Electroencephalographic (EEG) features may provide objective data regarding prognosis in children resuscitated from cardiac arrest (CA), but therapeutic hypothermia (TH) may impact its predictive value. We aimed to determine whether specific EEG features were predictive of short-term outcome in children treated with TH after CA, both during hypothermia and after return to normothermia.
Thirty-five children managed with a standard clinical TH algorithm after CA were prospectively enrolled. EEG recordings were scored in a standardized manner and categorized. EEG category 1 consisted of continuous and reactive tracings. EEG category 2 consisted of continuous but unreactive tracings. EEG category 3 included those with any degree of discontinuity, burst suppression, or lack of cerebral activity. The primary outcome was unfavorable short-term outcome defined as Pediatric Cerebral Performance Category score of 4–6 (severe disability, vegetative, death) at hospital discharge. Univariate analyses of the association between EEG category and outcome was performed using logistic regression.
For tracings obtained during hypothermia, patients with EEGs in categories 2 or 3 were far more likely to have poor outcome than those in category 1 (OR 10.7, P = 0.023 and OR 35, P = 0.004, respectively). Similarly, for tracings obtained during normothermia, patients with EEGs in categories 2 or 3 were far more likely to have poor outcomes than those in category 1 (OR 27, P = 0.006 and OR 18, P = 0.02, respectively).
A simple EEG classification scheme has predictive value for short-term outcome in children undergoing TH after CA.
Therapeutic hypothermia; Outcome; Pediatric; Hypoxic ischemic encephalopathy; Heart arrest; Prognosis
Hypoxic ischemic brain injury secondary to pediatric cardiac arrest (CA) may result in acute symptomatic seizures. A high proportion of seizures may be nonconvulsive, so accurate diagnosis requires continuous EEG monitoring. We aimed to determine the safety and feasibility of long-term EEG monitoring, to describe electroencephalographic background and seizure characteristics, and to identify background features predictive of seizures in children undergoing therapeutic hypothermia (TH) after CA.
Nineteen children underwent TH after CA. Continuous EEG monitoring was performed during hypothermia (24 hours), rewarming (12–24 hours), and then an additional 24 hours of normothermia. The tolerability of these prolonged studies and the EEG background classification and seizure characteristics were described in a standardized manner.
No complications of EEG monitoring were reported or observed. Electrographic seizures occurred in 47% (9/19), and 32% (6/19) developed status epilepticus. Seizures were nonconvulsive in 67% (6/9) and electrographically generalized in 78% (7/9). Seizures commenced during the late hypothermic or rewarming periods (8/9). Factors predictive of electrographic seizures were burst suppression or excessively discontinuous EEG background patterns, interictal epileptiform discharges, or an absence of the expected pharmacologically induced beta activity. Background features evolved over time. Patients with slowing and attenuation tended to improve, whereas those with burst suppression tended to worsen.
EEG monitoring in children undergoing therapeutic hypothermia after cardiac arrest is safe and feasible. Electrographic seizures and status epilepticus are common in this setting but are often not detectable by clinical observation alone. The EEG background often evolves over time, with milder abnormalities improving and more severe abnormalities worsening.
= burst suppression;
= cardiac arrest;
= cardiopulmonary resuscitation;
= developmental delay;
= hypoxic ischemic encephalopathy;
= nonconvulsive seizures;
= nonconvulsive status epilepticus;
= negative predictive value;
= periodic epileptiform discharge;
= pediatric intensive care unit;
= positive predictive value;
= status epilepticus;
= sudden infant death syndrome;
= therapeutic hypothermia;
= valproic acid;
= ventricular tachycardia.
Retrospective studies have reported the occurrence of nonconvulsive seizures in critically ill children. We aimed to prospectively determine the incidence and risk factors of nonconvulsive seizures in critically ill children using predetermined EEG monitoring indications and EEG interpretation terminology.
Critically ill children (non-neonates) with acute encephalopathy underwent continuous EEG monitoring if they met institutional clinical practice criteria. Study enrollment and data collection were prospective. Logistic regression analysis was utilized to identify risk factors for seizure occurrence.
One hundred children were evaluated. Electrographic seizures occurred in 46 and electrographic status epilepticus occurred in 19. Seizures were exclusively nonconvulsive in 32. The only clinical risk factor for seizure occurrence was younger age (p = 0.03). Of patients with seizures, only 52% had seizures detected in the first hour of monitoring, while 87% were detected within 24 hours.
