Nonconvulsive Status Epilepticus Diagnosis Research Articles

Nonconvulsive status epilepticus characteristics in glioma patients: a retrospective study

PurposeEpilepsy is a common complication of gliomas. The diagnosis of nonconvulsive status epilepticus (NCSE) is challenging because it causes impaired consciousness and mimics glioma progression. NCSE complication rate in the general brain tumor patient population is approximately 2%. However, there are no reports focusing on NCSE in glioma patient population. This study aimed to reveal the epidemiology and features of NCSE in glioma patients to enable appropriate diagnosis.MethodsWe enrolled 108 consecutive glioma patients (45 female, 63 male) who underwent their first surgery between April 2013 and May 2019 at our institution. We retrospectively investigated glioma patients diagnosed with tumor-related epilepsy (TRE) or NCSE to explore disease frequency of TRE/NCSE and patient background. NCSE treatment approaches and Karnofsky Performance Status Scale (KPS) changes following NCSE were surveyed. NCSE diagnosis was confirmed using the modified Salzburg Consensus Criteria (mSCC).ResultsSixty-one out of 108 glioma patients experienced TRE (56%), and five (4.6%) were diagnosed with NCSE (2 female, 3 male; mean age, 57 years old; WHO grade II 1, grade III 2, grade IV 2). All NCSE cases were controlled by stage 2 status epilepticus treatment as recommended in the Clinical Practice Guidelines for Epilepsy by the Japan Epilepsy Society. The KPS score significantly decreased after NCSE.ConclusionHigher prevalence of NCSE in glioma patients was observed. The KPS score significantly decreased after NCSE. Actively taking electroencephalograms analyzed by mSCC may facilitate accurate NCSE diagnosis and improve the activities of daily living in glioma patients.

Salzburg Criteria, A Useful Tool in Non-Convulsive Status Epilepticus Diagnosis: A Retrospective Study.

Introduction. Non-convulsive status epilepticus (NCSE) has been traditionally a challenging electroencephalographic (EEG) diagnosis. For this reason, Salzburg consensus criteria (SCC) have been proposed to facilitate correct diagnosis. Methods. We retrospectively reanalyzed 41 cases referred to our department (from 2016 to 2018) under the suspicion of NCSE. In this study, we compared the original description (standard criteria) versus the updated description (SCC) of the same EEG. Results. Originally, 15 patients were diagnosed as NCSE (37%) and 26 patients as no NCSE (63%), using the standard criteria. Then, we analyzed EEGs according to the SCC, which led to the following results: 9 patients fulfilled the criteria for definite NCSE (22%), 20 patients were diagnosed as possible NCSE (49%) and 12 patients were diagnosed as no NCSE (29%). Subsequently, when we analyze the outcome of possible NCSE cases, we note that 50% of these patients presented mild-poor outcome (neurological deficits, deceased). Indeed, we observed worse outcomes in patients previously diagnosed as no NCSE and untreated, specifically post-anoxic cases. Conclusions. Salzburg criteria seem to be a useful tool to support NCSE diagnosis, introducing the category of possible NCSE. In our study, we observed that it contributes to improving the prognosis and management of the patients. However, more prospective studies are needed to demonstrate the accuracy of SCC.

Nonconvulsive Status Epilepticus in Metabolic Encephalopathy in Indonesia Referral Hospital.

