not experienced a seizure but were given an alternative diagnosis. Secondly, our study indicates that the risk of seizure recurrence following a first seizure is quite low (22%). This is because a substantial proportion of the patients were diagnosed with epilepsy already at the first assessment. The high proportion of patients being diagnosed with epilepsy was mainly due to a history of previous seizures. Thirdly, patients who were given an alternative diagnosis at the first assessment had a low probability (5%) for seizure recurrence.

Sturge-Weber syndrome: an update on the relevant issues for neurosurgeons

PURPOSE

Sturge-Weber syndrome (SWS) is a neurocutaneous facomatosis characterized by facial and leptomeningeal angioma, glaucoma, seizures, and neurological disability. Therefore, a challenging multidisciplinary interaction is required for its management. The goal of this paper is to review the main aspects of SWS and to present an illustrative pediatric series.

METHODS

The pertinent literature has been analyzed, focused mainly on etiopathogenesis, pathology, clinical features, diagnostic tools, management, and outcome of the disease. Moreover, a series of 11 children operated on for refractory epilepsy between 2005 and 2015 (minimum follow-up 5 years, mean follow-up 9.6 years) is reported. The series consists of six boys and five girls with 6.5-month and 16.2-month mean age at seizure onset and at surgery, respectively. Seizures affected all children, followed by hemiparesis and psychomotor delay (81%), glaucoma (54%), and other neurological deficits (45%).

RESULTS

All children underwent hemispherectomy (anatomical in three cases, functional in two cases, hemispherotomy in six cases); one patient needed a redo hemispherotomy. Mortality was nil; disseminated intravascular coagulation and interstitial pneumonia occurred in one patient each; three children had subdural fluid collection. Eight patients (72%) are in the ILAE Class 1 (completely seizure and aura free), two in Class 2 (only auras, no seizure), and one in Class 3 (1-3 seizure days per year). AEDs discontinuation was possible in 73% of cases. The most important news from the literature concerned the pathogenesis (role of the mutation of the GNAQ gene in the abnormal SWS vasculogenesis), the clinical findings (the features and pathogenesis of the stroke-like episodes are being understood), the diagnostic tools (quantitative MRI and EEG), and both the medical (migraine, seizures) and surgical management (epilepsy). The epileptic outcome of SWS patients is very good (80% are seizure-free), if compared with other hemispheric syndromes. The quality of life is affected by the neurological and cognitive deficits.

CONCLUSIONS

SWS still is an etiological and clinical challenge. However, the improvements over the time are consistent. In particular, the neurosurgical treatment of refractory epilepsy provides very good results as long as the indication to treatment is correct.

Critically ill benign EEG variants: Is there such a thing?

Despite growing use of critical care electroencephalography (ccEEG) to detect seizures and status epilepticus in the intensive care unit (ICU), integrating ccEEG findings with traditionally described benign EEG variants (BEVs) is a relatively new concept. BEV-like waveforms are now increasingly encountered in the ICU, and have also been explicitly included in proposed definitions of brief potentially ictal rhythmic discharges (BIRDs) in the ICU, bringing to the fore the question of if and which EEG patterns in critically ill patients can be safely deemed "benign". Though well-characterized as benign in healthy outpatients at low pre-test risk for neurologic disease, the significance of BEVs in the ICU remains largely unknown. Simultaneously, there has been mounting evidence to suggest that certain BEVs can arise from heterogeneous intracranial sources, including some pathologic generators. We conducted an extensive literature review on all known BEVs to assess what is known of BEVs in the ICU. Here we discuss critically ill BEVs and how to interpret them.

Consistency of quantitative electroencephalography features in a large clinical data set

OBJECTIVE

Despite their increasing use and public health importance, little is known about the consistency and variability of the quantitative features of baseline electroencephalography (EEG) measurements in healthy individuals and populations. This study aims to investigate population consistency of EEG features.

APPROACH

We propose a non-parametric method of evaluating consistency of commonly used EEG features based on counts of non-significant statistical tests using a large data set. We first replicate stationarity results of absolute band powers using coefficients of variation. We then determine feature stationarity, intra-subject consistency, inter-subject consistency, and intra- versus inter-subject consistency across different epoch lengths for 30 features.

MAIN RESULTS

We find in general that features with normalizing constants are more stationary. We also find entropy, median, skew, and kurtosis of EEG to behave as baseline EEG metrics. However, other spectral and signal shape features have stronger intra-subject consistency and thus are better for distinguishing individuals.

SIGNIFICANCE

These results provide data-driven non-parametric methods of identifying EEG features and their spatial characteristics ideal for various EEG applications, and determining future EEG feature consistencies using an existing EEG data set.