Seizures were common in critically ill children with acute encephalopathy. Most were nonconvulsive. Clinical features had little predictive value for seizure occurrence. Further study is needed to confirm these data in independent high-risk populations, to clarify which children are at highest risk for seizures so limited monitoring resources can be allocated optimally, and to determine whether seizure detection and management improves outcome.
Background and Purpose:
This study aimed to determine whether preoperative or postoperative electroencephalography (EEG) can predict surgical outcome for corpus callosotomy.
We retrospectively reviewed the medical records of 16 patients enrolled. We compared postoperative seizure outcome according to seizure type, preoperative interictal EEG, preoperative ictal EEG, and postoperative interictal EEG. Seizure outcome was classified according to postoperative seizure reduction, i.e., seizure free, >90%, 50–90%, <50%, and no change or worsened. A seizure reduction of 50% or more was judged as a “favorable outcome”.
Most patients showed a favorable outcome (12 patients, 75%) and two patients became seizure free (13%). Atonic seizure was most responsive to corpus callosotomy. Preoperative interictal epileptiform discharge had 3 patterns; bilateral independent, generalized, and combination of independent and generalized. None of the preoperative interictal epileptiform discharge (EDs) had significant correlation with seizure outcome. The preoperative ictal rhythm did not predict seizure outcome. However disappearance of generalized EDs on postoperative EEG was correlated with favorable seizure outcome.
The presence of generalized EDs on postoperative interictal EEG predicted seizure outcome, whereas preoperative EEG did not.
Corpus callosum/surgery; Electroencephalography; Epilepsy/surgery; Child
Develop a real-time algorithm to automatically discriminate suppressions from non-suppressions (bursts) in electroencephalograms of critically ill adult patients.
A real-time method for segmenting adult ICU EEG data into bursts and suppressions is presented based on thresholding local voltage variance. Results are validated against manual segmentations by two experienced human electroencephalographers. We compare inter-rater agreement between manual EEG segmentations by experts with inter-rater agreement between human vs automatic segmentations, and investigate the robustness of segmentation quality to variations in algorithm parameter settings. We further compare the results of using these segmentations as input for calculating the burst suppression probability (BSP), a continuous measure of depth-of-suppression.
Automated segmentation was comparable to manual segmentation, i.e. algorithm-vs-human agreement was comparable to human-vs-human agreement, as judged by comparing raw EEG segmentations or the derived BSP signals. Results were robust to modest variations in algorithm parameter settings.
Our automated method satisfactorily segments burst suppression data across a wide range adult ICU EEG patterns. Performance is comparable to or exceeds that of manual segmentation by human electroencephalographers.
Automated segmentation of burst suppression EEG patterns is an essential component of quantitative brain activity monitoring in critically ill and anesthetized adults. The segmentations produced by our algorithm provide a basis for accurate tracking of suppression depth.
Burst suppression; Medically-induced coma; Quantitative EEG; ICU EEG monitoring
High doses of dextromethorphan (20-42 mg/kg/day) were given to four critically ill children with seizures and frequent epileptiform abnormalities in the EEG that were refractory to antiepileptic drugs. Their acute diseases (hypoxia, head trauma and hypoxia, neurodegenerative disease, hypoglycaemia) were thought to be due in part to N-methyl-D-aspartate (NMDA) receptor mediated processes. Treatment with dextromethorphan, an NMDA receptor antagonist, was started between 48 hours and 14 days after the critical incident. In three patients the EEG improved considerably within 48 hours and seizures ceased within 72 hours. In the patient with neurodegenerative disease the effect on the EEG was impressive, but the seizures were not controlled. Despite the improvement of the EEG the clinical outcome was poor in all children: three died in the critical period or due to the progressing disease; the patient with hypoglycaemia survived with severe neurological sequelae. Plasma concentrations of dextromethorphan varied between 74-1730 ng/ml and its metabolite dextrorphan varied between 349-3790 ng/ml. In one patient corresponding concentrations in CSF were lower than those in plasma. The suppression of epileptic discharges by the doses of dextromethorphan given suggests that such doses are sufficient to block NMDA receptors.