Nonconvulsive status epilepticus (NCSE) is often underdiagnosed in patients with metabolic encephalopathy (ME). The diagnosis of ME should be made specifically to recognize the underlying etiology. Delay in seizure identification and making a diagnosis of NCSE contributed to the poor outcome. This study aimed to find the incidence and outcome of NCSE in patients with ME. This was an observational prospective cross-sectional study in patients with ME in emergency and critical care units in Cipto Mangunkusumo General Hospital. The diagnosis of NCSE was based on EEG using Salzburg Criteria for Nonconvulsive Status Epilepticus (SCNC). The outcome was assessed within 30 days after the NCSE diagnosis has been made. A total of 50 patients with ME were involved in this study. NCSE was confirmed in 32 subjects (64%). The most common etiology of ME was sepsis (58%). The mortality rate in the NCSE and non-NCSE group was 40.6% vs 44.4%. Multiple aetiologies were risk factors to poor outcome in the NCSE group. The incidence of NCSE among patients with ME at our hospital was high. Despite the anti-epileptic treatment of the NCSE group, the underlying cause of ME is still the main factor that affected the outcome. Therefore, aggressive treatment of anti-epileptic drug (AED) should be very carefully considered knowing the possible side-effect that might worsen the outcome of patients with ME.

Quantitative Infrared Pupillometry in Nonconvulsive Status Epilepticus.

Nonconvulsive status epilepticus (NCSE) is a frequent disorder in neurocritical care and diagnosing it can be challenging. NCSE patients often show altered pupil function, but nature and extent may vary. Infrared pupillometry allows detection of subtle changes of pupil function. The neurological pupil index (NPi) is considered a surrogate marker of global pupil function which is supposed to be independent of absolute parameters such as the pupil diameter. Cross-sectional observational study to assess whether NPi is altered in NCSE. 128 consecutive adult emergency patients who had experienced a suspected seizure, have not reached their prior functional level regarding level of consciousness, mental status or focal deficits, had no obvious clinical signs of status epilepticus and had an EEG indication as determined by the treating clinician for exclusion of NCSE were examined by routine EEG and pupillometry. Exclusion criteria were ocular comorbidity (n = 21) and poor EEG quality (n = 4). Pupillometry was performed once directly before the beginning of EEG recording. NCSE diagnosis (no NCSE, possible NCSE and confirmed NCSE) was established according to Salzburg consensus criteria blinded to pupillometry results. Group comparison was performed for right NPi, left NPi, lowest NPi of both sides (minNPi) and the absolute difference of both sides (diffNPi) applying non-parametric testing. In post-hoc analysis, receiver operating characteristics (ROC) of NCSE diagnosis (combined confirmed NCSE and possible NCSE) were performed for minNPi and diffNPi. From 103 patients included in the final analysis, 5 (4.9%) had confirmed NCSE, 7 (6.8%) had possible NCSE. Right NPi (p = 0.002), left NPi (p < 0.001) and minNPi (p < 0.001) were significantly lower in "confirmed NCSE" and "possible NCSE" compared to "no NCSE"; diffNPi was significantly higher in "confirmed NCSE" and "possible NCSE" compared to "no NCSE" (p < 0.001). There was no significant difference of minNPi and diffNPi between "confirmed NCSE" and "possible NCSE". ROC analysis showed an optimal cut-off of minNPi for NCSE diagnosis of 4.0 (AUC = 0.93, 95% CI 0.86-0.99). Optimal ROC analysis cut-off of diffNPi for NCSE diagnosis was 0.2 (AUC = 0.89, 95% CI 0.80-0.99). NPi was significantly reduced and the difference between left and right NPi was significantly higher in confirmed NCSE. An NPi < 4.0 on either side as well as an NPi difference of both sides > 0.2 may be potential indicators of NCSE. Infrared pupillometry may be a helpful diagnostic tool in the assessment of NCSE and should be studied further in larger populations.