Cholinergic nervous system and glaucoma: From basic science to clinical applications

The cholinergic system has a crucial role to play in visual function. Although cholinergic drugs have been a focus of attention as glaucoma medications for reducing eye pressure, little is known about the potential modality for neuronal survival and/or enhancement in visual impairments. Citicoline, a naturally occurring compound and FDA approved dietary supplement, is a nootropic agent that is recently demonstrated to be effective in ameliorating ischemic stroke, traumatic brain injury, Parkinson's disease, Alzheimer's disease, cerebrovascular diseases, memory disorders and attention-deficit/hyperactivity disorder in both humans and animal models. The mechanisms of its action appear to be multifarious including (i) preservation of cardiolipin, sphingomyelin, and arachidonic acid contents of phosphatidylcholine and phosphatidylethanolamine, (ii) restoration of phosphatidylcholine, (iii) stimulation of glutathione synthesis, (iv) lowering glutamate concentrations and preventing glutamate excitotoxicity, (v) rescuing mitochondrial function thereby preventing oxidative damage and onset of neuronal apoptosis, (vi) synthesis of myelin leading to improvement in neuronal membrane integrity, (vii) improving acetylcholine synthesis and thereby reducing the effects of mental stress and (viii) preventing endothelial dysfunction. Such effects have vouched for citicoline as a neuroprotective, neurorestorative and neuroregenerative agent. Retinal ganglion cells are neurons with long myelinated axons which provide a strong rationale for citicoline use in visual pathway disorders. Since glaucoma is a form of neurodegeneration involving retinal ganglion cells, citicoline may help ameliorate glaucomatous damages in multiple facets. Additionally, trans-synaptic degeneration has been identified in humans and experimental models of glaucoma suggesting the cholinergic system as a new brain target for glaucoma management and therapy.

Alternative Diagnosis of Epilepsy in Children Without Epileptiform Discharges Using Deep Convolutional Neural Networks

Numerous nonepileptic paroxysmal events, such as syncope and psychogenic nonepileptic seizures, may imitate seizures and impede diagnosis. Misdiagnosis can lead to mistreatment, affecting patients’ lives considerably. Electroencephalography is commonly used for diagnosing epilepsy. Although on electroencephalograms (EEGs), epileptiform discharges (ED) specifically indicate epilepsy, only approximately 50% of patients with epilepsy have ED in their first EEG. In this study, we developed a deep convolutional neural network (ConvNet)-based classifier to distinguish EEG between patients with epilepsy without ED and controls. Overall, 25 patients with epilepsy without ED in their EEGs and 25 age-matched patients with Tourette syndrome or syncope were enrolled. Their EEGs were classified using the deep ConvNet. When the EEG data without overlapping were used, the accuracy, sensitivity, and specificity were 65.00%, 48.00%, and 82.00%, respectively. The performance measures improved when the input EEG data were augmented through overlapping. With 95% EEG data overlapping, the accuracy, sensitivity, and specificity increased to 80.00%, 70.00%, and 90.00%, respectively. The proposed method could be regarded as a pilot study to demonstrate a proof of concept of a potential diagnostic value of deep ConvNet in patients with epilepsy without ED. Further studies are needed to assist neurologists in distinguishing nonepileptic paroxysmal events from epilepsy.

An objective score to identify psychogenic seizures based on age of onset and history

OBJECTIVE

Psychogenic nonepileptic seizure (PNES) is a common diagnosis after evaluation of medication resistant or atypical seizures with video-electroencephalographic monitoring (VEM), but usually follows a long delay after the development of seizures, during which patients are treated for epilepsy. Therefore, more readily available diagnostic tools are needed for earlier identification of patients at risk for PNES. A tool based on patient-reported psychosocial history would be especially beneficial because it could be implemented in the outpatient clinic.

METHODS

Based on the data from 1375 patients with VEM-confirmed diagnoses, we used logistic regression to compare the frequency of specific patient-reported historical events, demographic information, age of onset, and delay from first seizure until VEM in five mutually exclusive groups of patients: epileptic seizures (ES), PNES, physiologic nonepileptic seizure-like events (PSLE), mixed PNES plus ES, and inconclusive monitoring. To determine the diagnostic utility of this information to differentiate PNES only from ES only, we used multivariate piecewise-linear logistic regression trained using retrospective data from chart review and validated based on data from 246 prospective standardized interviews.

RESULTS

The prospective area under the curve of our weighted multivariate piecewise-linear by-sex score was 73%, with the threshold that maximized overall retrospective accuracy resulting in a prospective sensitivity of 74% (95% CI: 70-79%) and prospective specificity of 71% (95% CI: 64-82%). The linear model and piecewise linear without an interaction term for sex had very similar performance statistics. In the multivariate piecewise-linear sex-split predictive model, the significant factors positively associated with ES were history of febrile seizures, current employment or active student status, history of traumatic brain injury (TBI), and longer delay from first seizure until VEM. The significant factors associated with PNES were female sex, older age of onset, mild TBI, and significant stressful events with sexual abuse, in particular, increasing the likelihood of PNES. Delays longer than 20years, age of onset after 31years for men, and age of onset after 40years for women had no additional effect on the likelihood of PNES.

DISCUSSION

Our promising results suggest that an objective score has the potential to serve as an early outpatient screening tool to identify patients with greater likelihood of PNES when considered in combination with other factors. In addition, our analysis suggests that sexual abuse, more than other psychological stressors including physical abuse, is more associated with PNES. There was a trend of increasing frequency of PNES for women during childbearing years and plateauing outside those years that was not observed in men.

Identifying psychogenic seizures through comorbidities and medication history

OBJECTIVE

Low-cost evidence-based tools are needed to facilitate the early identification of patients with possible psychogenic nonepileptic seizures (PNES). Prior to accurate diagnosis, patients with PNES do not receive interventions that address the cause of their seizures and therefore incur high medical costs and disability due to an uncontrolled seizure disorder. Both seizures and comorbidities may contribute to this high cost.