Methods: MEG and simultaneous EEG were recorded with a 204 channel whole head MEG system. Ten habitual seizures occurred during the acquisition, which was done twice. The equivalent current dipoles (ECDs) for ictal discharges on MEG were calculated using a single dipole model. The ECDs were superimposed on a magnetic resonance image.
Results: During the seizures, EEG showed prolonged bursts of 5–6 Hz high voltage slow waves with spike components, dominantly in the bilateral frontal region. MEG showed epileptiform discharges corresponding to the ictal EEG. Ictal discharges on MEG were dominant in the frontal area in the initial portion, and then spread in the bilateral temporal area in the middle of the seizure. ECDs obtained from the spikes of the initial portion were clustered in the medial frontal lobe.
Conclusions: The source of the ictal MEG was localised in the medial frontal lobe. The findings suggest that the mechanism underlying epilepsy in this case might be similar to medial frontal lobe epilepsy. Ictal MEG is a valuable tool for detecting the site of seizure onset.
BI-RADS was first developed in 1993 for mammography and in 2003 it was redesigned for ultrasonography (US). If the observer agreement is high, the method used in the classification of lesion would be reproducible.
The aim of this study is to evaluate the inter- and intraobserver agreement of sonographic BI-RADS lexicon in the categorization and feature characterization of nonpalpable breast lesions.
Patients and Methods
We included 223 patients with 245 nonpalpable breast lesions who underwent ultrasound-guided wire needle localization. Two radiologists retrospectively described each lesion using sonographic BI-RADS descriptors and final assessment. The observers were blinded to mammographic images, medical history and pathologic results. Inter- and intraobserver agreement was assessed using Kappa (κ) agreement coefficient.
The interobserver agreement for sonographic descriptors changed between fair and substantial. The highest agreement was detected for mass orientation (κ=0.66). The lowest agreement was found in the margin (κ=0.33). The interobserver agreement for BI-RADS final category was found as fair (κ=0.35). The intraobserver agreement for sonographic descriptors changed between substantial and almost perfect. The intraobserver agreement of BI-RADS result category was found as substantial for observer 1 (κ=0.64) and excellent for observer 2 (κ=0.83).
Our results demonstrated that each observer was self-consistent in interpreting US BI-RADS classification, while interobserver agreement was relatively poor. Although it has been ten years since the description of sonographic BI-RADS lexicon, further training and periodic performance evaluations would probably help to achieve better agreement among radiologists.
Mammography; Breast; Ultrasonography
To quantify the ictal subdural electroencephalogram (EEG) changes using spectral analysis, and to delineate the quantitatively defined ictal onset zones on high-resolution 3D MR images in children with intractable neocortical epilepsy.
Fourteen children with intractable neocortical epilepsy (age: 1–16 years) who had subsequent resective surgery were retrospectively studied. The subjects underwent a high-resolution MRI and prolonged subdural EEG recording. Spectral analysis was applied to 3 habitual focal seizures. After fast Fourier transformation of the EEG epoch at ictal onset, an amplitude spectral curve (square root of the power spectral curve) was created for each electrode. The EEG magnitude of ictal rhythmic discharges was defined as the area under the amplitude spectral curve within a preset frequency band including the ictal discharge frequency, and calculated for each electrode. The topography mapping of ictal EEG magnitude was subsequently displayed on a surface-rendered MRI. Finally, receiver operating characteristic (ROC) analysis was performed to evaluate the consistency between quantitatively and visually defined ictal onset zones.
The electrode showing the maximum of the averaged ictal EEG magnitude was part of the visually defined ictal onset zone in all cases. ROC analyses demonstrated that electrodes showing >30% of the maximum of the averaged ictal EEG magnitude had a specificity of 0.90 and a sensitivity of 0.74 for the concordance with visually defined ictal onset zones.
Quantitative ictal subdural EEG analysis using spectral analysis may supplement conventional visual inspection in children with neocortical epilepsy by providing an objective definition of the onset zone and its simple visualization on the patient’s MRI.
Clinical neurophysiology; Pediatric epilepsy surgery; Quantitative ictal intracranial electroencephalography; Focal cortical dysplasia; Tuberous sclerosis complex
To develop standardized definitions for classification of partial seizure symptoms for use in genetic research on the epilepsies, and evaluate inter-rater reliability of classifications based on these definitions.