Usefulness of HMPAO-SPECT in the diagnosis of nonconvulsive status epilepticus

BackgroundThe diagnosis of nonconvulsive status epilepticus (NCSE) can pose a challenge. Electroencephalogram (EEG) patterns can be difficult to interpret, and the absence of an EEG correlate does not rule out the diagnosis of NCSE. In this setting, neuroimaging tools to help in the diagnosis are crucial. Our aim was to evaluate the role of 99mTc-hexamethyl propyleneamine oxime (HMPAO) single photon emission computed tomography (SPECT) and quantitative HMPAO-SPECT (QtSPECT) in patients with clinical suspicion of NCSE, and to evaluate their value in the final diagnosis of NCSE. MethodsWe recruited consecutive patients admitted in our center with suspicion of NCSE, and selected those who underwent an HMPAO-SPECT. All patients were admitted to the neurology ward and underwent an EEG. We divided the patients into those who were finally with diagnosed NCSE (NCSE-p) and those who were not (non-NCSE) according to the Salzburg Diagnostic EEG criteria. Sensitivity and specificity of the diagnostic tools were calculated. The SPECTs were acquired in a Skylight SPECT (Philips Healthcare, Amsterdam). The injections were done during the clinical episode suspected of being an NCSE. The HMPAO-SPECT was analyzed by two experts and was also quantified. All data were normalized to the SPM SPECT template. We used an external healthy normal database to obtain a Z-score map for each individual versus the normal database. The Z-score maximum (Zmax) was extracted from each region of the AAL atlas as was the percentage of voxels with a Z-score higher than 2.5 (N(%)). A logistic regression combining the Zmax, N(%), and the effect of patient age was fitted to predict the final NCSE diagnosis. A receiver operator characteristic (ROC) curve and the area under the curve (AUC) were obtained to evaluate the classification performance. ResultsWe included 55 patients, 21 of them women (38.9%), with a median age of 62.1 years old (range 25–84). Thirty-six patients were with diagnosed NCSE (62.9%). Initial EEG had a sensitivity of 61.1% and a specificity of 89%. Most of the patients were critically ill with diagnostic difficulties, and it could be one of the main reasons to find low sensitivity of the Salzburg diagnostic EEG criteria. The Zmax and N(%) were significantly higher in NCSE-p than in non-NCSE (p = 0.005 and p < 0.001, respectively). The HMPAO-SPECT qualitative analysis had a sensitivity of 80.5% and specificity of 89.5% while QtSPECT had a sensitivity of 82% and specificity of 81%. ConclusionBoth 99mTc-HMPAO-SPECT and QtSPECT can be useful in the diagnosis of NCSE.This article is part of the Special Issue “Proceedings of the 7th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures”

Initial experience of a telemetry EEG amplifier (Headset™) in the emergent diagnosis of nonconvulsive status epilepticus

Objectives: In the diagnosis of nonconvulsive status epilepticus (NCSE), the use of ongoing ictal electroencephalographic (EEG) findings is the gold standard. However, this is difficult without the availability of continuous EEG monitoring facilities. Given this, a small telemetry EEG amplifier (Headset-EEG; AE-120A EEG Headset™) was introduced for use in simple EEG monitoring facilities. In this study, we examined the diagnostic performance of the Headset-EEG for NCSE in a neuroemergency setting.Methods: We retrospectively selected five patients who were diagnosed with NCSE using Headset-EEG by attending physicians between October 2017 and July 2018. Reevaluation with Headset-EEG was performed, and the findings were compared with the initial diagnosis. Results: In Case 1, Headset-EEG clearly revealed repeated ictal discharges associated with acute subdural hematoma. However, in Cases 2 and 3, the initial EEG diagnosis was incorrectly made because of an EEG interpretation error. In Cases 4 and 5, various artifacts, caused by unstable electrode placement, resulted in an initial diagnosis of ongoing seizure activity. Nevertheless, the initial diagnoses and subsequent treatment of Cases 2–5 did not directly affect the patients' outcomes.Conclusion: The present study indicates that Headset-EEG is a possible tool for use in NCSE screening. However, considerable knowledge of EEG interpretation is needed to establish a correct NCSE diagnosis. When NCSE is suspected per Headset-EEG, a subsequent routine EEG with a full montage of 10–20 EEG electrodes should be performed in collaboration with an epileptologist or electroencephalographer.

Nonconvulsive Epileptic Seizure Detection in Scalp EEG Using Multiway Data Analysis.