METHODS

Based on data from 1,365 adult patients with video-electroencephalography-confirmed diagnoses from a single center, we used logistic and Poisson regression to compare the total number of comorbidities, number of medications, and presence of specific comorbidities in five mutually exclusive groups of diagnoses: epileptic seizures (ES) only, PNES only, mixed PNES and ES, physiologic nonepileptic seizurelike events, and inconclusive monitoring. To determine the diagnostic utility of comorbid diagnoses and medication history to differentiate PNES only from ES only, we used multivariate logistic regression, controlling for sex and age, trained using a retrospective database and validated using a prospective database.

RESULTS

Our model differentiated PNES only from ES only with a prospective accuracy of 78% (95% confidence interval =72-84%) and area under the curve of 79%. With a few exceptions, the number of comorbidities and medications was more predictive than a specific comorbidity. Comorbidities associated with PNES were asthma, chronic pain, and migraines (p < 0.01). Comorbidities associated with ES were diabetes mellitus and nonmetastatic neoplasm (p < 0.01). The population-level analysis suggested that patients with mixed PNES and ES may be a population distinct from patients with either condition alone.

SIGNIFICANCE

An accurate patient-reported medical history and medication history can be useful when screening for possible PNES. Our prospectively validated and objective score may assist in the interpretation of the medication and medical history in the context of the seizure description and history.

ACNS Critical Care EEG Terminology: Value, Limitations, and Perspectives

The interpretation of the EEG in the critically ill remains a clinical challenge. Because continuous EEG monitoring plays an increasing role in patients' care, it is important that research efforts investigate the clinical significance of periodic and rhythmic discharges and of background abnormalities. The 2012 American Clinical Neurophysiology Society critical care EEG terminology was designed to provide a comprehensive and objective vocabulary for that purpose. The interrater reliability of most of the proposed terms has been established, confirming that they represent a solid basis for research. Studies using the terminology have already started to define the clinical and prognostic values of several known or newly described EEG patterns. Yet, as the field of critical care EEG evolves, improvements will be required to further enhance the clarity of the terminology and incorporate new findings from ongoing research.

Etiological associations and outcome predictors of acute electroencephalography in childhood encephalitis

OBJECTIVES

To examine EEG features in a retrospective 13-year cohort of children with encephalitis.

METHODS

354 EEGs from 119 patients during their admission were rated blind using a proforma with demonstrated inter-rater reliability (mean k=0.78). Patients belonged to 12 etiological groups that could be grouped into infectious and infection-associated (n=47), immune-mediated (n=36) and unknown (n=33). EEG features were analyzed between groups and for risk of abnormal Liverpool Outcome Score and drug resistant epilepsy (DRE) at last follow up.

RESULTS

86% children had an abnormal first EEG and 89% had at least one abnormal EEG. 55% had an abnormal outcome, and 13% had DRE after median follow-up of 7.3years (2.0-15.8years). Reactive background on first EEGs (9/11, p=0.04) and extreme spindles (4/11, p<0.001) distinguished patients with anti-N-Methyl-d-Aspartate Receptor encephalitis. Non-reactive EEG background (48% first EEGs) predicted abnormal outcome (OR 3.8, p<0.001). A shifting focal seizure pattern, seen in FIRES (4/5), anti-voltage gated potassium channel (2/3), Mycoplasma (1/10), other viral (1/10) and other unknown (1/28) encephalitis, was most predictive of DRE after multivariable analysis (OR 11.9, p<0.001).

CONCLUSIONS

Non-reactive EEG background and the presence of shifting focal seizures resembling migrating partial seizures of infancy are predictors of abnormal outcome and DRE respectively in childhood encephalitis.

SIGNIFICANCE

EEG is a sensitive but non-discriminatory marker of childhood encephalitis. We highlight the EEG features that predict abnormal outcome and DRE.

Generalized periodic discharges and 'triphasic waves': A blinded evaluation of inter-rater agreement and clinical significance

OBJECTIVES

Generalized periodic discharges (GPDs) are associated with nonconvulsive seizures. Triphasic waves (TWs), a subtype of GPDs, have been described in relation to metabolic encephalopathy and not felt to be associated with seizures. We sought to establish the consistency of use of this descriptive term and its association with seizures.

METHODS

11 experts in continuous EEG monitoring scored 20 cEEG samples containing GPDs using Standardized Critical Care EEG Terminology. In the absence of patient information, the inter-rater agreement (IRA) for EEG descriptors including TWs was assessed along with raters' clinical EEG interpretation and compared with actual patient information.

RESULTS

The IRA for 'generalized' and 'periodic' was near-perfect (kappa=0.81), but fair for 'triphasic' (kappa=0.33). Patients with TWs were as likely to develop seizures as those without (25% vs 26%, N.S.) and surprisingly, patients with TWs were less likely to have toxic-metabolic encephalopathy than those without TWs (55% vs 79%, p<0.01).

CONCLUSIONS

While IRA for the terms "generalized" and "periodic" is high, it is only fair for TWs. EEG interpreted as TWs presents similar risk for seizures as GPDs without triphasic appearance. GPDs are commonly associated with metabolic encephalopathy, but 'triphasic' appearance is not predictive.

SIGNIFICANCE

Conventional association of 'triphasic waves' with specific clinical conditions may lead to inaccurate EEG interpretation.