The authors developed the Partial Seizure Symptom Definitions (PSSD), which include standardized definitions of 41 partial seizure symptoms within the sensory, autonomic, aphasic, psychic, and motor categories. Based on these definitions, two epileptologists independently classified partial seizures in 75 individuals from 34 families selected because one person had ictal auditory symptoms or aphasia. The data used for classification consisted of standardized diagnostic interviews with subjects and family informants, and medical records obtained from treating neurologists. Agreement was assessed by kappa.
Agreement between the two neurologists using the PSSD was “substantial” or “almost perfect” for most symptom categories.
Use of standardized definitions for classification of partial seizure symptoms such as those in the Partial Seizure Symptom Definitions should improve reliability and accuracy in future genetic studies of the epilepsies.
Electroencephalography (EEG) has an important role in the diagnosis and classification of epilepsy. It can provide information for predicting the response to antiseizure drugs and to identify the surgically remediable epilepsies. In temporal lobe epilepsy (TLE) seizures could originate in the medial or lateral neocortical temporal region, and many of these patients are refractory to medical treatment. However, majority of patients have had excellent results after surgery and this often relies on the EEG and magnetic resonance imaging (MRI) data in presurgical evaluation. If the scalp EEG data is insufficient or discordant, invasive EEG recording with placement of intracranial electrodes could identify the seizure focus prior to surgery. This paper highlights the general information regarding the use of EEG in epilepsy, EEG patterns resembling epileptiform discharges, and the interictal, ictal and postictal findings in mesial temporal lobe epilepsy using scalp and intracranial recordings prior to surgery. The utility of the automated seizure detection and computerized mathematical models for increasing yield of non-invasive localization is discussed. This paper also describes the sensitivity, specificity, and predictive value of EEG for seizure recurrence after withdrawal of medications following seizure freedom with medical and surgical therapy.
Electroencephalography (EEG) occupies an important place for studying human brain activity in general, and epileptic processes in particular, with appropriate time resolution. Scalp EEG or intracerebral EEG signals recorded in patients with drug-resistant partial epilepsy convey important information about epileptogenic networks that must be localized and understood prior to subsequent therapeutic procedures. However, this information, often subtle, is ‘hidden’ in the signals. It is precisely the role of signal processing to extract this information and to put it into a ‘coherent and interpretable picture’ that can participate in the therapeutic strategy. Nowadays, the panel of available methods is very wide depending on the objectives such as, for instance, the detection of transient epileptiform events, the detection and/or prediction of seizures, the recognition and/or the classification of EEG patterns, the localization of epileptic neuronal sources, the characterization of neural synchrony, the determination of functional connectivity, among others. The intent of this paper is to focus on a specific category of methods providing relevant information about epileptogenic networks from the analysis of spatial properties of EEG signals in the time and frequency domain. These methods apply to either interictal or ictal recordings and share the common objective of localizing the subsets of brain structures involved in both types of paroxysmal activity. Most of these methods were developed by our group and are routinely used during pre-surgical evaluation. Examples are detailed. Results, as well as limitations of the methods, are also discussed.
electroencephalography; intracerebral; epilepsy; interictal; ictal; statistical signal processing
Electroencephalography (EEG) occupies an important place for studying human brain activity in general, and epileptic processes in particular, with appropriate time resolution. Scalp-EEG or intracerebral-EEG signals recorded in patients with drug-resistant partial epilepsy convey important information about epileptogenic networks that must be localized and understood prior to subsequent therapeutic procedure. However, this information, often subtle, is “hidden” into the signals. It is precisely the role of signal processing to extract this information and to put it into a “coherent and interpretable picture” that can participate into the therapeutic strategy. Nowadays, the panel of available methods is very wide depending on the objectives like, for instance, the detection of transient epileptiform events, the detection and/or prediction of seizures, the recognition and/or the classification of EEG patterns, the localization of epileptic neuronal sources, the characterization of neural synchrony, the determination of functional connectivity, among others. The intent of this paper is to focus on a specific category of methods providing relevant information about epileptogenic networks from the analysis of spatial properties of EEG signals in the time and frequency domain. These methods apply either to interictal or to ictal recordings and share the common objective of localizing the subsets of brain structures involved in both types of paroxysmal activity. Most of these methods were developed by our group and are routinely used during pre-surgical evaluation. Examples are detailed. Results, as well as limitations of the methods, are also discussed.