Nonconvulsive status epilepticus is a condition where the patient is exposed to abnormally prolonged epileptic seizures without evident physical symptoms. Since thesecontinuous seizures may cause permanent brain damage, it constitutes a medical emergency. This paper proposes a method to detect nonconvulsive seizures for a further nonconvulsive status epilepticus diagnosis. To differentiate between the normal and seizure electroencephalogram (EEG), a K-Nearest Neighbor, a Radial Basis Support Vector Machine, and a Linear Discriminant Analysis classifier are used. The classifier features are obtained from the Canonical Polyadic Decomposition (CPD) and Block Term Decomposition of the EEG data represented as third order tensor. To expand the EEG into a tensor, Wavelet or Hilbert-Huang transform are used. The algorithm is tested on a scalp EEG database of 139 seizures of different duration. The experimental results suggest that a Hilbert-Huang tensor representation and the CPD analysis provide the most suitable framework for nonconvulsive seizure detection. The Radial Basis Support Vector Machine classifier shows the best performance with sensitivity, specificity, and accuracy values over 98%. A rough comparison with other methods proposed in the literature shows the superior performance of the proposed method for nonconvulsive epileptic seizure detection.

Non-Convulsive Status Epilepticus in Emergency Department: A Diagnostic Challenge

Non-convulsive status epilepticus had always been a diagnostic dilemma to emergency physicians. The challenge falls in its elusive nature and the subtlety of physical findings. Understanding the essence this disease process and the approach to it will result into a rewarding outcome for the patient and the physician. In this brief review we are trying to shed some light on that ambiguous neurological emergency and try to come up with a facilitated way of dealing with this common source of morbidity and mortality. Discussion Non-convulsive status epilepticus (NCSE) is a term used to refer to a prolonged seizure without an overt motor signs. It’s also defined as an altered mental status or change in the behavior from baseline with continuous epileptiform EEG changes. A review of literature showed that till now there is no acceptable definition. [1] NCSE are thought to be responsible for about 25% of the status epilepitcus. [2] De Lorenzo et al conducted a retrospective study in which 164 patients were subjected to a continuous 24 hours EEG monitoring after seizure treatment. He found that 14% of the patients had a NCSE and about 48% of the patient had a persistent seizure activity on EEG. [3] Treiman et al also in a similar manner found that 25% of the patient had NCSE after treatment for GCSE when monitored by EEG in his study that included 384 patients. [23] NCSE diagnosis has always been a diagnostic challenge to emergency physicians as there are no definitive diagnostic criteria, and due to the hectic nature of the emergency department its sound to difficult to do full neurological exam and in-depth medical history. [4] NCSE encompasses a group of syndromes that varies from self-limiting to refractory form. Absence SE and partial complex SE are the 2 major types that are commonly known although some recent data from medical literature had shown other subtypes. Clinical suspicion and EEG findings are mainstay to establish the diagnosis. Clinically, high index of suspicions should be kept in cases of: [5]  Prolonged postictal states  Absence of other clinical explanation for the patients with altered mental status  Stroke patients that seemed worse than expected  Subtle signs (blinking, twitching, fluctuating sensorium. Etc.). www.jmscr.igmpublication.org Impact Factor 5.244 Index Copernicus Value: 83.27 ISSN (e)-2347-176x ISSN (p) 2455-0450 DOI: http://dx.doi.org/10.18535/jmscr/v4i8.103

Anti-NMDA-R encephalitis: Should we consider extreme delta brush as electrical status epilepticus?