Abnormal neuronal response to rectal and anal stimuli in patients with idiopathic fecal incontinence

BACKGROUND

The pathophysiology behind idiopathic fecal incontinence (IFI) is poorly understood. We hypothesized abnormal sensory pathways along the brain-gut axis as a key player in this disease, reflected in cortical evoked potentials (CEP) from mechanical stimuli of the rectum and the anal canal.

METHODS

CEPs were recorded during repeated rapid balloon distensions of the rectum and anal canal in 19 women with IFI (mean age: 60 ± 14, mean Wexner score: 14.7 ± 2.9) and in 19 healthy women (mean age: 56 ± 11, mean Wexner score: 1.1 ± 1.3). Latencies, amplitudes and topography of CEPs elicited by rectal distension were compared between the groups. CEPs from both rectal and anal distensions were examined using spectral band analysis of single sweeps determining the relative amplitude of five spectral bands as a proxy of neuronal processing.

KEY RESULTS

Compared to controls IFI patients had prolonged latency of CEPs from rectal distension by up to 27% (p < 0.001) while amplitudes and topography were similar (all p > 0.7 and all p > 0.23). Spectral analysis of CEPs from rectal distensions showed no difference (all p > 0.1) between groups. However, analysis of CEPs following distension of the anal canal resulted in abnormally low activity in beta (8-12 Hz; p < 0.001) band and high activity in the gamma (32-70 Hz; p = 0.04) band in patients.

CONCLUSIONS & INFERENCES

IFI seems to be associated with impaired ano-rectal sensory functions in both the afferent fibers to the brain and the cortical processing of anal sensory pathways. This may play a central role for the pathogenesis of IFI.

A novel approach to pharmaco-EEG for investigating analgesics: assessment of spectral indices in single-sweep evoked brain potentials

AIMS

To compare results from analysis of averaged and single-sweep evoked brain potentials (EPs) by visual inspection and spectral analysis in order to identify an objective measure for the analgesic effect of buprenorphine and fentanyl.

METHODS

Twenty-two healthy males were included in a randomized study to assess the changes in EPs after 110 sweeps of painful electrical stimulation to the median nerve following treatment with buprenorphine, fentanyl or placebo patches. Bone pressure, cutaneous heat and electrical pain ratings were assessed. EPs and pain assessments were obtained before drug administration, 24, 48, 72 and 144 h after beginning of treatment. Features from EPs were extracted by three different approaches: (i) visual inspection of amplitude and latency of the main peaks in the average EPs, (ii) spectral distribution of the average EPs and (iii) spectral distribution of the EPs from single-sweeps.

RESULTS

Visual inspection revealed no difference between active treatments and placebo (all P > 0.05). Spectral distribution of the averaged potentials showed a decrease in the beta (12-32 Hz) band for fentanyl (P = 0.036), which however did not correlate with pain ratings. Spectral distribution in the single-sweep EPs revealed significant increases in the theta, alpha and beta bands for buprenorphine (all P < 0.05) as well as theta band increase for fentanyl (P = 0.05). For buprenorphine, beta band activity correlated with bone pressure and cutaneous heat pain (both P = 0.04, r = 0.90).

CONCLUSION

In conclusion single-sweep spectral band analysis increases the information on the response of the brain to opioids and may be used to identify the response to analgesics.

Interrater agreement for Critical Care EEG Terminology

OBJECTIVE

The interpretation of critical care electroencephalography (EEG) studies is challenging because of the presence of many periodic and rhythmic patterns of uncertain clinical significance. Defining the clinical significance of these patterns requires standardized terminology with high interrater agreement (IRA). We sought to evaluate IRA for the final, published American Clinical Neurophysiology Society (ACNS)-approved version of the critical care EEG terminology (2012 version). Our evaluation included terms not assessed previously and incorporated raters with a broad range of EEG reading experience.

METHODS

After reviewing a set of training slides, 49 readers independently completed a Web-based test consisting of 11 identical questions for each of 37 EEG samples (407 questions). Questions assessed whether a pattern was an electrographic seizure; pattern location (main term 1), pattern type (main term 2); and presence and classification of eight other key features ("plus" modifiers, sharpness, absolute and relative amplitude, frequency, number of phases, fluctuation/evolution, and the presence of "triphasic" morphology).

RESULTS

IRA statistics (κ values) were almost perfect (90-100%) for seizures, main terms 1 and 2, the +S modifier (superimposed spikes/sharp waves or sharply contoured rhythmic delta activity), sharpness, absolute amplitude, frequency, and number of phases. Agreement was substantial for the +F (superimposed fast activity) and +R (superimposed rhythmic delta activity) modifiers (66% and 67%, respectively), moderate for triphasic morphology (58%), and fair for evolution (21%).

SIGNIFICANCE

IRA for most terms in the ACNS critical care EEG terminology is high. These terms are suitable for multicenter research on the clinical significance of critical care EEG patterns. A PowerPoint slide summarizing this article is available for download in the Supporting Information section http://dx.doi.org/10.1111/epi.12653/supinfo.