Algorithms; Amygdala; physiopathology; Automatic Data Processing; Brain; physiopathology; Electroencephalography; statistics & numerical data; Epilepsies, Partial; physiopathology; Hippocampus; physiopathology; Humans; Models, Anatomic; Nerve Net; Regression Analysis; Signal Processing, Computer-Assisted; Electroencephalography; intracerebral; epilepsy; interictal; ictal; statistical signal processing; spike detection; bivariate analysis; time-frequency analysis
In the diagnostic microbiology laboratory, interpretation of Gram-stained slides of vaginal swab specimens is used to support the clinical diagnosis of bacterial vaginosis. The reproducibility with which technologists interpret these Gram-stained slides was evaluated by presenting, in coded fashion, 80 original slides and 80 duplicate slides of vaginal swab specimens to three technologists. They each interpreted the original slide twice and the duplicate slide from the same specimen once. Intraobserver and interobserver agreement was assessed by use of the weighted kappa statistic. Semiquantitation of Lactobacillus and Gardnerella morphotypes and a diagnosis of bacterial vaginosis showed the greatest intraobserver agreement, with kappa values ranging from 0.772 to 1.000. Interobserver agreement was also high for rating Lactobacillus morphotypes and clue cells (kappa values between 0.735 and 0.869) but decreased slightly for Gardnerella morphotypes and a diagnosis of bacterial vaginosis (kappa values between 0.656 and 0.800). These results indicate that there is good agreement for the interpretation of Gram-stained slides of vaginal swab specimens and that this method alone, without culture, can be used reliably to support the clinical diagnosis of bacterial vaginosis.
It has been proposed that intensive care unit (ICU)-acquired weakness (ICUAW) should be assessed using the sum of manual muscle strength test scores in 12 muscle groups (the sum score). This approach has been tested in patients with Guillain-Barré syndrome, yet little is known about the feasibility or test characteristics in other critically ill patients. We studied the feasibility and interobserver agreement of this sum score in a mixed cohort of critically ill and injured patients.
We enrolled patients requiring more than 3 days of mechanical ventilation. Two observers performed systematic strength assessments of each patient. The primary outcome measure was interobserver agreement of weakness as a binary outcome (ICUAW is sum score less than 48; "no ICUAW" is a sum score greater than or equal to 48) using the Cohen's kappa statistic.
We identified 135 patients who met the inclusion criteria. Most were precluded from study participation by altered mental status or polytrauma. Thirty-four participants were enrolled, and 30 of these individuals completed assessments conducted by both observers. Six met the criteria for ICUAW recorded by at least one observer. The observers agreed on the diagnosis of ICUAW for 93% of participants (Cohen's kappa = 0.76; 95% confidence interval (CI), 0.44 to 1.0). Observer agreement was fair in the ICU (Cohen's kappa = 0.38), and agreement was perfect after ICU discharge (Cohen's kappa = 1.0). Absolute values of sum scores were similar between observers (intraclass correlation coefficient 0.83; 95% CI, 0.67 to 0.91), but they differed between observers by six points or more for 23% of the participants.
Manual muscle testing (MMT) during critical illness was not possible for most patients because of coma, delirium and/or injury. Among patients who were able to participate in testing, we found that interobserver agreement regarding ICUAW was good, particularly when evaluated after ICU discharge. MMT is insufficient for early detection of ICU-acquired neuromuscular dysfunction in most patients and may be unreliable during critical illness.
We examined 114 segments in 23 patients' lumbar spine plain radiographs affected by disc degeneration. Two consultant orthopaedic surgeons, two consultant radiologists, and one spine nurse practitioner made independent observations on the radiographs. MRI scan films of the corresponding 114 segments were used as a gold standard. Kappa coefficients were used to evaluate the interobserver error, and the error between the independent observers and the MRI scanning reports. The systematic differences between the observers for the diagnosis of the disc degeneration at each segment level was recorded.
There was significant interobserver error between the independent observers. The pairwise interobserver agreement ranged from fair to substantial on the plain radiograph observations [Weighted kappa coefficient, mean: 0.517 (CI=0.388-0.646)]. The pairwise interobserver agreement between the independent observers and the MRI scan ranged from fair to moderate [Weighted kappa coefficient, mean: 0.388 (CI=0.259-0.518)].