Seizures are common clinical manifestations in anti-N-methyl-d-aspartate receptor (anti-NMDA-R) encephalitis, among other neurological and psychiatric symptoms. During the course of the disease, some specific EEG patterns have been described: generalized rhythmic delta activity (GRDA) and extreme delta brush (EDB). In comatose patients, the association of these EEG abnormalities with subtle motor manifestations can suggest ongoing non-convulsive status epilepticus (NCSE). We report the case of a 28-year-old woman admitted for a clinical presentation typical of anti-NMDA-R encephalitis, which was confirmed by CSF analysis. She was rapidly intubated because of severe dysautonomia and disturbed consciousness. Clinical examination revealed subtle paroxysmal and intermittent myoclonic and tonic movements, correlated on video-EEG with GRDA and/or EDB. NCSE was then suspected, but electroclinical manifestations persisted despite many anti-epileptic drugs combinations, or reappeared when barbiturate anesthesia was decreased. In order to confirm or dismiss the diagnosis, intracranial pressure (ICP) and surface video-EEG monitoring were performed simultaneously and revealed no ICP increase, thus being strongly against a diagnosis of seizures. Sedation was progressively weaned, and clinical condition as well as EEG appearance progressively improved. Literature review revealed 11 similar cases, including 2 with focal NCSE. Of the nine other cases, NCSE diagnosis was finally excluded in 5 cases. NCSE diagnosis in association with anti-NMDA-R encephalitis is sometimes very difficult and its occurrence might be overestimated. Video-EEG is highly recommended and more invasive techniques may sometimes be necessary.

Epilepsia Partialis Continua and Generalized Nonconvulsive Status Epilepticus during the Course of Argininemia: A Report on Two Cases

Argininemia is a rare inherited disorder of the urea cycle because of a deficiency of the enzyme arginase I causing an increase of arginine and guanidino compounds in the blood, urine, and cerebrospinal fluid. The clinical picture is characterized by a mild cognitive dysfunction, progressive asymmetrical paraparesis, and seizures. Here, we describe two cases of argininemia where either epilepsia partialis continua (EPC) or nonconvulsive status epilepticus (NCSE) were the presenting manifestations of epilepsy. This is the first report of EPC in an urea cycle disorder. In both the cases, status epilepticus resolved with anticonvulsive drugs. EPC was successfully treated with levetiracetam, and NCSE with valproic acid. No side effects were observed. Because hyperammonemia and NCSE may have the same features of stupor, a neurophysiological approach might prove useful in differentiating these two conditions. Overall, our results strongly indicate that a correct NCSE diagnosis is mandatory to prevent further deterioration in these patients.

Continuous video-EEG monitoring increases detection rate of nonconvulsive status epilepticus in the ICU

Status epilepticus (SE) is an important neurologic emergency requiring treatment on an intensive care unit (ICU). Although convulsive SE is self-evident, the diagnosis of nonconvulsive SE (NCSE) depends on electroencephalography (EEG) confirmation. Previous work showed that 82% of patients with SE had NCSE in our ICU. We hypothesize that continuous video-EEG monitoring (CVEM) may increase the diagnostic yield in patients with SE, especially NCSE, and leave fewer patients undiagnosed. We retrospectively assessed the EEG reports of 537 patients with suspected SE during three comparable 9-month periods, two groups before (groups 1 and 2) and one (group 3) after CVEM introduction. Differences in monthly rates of SE between groups were assessed using the Mann-Whitney U-test. The rates of diagnosis increased significantly after implementation of CVEM (p = 0.0546). There was no significant difference in monthly rates of NCSE diagnosis between groups 2 and 1 (difference = 0.78 new diagnosis/month; p = 0.374). Differences between groups 3 and 2 (2.89; p = 0.0173), between groups 3 and 1 (3.67; p = 0.006) and between group 3 and pooled groups 1 and 2 (3.28; p = 0.002) were statistically significant. Frequency of NCSE diagnosis increased significantly after implementation of CVEM and was higher than the increment of performed investigations alone. Such an effect may result from the combination of longer observation periods during CVEM, greater and permanent availability of EEG recordings, and heightened awareness of NCSE. Future studies may corroborate improvement of diagnosis and outcomes in patients with disorders of consciousness by CVEM.