Multimodal diagnosis of epilepsy using conditional dependence and multiple imputation

The definitive diagnosis of the type of epilepsy, if it exists, in medication-resistant seizure disorder is based on the efficient combination of clinical information, long-term video-electroencephalography (EEG) and neuroimaging. Diagnoses are reached by a consensus panel that combines these diverse modalities using clinical wisdom and experience. Here we compare two methods of multimodal computer-aided diagnosis, vector concatenation (VC) and conditional dependence (CD), using clinical archive data from 645 patients with medication-resistant seizure disorder, confirmed by video-EEG. CD models the clinical decision process, whereas VC allows for statistical modeling of cross-modality interactions. Due to the nature of clinical data, not all information was available in all patients. To overcome this, we multiply-imputed the missing data. Using a C4.5 decision tree, single modality classifiers achieved 53.1%, 51.5% and 51.1% average accuracy for MRI, clinical information and FDG-PET, respectively, for the discrimination between non-epileptic seizures, temporal lobe epilepsy, other focal epilepsies and generalized-onset epilepsy (vs. chance, p<0.01). Using VC, the average accuracy was significantly lower (39.2%). In contrast, the CD classifier that classified with MRI then clinical information achieved an average accuracy of 58.7% (vs. VC, p<0.01). The decrease in accuracy of VC compared to the MRI classifier illustrates how the addition of more informative features does not improve performance monotonically. The superiority of conditional dependence over vector concatenation suggests that the structure imposed by conditional dependence improved our ability to model the underlying diagnostic trends in the multimodality data.

Best-case kappa scores calculated retrospectively from EEG report databases

PURPOSE

The most popular metric for interrater reliability in electroencephalography is the kappa (κ) score. κ calculation is laborious, requiring EEG readers to read the same EEG studies. We introduce a method to determine the best-case κ score (κBEST) for measuring interrater reliability between EEG readers, retrospectively.

METHODS

We incorporated 1 year of EEG reports read by four adult EEG readers at our institution. We used SQL queries to determine EEG findings for subsequent analysis. We generated logistic regression models for particular EEG findings, dependent on patient age, location acuity, and EEG reader. We derived a novel measure, the κBEST statistic, from the logistic regression coefficients.

RESULTS

Increasing patient age and location acuity were associated with decreased sleep and increased diffuse abnormalities. For certain findings, EEG readers exhibited the dominant influence, manifesting directly as lower between-reader κBEST scores for certain EEG findings. Within-reader κBEST control scores were higher than between-reader scores, suggesting internal consistency.

CONCLUSIONS

The κBEST metric can measure significant interrater reliability differences between any number of EEG readers and reports, retrospectively, and is generalizable to other domains (e.g., pathology or radiology reporting). We suggest using this metric as a guide or starting point for focused quality control efforts.

Diagnostic delays in children with early onset epilepsy: impact, reasons, and opportunities to improve care

PURPOSE

Delayed diagnosis of early onset epilepsy is a potentially important and avoidable complication in epilepsy care. We examined the frequency of diagnostic delays in young children with newly presenting epilepsy, their developmental impact, and reasons for delays.

METHODS

Children who developed epilepsy before their third birthday were identified in a prospective community-based cohort. An interval ≥1 month from second seizure to diagnosis was considered a delay. Testing of development at baseline and for up to 3 years after and of intelligence quotient (IQ) 8-9 years later was performed. Detailed parental baseline interview accounts and medical records were reviewed to identify potential reasons for delays. Factors associated with delays included the parent, child, pediatrician, neurologist, and scheduling.

RESULTS

Diagnostic delays occurred in 70 (41%) of 172 children. Delays occurred less often if children had received medical attention for the first seizure (p < 0.0001), previously had neonatal or febrile seizures (p = 0.02), had only convulsions before diagnosis (p = 0.005), or had a college-educated parent (p = 0.01). A ≥1 month diagnostic delay was associated with an average 7.4 point drop (p = 0.02) in the Vineland Scales of Adaptive Behavior motor score. The effect was present at diagnosis, persisted for at least 3 years, and was also apparent in IQ scores 8-9 years later, which were lower in association with a diagnostic delay by 8.4 points (p = 0.06) for processing speed up to 14.5 points (p = 0.004) for full scale IQ, after adjustment for parental education and other epilepsy-related clinical factors. Factors associated with delayed diagnosis included parents not recognizing events as seizures (N = 47), pediatricians missing or deferring diagnosis (N = 15), neurologists deferring diagnosis (N = 7), and scheduling problems (N = 11).

SIGNIFICANCE

Diagnostic delays occur in many young children with epilepsy. They are associated with substantial decrements in development and IQ later in childhood. Several factors influence diagnostic delays and may represent opportunities for intervention and improved care.

A systematic review classifies sources of bias and variation in diagnostic test accuracy studies

OBJECTIVE

To classify the sources of bias and variation and to provide an updated summary of the evidence of the effects of each source of bias and variation.

STUDY DESIGN AND SETTING

We conducted a systematic review of studies of any design with the main objective of addressing bias or variation in the results of diagnostic accuracy studies. We searched MEDLINE, EMBASE, BIOSIS, the Cochrane Methodology Register, and Database of Abstracts of Reviews of Effects (DARE) from 2001 to October 2011. Citation searches based on three key papers were conducted, and studies from our previous review (search to 2001) were eligible. One reviewer extracted data on the study design, objective, sources of bias and/or variation, and results. A second reviewer checked the extraction.

RESULTS

We summarized the number of studies providing evidence of an effect arising from each source of bias and variation on the estimates of sensitivity, specificity, and overall accuracy.