There is significant error in interpretation of the plain radiographs for the diagnosis of lumbar disc degeneration. MRI may be more accurate in the diagnosis of lumbar disc degeneration.
Functional hemispherectomy is effective in carefully selected patients, resulting in a reduction of seizure burden up to complete resolution, improvement of intellectual development, and developmental benefit despite possible additional neurological deficit. Despite apparent hemispheric pathology on brain magnetic resonance imaging (MRI) or other imaging tests, scalp electroencephalography (EEG) could be suggestive of bilateral ictal onset or even ictal onset contralateral to the dominant imaging abnormality. We aimed to investigate the role of scalp EEG lateralization pre-operatively in predicting outcome.
We retrospectively reviewed 54 patients who underwent hemispherectomy between 1991 and 2009 at Medical College of Georgia (1991–2006) and Cincinnati Children’s Hospital Medical Center (2006–2009) and had at least one year post-operative follow-up. All preoperative EEGs were reviewed, and classified as either lateralizing or nonlateralizing, for both ictal and interictal EEG recordings.
Of 54 patients, 42 (78%) became seizure free. Twenty-four (44%) of 54 had a nonlateralizing ictal or interictal EEG. Further analysis was based on etiology of epilepsy, including malformation of cortical development (MCD), Rasmussen syndrome (RS), and stroke (CVA). EEG nonlateralization did not predict poor outcome in any of the etiology groups evaluated.
Scalp EEG abnormalities in contralateral or bilateral hemispheres do not, in isolation, predict a poor outcome from hemispherectomy. Results of other non-invasive and invasive evaluations should be used to determine candidacy.
Hemispherectomy; Hemispherotomy; EEG; Bilateral; Outcome
Background: The cerebral function monitor (CFM) is widely used to detect neonatal seizures, but there are very few studies comparing it with simultaneous electroencephalography (EEG).
Objective: To determine the accuracy of non-expert use of the CFM and to assess interobserver agreement of CFM seizure detection.
Patients: Babies admitted to the neonatal intensive care unit at King's College Hospital who were at high risk of seizure and had video-EEG monitoring.
Methods: Video-EEG was used to detect seizures. Each baby had CFM recordings at speeds of 6, 15, and 30 cm/h during the EEG. Four neonatologists, trained in CFM seizure recognition, independently rated one hour CFM samples at three speeds from each baby. Interobserver agreement was quantified using Cohen's κ.
Results: CFM traces from 19 babies with EEG seizures and 21 babies without EEG seizures were analysed. Overall non-expert interpretation of the CFM performed poorly as a seizure detector compared with simultaneous EEG (sensitivities 38% at 6 cm/h; 54% at 15 cm/h; 55% at 30 cm/h). Although babies with seizures were more likely to be correctly classified at higher speeds (p = 0.02), babies without seizures were also more likely to be misclassified (p < 0.001). Agreement between observers was not good at any speed (κ values from 0.01 to 0.39). The observers usually detected generalised seizures but often missed seizures that were focal, low amplitude, or lasted less than one minute.
Conclusion: Approximately half of all neonatal seizures may be missed using CFM alone. Neonatal seizures need to be diagnosed, characterised, and quantified first using EEG. The CFM may then be useful for long term monitoring.
It has been well established in animal models that electrical fields generated during inter-ictal and ictal discharges are strong enough in intensity to influence action potential firing threshold and synchronization. We discuss recently published data from microelectrode array recordings of human neocortical seizures and speculate about the possible role of field effects in neuronal synchronization. We have identified two distinct seizure territories that cannot be easily distinguished by traditional EEG analysis. The ictal core exhibits synchronized neuronal burst firing, while the surrounding ictal penumbra exhibits asynchronous and relatively sparse neuronal activity. In the ictal core large amplitude rhythmic ictal discharges produce large electric fields that correspond with highly synchronous neuronal firing. In the penumbra rhythmic ictal discharges are smaller in amplitude, but large enough to influence spike timing, yet neuronal synchrony is not observed. These in homine observations are in accord with decades of animal studies supporting a role of field effects in neuronal synchronization during seizures, yet also highlight how field effects may be negated in the presence of strong synaptic inhibition in the penumbra.
ephaptic conduction; field effect; seizures; epilepsy; synchrony
Electrographic seizures (ES) and electrographic status epilepticus (ESE) are common in critically ill children. We aimed to determine whether ES and ESE are associated with higher mortality or worse short-term neurologic outcome.