CONCLUSIONS

We found consistent evidence for the effects of case-control design, observer variability, availability of clinical information, reference standard, partial and differential verification bias, demographic features, and disease prevalence and severity. Effects were generally stronger for sensitivity than for specificity. Evidence for other sources of bias and variation was limited.

Computer-Aided Diagnosis and Localization of Lateralized Temporal Lobe Epilepsy Using Interictal FDG-PET

Interictal FDG-PET (iPET) is a core tool for localizing the epileptogenic focus, potentially before structural MRI, that does not require rare and transient epileptiform discharges or seizures on EEG. The visual interpretation of iPET is challenging and requires years of epilepsy-specific expertise. We have developed an automated computer-aided diagnostic (CAD) tool that has the potential to work both independent of and synergistically with expert analysis. Our tool operates on distributed metabolic changes across the whole brain measured by iPET to both diagnose and lateralize temporal lobe epilepsy (TLE). When diagnosing left TLE (LTLE) or right TLE (RTLE) vs. non-epileptic seizures (NES), our accuracy in reproducing the results of the gold standard long term video-EEG monitoring was 82% [95% confidence interval (CI) 69-90%] or 88% (95% CI 76-94%), respectively. The classifier that both diagnosed and lateralized the disease had overall accuracy of 76% (95% CI 66-84%), where 89% (95% CI 77-96%) of patients correctly identified with epilepsy were correctly lateralized. When identifying LTLE, our CAD tool utilized metabolic changes across the entire brain. By contrast, only temporal regions and the right frontal lobe cortex, were needed to identify RTLE accurately, a finding consistent with clinical observations and indicative of a potential pathophysiological difference between RTLE and LTLE. The goal of CADs is to complement - not replace - expert analysis. In our dataset, the accuracy of manual analysis (MA) of iPET (∼80%) was similar to CAD. The square correlation between our CAD tool and MA, however, was only 30%, indicating that our CAD tool does not recreate MA. The addition of clinical information to our CAD, however, did not substantively change performance. These results suggest that automated analysis might provide clinically valuable information to focus treatment more effectively.

Interrater reliability of ICU EEG research terminology

BACKGROUND

Standardized research terminology critical to the establishment of a multicenter intensive care unit (ICU) electroencephalogram (EEG) database was originally proposed in 2005 and has been modified many times since. However, interrater agreement (IRA) of the revised terminology has not been investigated.

METHODS

After a brief tutorial, investigators of ICU EEG research centers (n = 16) took an 82-question EEG certification test comprising 10-second EEG samples, which assessed the use of main term 1 (pattern location), main term 2 (pattern type), and modifiers from the most recently revised terminology.

RESULTS

Kappa values for main terms 1 and 2 were 0.87 and 0.92, respectively. Agreement was 93% for determination of amplitude and 80% for determination of frequency. Kappa values for each of the "plus" modifiers (fast, rhythmic, and sharp/spike activity) were 0.54, 0.62, and 0.16 respectively.

CONCLUSIONS

Main terms 1 and 2 have high IRA and are reasonable for use in multicenter research. There is a suggestion that assessment of amplitude has good reliability, while assessment of frequency may have less reliability. The fast and rhythmic "plus" modifiers have moderate IRA, while sharp/spike modifier has only slight IRA implying that further refinement and assessment of terminology modifiers may be necessary.

Automated diagnosis of epilepsy using EEG power spectrum

Interictal electroencephalography (EEG) has clinically meaningful limitations in its sensitivity and specificity in the diagnosis of epilepsy because of its dependence on the occurrence of epileptiform discharges. We have developed a computer-aided diagnostic (CAD) tool that operates on the absolute spectral energy of the routine EEG and has both substantially higher sensitivity and negative predictive value than the identification of interictal epileptiform discharges. Our approach used a multilayer perceptron to classify 156 patients admitted for video-EEG monitoring. The patient population was diagnostically diverse; 87 were diagnosed with either generalized or focal seizures. The remainder of the patients were diagnosed with nonepileptic seizures. The sensitivity was 92% (95% confidence interval [CI] 85-97%) and the negative predictive value was 82% (95% CI 67-92%). We discuss how these findings suggest that this CAD can be used to supplement event-based analysis by trained epileptologists.

Updates and future horizons on the understanding, diagnosis, and treatment of Sturge-Weber syndrome brain involvement

AIM

To review recent developments in the understanding, diagnosis, and treatment of Sturge-Weber syndrome (SWS).

METHOD

Members of the Brain Vascular Malformation Consortium Sturge-Weber Syndrome National Workgroup contributed their expertise to review the literature and present promising directions for research.

RESULTS

The increasing number of reports dealing with SWS over the last decade reflects progress in the diagnosis and understanding of the neurological involvement. The proliferation of centers and advocacy groups to care for patients with SWS and to stimulate research has aided the development of new insights into the clinical manifestations and the pathophysiology of neurological progression, and the development of novel hypotheses to direct future research. Many key questions remain, but the tools and networks to answer them are being developed.

INTERPRETATION

This review summarizes important new knowledge and presents new research directions that are likely to provide further insights, earlier diagnosis, improved treatments, and possibly, prevention of this syndrome.

The role of the interictal EEG in selecting candidates for resective epilepsy surgery

The interictal EEG is a noninvasive and useful test for selecting candidates for resective epilepsy surgery, although it has many pitfalls. It is an essential test for the most common drug-resistant epilepsy, mesial temporal sclerosis, and predicts good outcome when interictal epileptiform discharges are concordant with unilateral hippocampal atrophy or sclerosis, and predicts poor outcome when interictal epileptic discharges are discordant with the lesion. Its role in other types of epilepsy surgery, including nonlesional cases and corpus callosotomy, is less clear. Future research gathering large multicenter prospective data is needed to maximize the role of this classic neurophysiological test in the evaluation of candidates for epilepsy surgery.

A guide to disorders causing transient loss of consciousness: focus on syncope

Episodes of transient loss of consciousness (TLOC) events pose diagnostic difficulties, as the causes are diverse, carry vastly different risks, and span various specialties. An inconsistent terminology contributes to the confusion. Here, we present a classification scheme for TLOC, based on ongoing multidisciplinary efforts including those of the Task Force on Syncope of the European Society of Cardiology. We also discuss the pathophysiology of TLOC and the key clinical features that aid diagnosis. TLOC is defined as an apparent loss of consciousness with an abrupt onset, a short duration, and a spontaneous and complete recovery. Syncope is defined as TLOC due to cerebral hypoperfusion, and is divided into reflex syncope (synonymous with neurally mediated syncope), syncope due to orthostatic hypotension, and cardiac syncope (arrhythmic or associated with structural cardiac disease). The other major groups of TLOC are generalized epileptic seizures, functional TLOC (psychogenic TLOC mimicking either epilepsy or syncope), and a further group of miscellaneous disorders. The management of patients who experience TLOC requires the recognition of the defining features of each of the major groups, and cooperation between different clinical specialties.

Effects of sleep deprivation on the pediatric electroencephalogram

BACKGROUND

The routine electroencephalogram aids in epilepsy syndrome diagnosis. Unfortunately, routine outpatient electroencephalogram results are normal in roughly half of children with epilepsy. To increase the yield, practice guidelines recommend electroencephalograms with sleep and sleep deprivation. The purpose of this study was to rigorously evaluate this recommendation in children.

METHODS

We conducted a randomized, blinded comparison of routine electroencephalograms versus sleep-deprived electroencephalograms in 206 children aged 0 to 18 years. Electroencephalograms were ordered for standard indications after a neurologist's clinical assessment indicated > or =1 seizure (83%) or unclear spell (17%). The primary outcome was the proportion of normal routine electroencephalogram results versus sleep-deprived electroencephalogram results. Logistic regression modeling was used to assess the influence of sleep, as well as other clinical factors.

RESULTS

Although children with sleep-deprived electroencephalograms had less sleep the night before (4.9 vs 7.9 hours) and more sleep during electroencephalograms (73% vs 55%), the increase in electroencephalogram yield was borderline significant (56% normal sleep-deprived electroencephalogram versus 68% normal routine electroencephalogram). Moreover, sleep during the electroencephalogram did not increase its diagnostic yield. Sleep-deprived electroencephalogram yield tended to be higher in children with preelectroencephalogram clinical diagnosis of seizure(s) and at older ages (>3 years).

CONCLUSIONS

Sleep deprivation, but not sleep during the electroencephalogram, modestly increases the yield of the electroencephalogram in children diagnosed with seizures by neurologists. Compared with a routine electroencephalogram, the number needed to test with sleep-deprived electroencephalogram to identify 1 additional child with epileptiform discharges is approximately 11.

Interobserver agreement in the interpretation of EEG patterns in critically ill adults

The significance of rhythmic and periodic EEG patterns in critically ill patients is unclear. A universal terminology is needed to facilitate study of these patterns, and consistent observer agreement should be demonstrated in its use. The authors evaluated inter- and intraobserver agreement using the standardized terminology (Hirsch et al., J Clin Neurophysiol 2005;22:128-135) recently proposed by the American Clinical Neurophysiology Society. Trained electroencephalographers viewed a series of 10-second EEG samples from critically ill adults (phase I), a set of >/=20-minute EEGs from the same patient cohort (phase II), and then reevaluated the first sample set (phase III). The readers used the proposed terminology to "score" each EEG. For each possible term, interobserver agreement (phases I and II) and intraobserver agreement (phase III) were calculated using pairwise kappa (kappa) values. Moderate agreement beyond chance was seen for the presence/absence of rhythmic or periodic patterns and for localization of these patterns. Agreement for other terms was slight to fair. Inter- and intraobserver agreement were consistently lower for optional terms than mandatory terms. Even when standardized terminology is used, the description of rhythmic and periodic EEG patterns varies significantly. Further refinement of the proposed terminology is required to improve inter- and intraobserver agreement.

Latency to first spike in the EEG of epilepsy patients

BACKGROUND

Routine EEGs in individuals with epilepsy have interictal spikes in 56% of cases. The availability of prolonged EEG has changed the use of EEG in the assessment of epilepsy.

OBJECTIVE

To determine the time to first epileptiform activity on EEG in patients with epilepsy. This data will help optimize the duration of electrographic assessment for interictal activity in epileptic individuals.

METHODS

46 consecutive patients aged 10 years or older with epilepsy were evaluated. Individuals with seizures in the prior 24h or with acute symptomatic seizures were excluded. Continuous EEG (for 1-7 days) was analyzed to find the first definite epileptiform activity and the latency assessed.