Prospective observational study.
Pediatric intensive care unit of a tertiary children’s hospital.
Non-neonatal children admitted to a pediatric intensive care unit (PICU) with acute encephalopathy underwent continuous electroencephalographic (cEEG) monitoring. EEGs were scored as (1) no seizures, (2) ES, or (3) ESE. Covariates included age, acute neurologic disorder category, prior neurodevelopmental status, sex, and EEG background category. Outcomes were mortality and worsening of Pediatric Cerebral Performance Category (PCPC) from pre-admission to PICU discharge. Chi-squared analysis, Fisher’s exact test, and multivariable logistic regression were used to evaluate the associations between ES or ESE and mortality or short-term neurologic outcome, using odds ratios (OR) and 95% confidence intervals (95%CI).
Two hundred children underwent cEEG. Eighty-four (42%) had seizures which were categorized as ES in 41 (20.5%) and ESE in 43 (21.5%). Thirty-six subjects (18%) died and 88 subjects (44%) had PCPC worsening. In multivariable analysis ESE was associated with an increased risk of mortality (OR 5.1; 95%CI 1.4, 18, p=0.01) and PCPC worsening (OR 17.3; 95%CI 3.7, 80, p<0.001) while ES was not associated with an increased risk of mortality (OR 1.3; 95%CI 0.3, 5.1; p=0.74) or PCPC worsening (OR 1.2; 95%CI 0.4, 3.9; p=0.77).
ESE, but not ES, is associated with mortality and worse short-term neurologic outcome in critically ill children with acute encephalopathy.
EEG Monitoring; Seizure; Status Epilepticus; Pediatric; Outcome; Non-Convulsive Seizure
Electroencephalography (EEG) is frequently ordered for patients with febrile seizures despite its unclear diagnostic value. We evaluated the prevalence of abnormal EEGs, the association between clinical findings and abnormal EEGs, and the predictive value of EEG for the recurrence of febrile seizures.
Data were collected on 230 children who were treated for febrile seizures at Kyung Hee University Medical Center from 2005 to 2009. EEGs were recorded after 1-2 days of hospitalization when children became afebrile. EEG patterns were categorized as normal, epileptiform, or nonspecific relative to abnormalities. The patients' medical records were reviewed, and telephone interviews with the families of the children were conducted to inquire about seizure recurrence. The relationships between clinical variables, including seizure recurrence, and EEG abnormalities were evaluated.
Of the 131 children included, 103 had simple and 28 had complex febrile seizures. EEG abnormalities were found in 41 children (31%). EEG abnormalities were more common in children with complex than simple febrile seizures (43% vs. 28%), but the difference was not statistically significant. Logistical regression analysis showed that having multiple seizures in a 24-hour period was significantly predictive of abnormal EEG (odds ratio, 2.98; 95% confidence interval, 1.0 to 88; P=0.048). The frequency of recurrence did not differ significantly in the normal (31%) and abnormal (23%) EEG groups.
Multiple seizures within 24 hours were predictive of abnormal EEG in children with febrile seizures. Abnormal EEG was not predictive of febrile seizure recurrence.
Febrile seizures; Postictal; Electroencephalography
Continuous EEG monitoring is used with increasing frequency in critically ill children to provide insight into brain function and to identify electrographic seizures. EEG monitoring use often impacts clinical management, most often by identifying electrographic seizures and status epilepticus. Most electrographic seizures have no clinical correlate, and thus would not be identified without EEG monitoring. There is increasing data that electrographic seizures and electrographic status epilepticus are associated with worse outcome. Seizure identification efficiency may be improved by further development of quantitative EEG trends. This review describes the clinical impact of EEG data, the epidemiology of electrographic seizures and status epilepticus, the impact of electrographic seizures on outcome, the utility of quantitative EEG trends for seizure identification, and practical considerations regarding EEG monitoring.