RESULTS

37% of the patients had epileptiform activity in the first 20min of the continuous recording (duration of a routine EEG). 89% had epileptiform activity within 24h. The yield drops beyond 24h. 8% of the individuals had no epileptiform activity even after 72h.

CONCLUSIONS

The study suggests the need to consider a change in EEG strategy to assess interictal epileptiform activity. The greatest probability of capturing an interictal abnormality within 20min was in individuals with generalized epilepsy. In individuals with suspected epilepsy in whom electrographic interictal spike confirmation is deemed necessary, after a first nonspecific or normal routine EEG, a 24h EEG should be the next step in the electrographic assessment. This study suggests that there may not be much benefit in monitoring for durations longer than 24h, unless capturing a seizure is the intent.

How confident are we of the diagnosis of epilepsy?

The diagnosis of a first seizure or epilepsy may be subject to interobserver variation and inaccuracy with possibly far-reaching consequences for the patients involved. We reviewed the current literature. Studies on the interobserver variation of the diagnosis of a first seizure show that such a diagnosis is subject to considerable interobserver disagreement. Interpretation of the electroencephalogram (EEG) findings is also subject to interobserver disagreement and is influenced by the threshold of the reader to classify EEG findings as epileptiform. The accuracy of the diagnosis of epilepsy varies from a misdiagnosis rate of 5% in a prospective childhood epilepsy study in which the diagnosis was made by a panel of three experienced pediatric neurologists to at least 23% in a British population-based study, and may be even higher in everyday practice. The level of experience of the treating physician plays an important role. The EEG may be helpful but one should be reluctant to make a diagnosis of epilepsy mainly on the EEG findings without a reasonable clinical suspicion based on the history. Being aware of the possible interobserver variation and inaccuracy, adopting a systematic approach to the diagnostic process, and timely referral to specialized care may be helpful to prevent the misdiagnosis of epilepsy.

Treatment of children and adolescents with tics and Tourette syndrome

Tics, patterned movements distinct from stereotypies, myoclonus, and other hyperkinetic movements, are quite common in children, particularly among those with developmental and psychiatric disorders. Thus, tics can indicate the presence of atypical neurodevelopment or broader difficulties with cognition or mood. Tics are also the cardinal feature of Tourette syndrome, a childhood-onset neurobehavioral disorder characterized by a chronic inability to suppress or an urge to perform patterned, repetitive movements. Patients with Tourette syndrome most commonly have, in addition to tics, symptoms of inattention, hyperactivity, obsessiveness, or anxiety. Achieving the most effective treatment of a child with tics is contingent on proper diagnosis of the movement disorder and thorough assessment for other problems, followed by consideration of both nonpharmacologic and pharmacologic interventions for any and all symptoms interfering with the child's function and quality of life. This review focuses primarily on the diagnosis and medical treatment of tics in children and adolescents with Tourette syndrome.

Diagnosing epilepsy

We know how important it is to diagnose epilepsy correctly, but how to do so is surprisingly little validated. An inadequate history and misinterpretation of the electroencephalogram (EEG) are the major reasons 4 to 26% of children and adults in European studies are misdiagnosed with epilepsy. Error rates are not available for most countries, or for more precise diagnoses of seizure types, epilepsy syndrome, and cause.

Predictors of epilepsy surgery outcome: a meta-analysis

The potential efficacy of temporal and extratemporal resection in patients with partial epilepsy uncontrolled by anti-epileptic drugs is undisputed. However, there are still uncertainties about which patients will benefit most. A systematic review of the available literature has been undertaken by four pairs of reviewers to assess the overall outcome of epilepsy surgery and to identify factors better correlated to seizure outcome. A Medline search for studies on epilepsy surgery published since 1984 was performed. Studies were included if they had a well-defined population and design, a sample size of at least 30 patients, an MRI performed in least 90% of cases, an expected duration of follow-up of at least one year, and a post-operative outcome measured as seizure remission. A good outcome was considered as seizure control or seizure-free status for at least one year or Engel class I. Based on the review of 47 articles meeting all the eligibility criteria, febrile seizures (odds ratio, OR, 0.48; 95% confidence interval, CI, 0.27-0.83), mesial temporal sclerosis (OR 0.47; 95% CI 0.35-0.64), tumors (OR 0.58; 95% CI 0.42-0.80), abnormal MRI (OR 0.44; 95% CI 0.29-0.65), EEG/MRI concordance (OR 0.52; 95% CI 0.32-0.83), and extensive surgical resection (OR 0.24; 95% CI 0.16-0.36) were the strongest prognostic indicators of seizure remission (positive predictors); by contrast, post-operative discharges (OR 2.41; 95% CI 1.37-4.27) and intracranial monitoring (OR 2.72; 95% CI 1.60-4.60) predicted an unfavorable prognosis (negative predictors). Firm conclusions cannot be drawn for extent of resection, EEG/MRI concordance and post-operative discharges for the heterogeneity of study results. Neuromigrational defects, CNS infections, vascular lesions, interictal spikes, and side of resection did not affect the chance of seizure remission after surgery. Despite a number of limitations, the results of the review provide some insight into the selection of the best surgical candidates in clinical practice but raise concerns on the quality of published reports, and may serve as the basis for the identification of better standards to assess surgical outcome in observational studies.