EEG; EEG monitoring; seizure; status epilepticus; intensive care unit; critical care
Epileptic seizures are due to abnormal synchronized neuronal discharges. Techniques measuring electrical changes are commonly used to analyze seizures. Neuronal activity can be also defined by concomitant hemodynamic and metabolic changes. Simultaneous electroencephalogram (EEG)-functional MRI (fMRI) measures noninvasively with a high-spatial resolution BOLD changes during seizures in the whole brain. Until now, only a static image representing the whole seizure was provided. We report in 10 focal epilepsy patients a new approach to dynamic imaging of seizures including the BOLD time course of seizures and the identification of brain structures involved in seizure onset and discharge propagation. The first activation was observed in agreement with the expected location of the focus based on clinical and EEG data (three intracranial recordings), thus providing validity to this approach. The BOLD signal preceded ictal EEG changes in two cases. EEG-fMRI may detect changes in smaller and deeper structures than scalp EEG, which can only record activity form superficial cortical areas. This method allowed us to demonstrate that seizure onset zone was limited to one structure, thus supporting the concept of epileptic focus, but that a complex neuronal network was involved during propagation. Deactivations were also found during seizures, usually appearing after the first activation in areas close or distant to the activated regions. Deactivations may correspond to actively inhibited regions or to functional disconnection from normally active regions. This new noninvasive approach should open the study of seizure generation and propagation mechanisms in the whole brain to groups of patients with focal epilepsies.
PMID: 19507156 CAMSID: cams3405
seizure; epilepsy; imaging; fMRI; EEG
The aim of this study was to evaluate reader variability in screening mammograms according to the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) assessment and breast density categories.
A stratified random sample of 100 mammograms was selected from a population-based breast cancer screening programme in Barcelona, Spain: 13 histopathologically confirmed breast cancers and 51 with true-negative and 36 with false-positive results. 21 expert radiologists from radiological units of breast cancer screening programmes in Catalonia, Spain, reviewed the mammography images twice within a 6-month interval. The readers described each mammography using BI-RADS assessment and breast density categories. Inter- and intraradiologist agreement was assessed using percentage of concordance and the kappa (κ) statistic.
Fair interobserver agreement was observed for the BI-RADS assessment [κ=0.37, 95% confidence interval (CI) 0.36–0.38]. When the categories were collapsed in terms of whether additional evaluation was required (Categories III, 0, IV, V) or not (I and II), moderate agreement was found (κ=0.53, 95% CI 0.52–0.54). Intra-observer agreement for BI-RADS assessment was moderate using all categories (κ=0.53, 95% CI 0.50–0.55) and substantial on recall (κ=0.66, 95% CI 0.63–0.70). Regarding breast density, inter- and intraradiologist agreement was substantial (κ=0.73, 95% CI 0.72–0.74 and κ=0.69, 95% CI 0.68–0.70, respectively).
We observed a substantial intra-observer agreement in the BI-RADS assessment but only moderate interobserver agreement. Both inter- and intra-observer agreement in mammographic interpretation of breast density was substantial.
Advances in knowledge
Educational efforts should be made to decrease radiologists' variability in BI-RADS assessment interpretation in population-based breast screening programmes.
In this study, we investigated the possibility of differential diagnosis of patients with epileptic seizures (ES) and patients with psychogenic non-epileptic seizures (PNES) by an advanced analysis of dynamics of the patients' scalp electroencephalograms (EEG). The underlying principle was the presence of resetting of brain's pre-ictal spatiotemporal entrainment following onset of ES and the absence of resetting following PNES. Long-term (days) scalp EEGs recorded from five ES and six PNES patients were analyzed. It was found that: (a) Pre-ictal entrainment of brain sites was reset by epileptic seizures (p<0.05) in 4 out of the 5 patients with ES, and not reset (p=0.28) in the fifth patient. (b) Resetting did not occur (p>0.1) in any of the 6 patients with PNES. These preliminary results in patients with ES are in agreement with our previous findings from intracranial EEG recordings on resetting of brain dynamics at ES and it is expected to constitute the basis for the development of a reliable and supporting tool in the differential diagnosis between ES and PNES. Finally, we believe that these results shed a novel light on the electrophysiology of psychogenic epilepsy by showing that occurrence of PNES does not assist patients to overcome a pathological entrainment of brain dynamics.
Epileptic Seizures; Psychogenic Non-Epileptic Seizures; Electroencephalography; Spatiotemporal Brain Dynamics; Seizure Resetting