Continuous EEG predictors of outcome in patients with altered sensorium

Comparison of Electroencephalography in Patients With Seizures Caused by Neurosyphilis and Viral Encephalitis

Background

Neurosyphilis (NS) lacks specificity in clinical and imaging features, and patients are frequently misdiagnosed as viral encephalitis when they present with seizures. This study aimed to compare electroencephalography (EEG) in patients with seizures resulting from the two diseases and provide guidance for differential diagnosis.

Methods

A retrospective study on patients diagnosed with neurosyphilis and viral encephalitis with seizures in the Department of Neurology, Zhongshan Hospital, Xiamen University from 2012 to 2020.

Results

A total of 39 patients with seizures caused by neurosyphilis and 40 patients with seizures caused by viral encephalitis were included. Chi-square test analysis showed that compared with patients with viral encephalitis, patients with neurosyphilis mainly developed in middle-aged and elderly people (p < 0.001), were more likely to have temporal epileptiform discharges (p < 0.001), and less likely to have status epilepticus (SE) (p = 0.029). There was difference between two groups in the EEG performance of lateralized periodic discharges (LPDs) (p = 0.085). The two groups were matched for age and sex by case-control matching, and 25 cases in each group were successfully matched. Patients with neurosyphilis were more likely to have temporal epileptiform discharges than those with viral encephalitis (p = 0.002), and there were no significant differences in LPDs (p = 0.077) and SE (p = 0.088) between two groups.

Conclusion

When EEG shows temporal epileptiform discharges, especially in the form of LPDs, we should consider the possibility of neurosyphilis.

The economic burden of newly diagnosed epilepsy in Spain

OBJECTIVE

The aim of this study was to determine the hospital burden and economic impact of epilepsy in adults in Spain and identify characteristics associated with higher direct medical costs.

METHOD

Patients newly diagnosed with epilepsy at the outpatient epilepsy unit of a tertiary hospital in Spain in 2012 were included. Sociodemographic and clinical data and use of health resources were collected retrospectively from electronic medical records from the time of diagnosis to the end of follow-up (2019). Direct costs (in 2012 Euro) were estimated and linear regression models built to explore predictors of higher costs.

RESULTS

We studied 110 patients with newly diagnosed epilepsy. Their mean (SD) age was 52.6 (19.6) years and 53.6% were men. Eighty-nine patients (80.9%) had focal epilepsy and 45 (40.9%) had an unknown etiology. At 6 months, 79.1% of patients were classified as responders and 17.6% as having drug-resistant epilepsy. The mean direct cost in the first year of epilepsy diagnosis was €3816.06, 49.7% of which was due to hospital admissions. The mean annual cost per patient was €2584.17, 51.4% of which was due to anti-seizure medications (ASMs). Focal epilepsy and poor response in the first 6 months of treatment predicted higher annual costs, while focal epilepsy and pre-existing comorbidities predicted higher costs in the first year.

CONCLUSIONS

The direct cost of newly diagnosed epilepsy in adults in our area is €2584 per patient/year. Anti-seizure medication use is the main cost driver. Focal epilepsy, comorbidities, and poor response to ASMs are independent predictors of higher costs.

Development of a novel outcome prediction score (PEDSS) for pediatric convulsive status epilepticus: A longitudinal observational study

OBJECTIVE

The objectives of this study were to evaluate ENDIT score and develop a novel outcome prediction score for outcome of pediatric convulsive status epilepticus (CSE) at the hospital and 3 months postdischarge.

METHODS

Children and adolescents aged 1 month to 14 years, presenting with CSE to a tertiary care teaching center in North India from January 2017 to March 2019, were screened for enrollment. In-hospital and 3-month postdischarge outcome were defined as poor if Pediatric Cerebral Performance Category Scale (PCPCS) score dropped by ≥2 levels.

RESULTS

Overall, 61 patients were enrolled for final analysis after applying exclusion and inclusion criteria. The area under the receiver operating characteristic (ROC) curve for ENDIT score in predicting mortality and differentiating good from poor outcome at the hospital and at 3 months postdischarge was 0.74 (95% confidence interval [CI] = 0.58-0.89), 0.7 (95% CI = 0.57-0.83), and 0.72 (95% CI = 0.6-0.82), respectively. Based on predictors in the present cohort that were significantly different between good and poor outcome cases at the hospital and 3 months postdischarge, a new six-point score named PEDSS (pre-status epilepticus PCPCS, background electroencephalographic abnormalities, drug refractoriness, semiology, and critical sickness) was developed. The area under ROC curves for PEDSS score in predicting mortality and differentiating good from poor outcome at the hospital and at 3 months postdischarge were 0.93 (95% CI = 0.87-0.99), 0.8 (95% CI = 0.7-0.9), and 0.89 (95% CI = 0.8-0.96), respectively. The best cutoff PEDSS scores for predicting mortality and poor outcome at the hospital and at 3 months postdischarge were ≥4, ≥3, and ≥3, respectively.

SIGNIFICANCE

The PEDSS score has high predictive accuracy for mortality and differentiating good from poor outcome at the hospital and 3 months postdischarge in pediatric CSE. Future studies should be planned to validate it in various geographical and health care settings and in adults.

How and Whom to Monitor for Seizures in an ICU: A Systematic Review and Meta-Analysis

OBJECTIVES

To pool prevalence of nonconvulsive seizure, nonconvulsive status epilepticus, and epileptiform activity detected by different electroencephalography types in critically ills and to compare detection rates among them.

DATA SOURCES

MEDLINE (via PubMed) and SCOPUS (via Scopus) STUDY SELECTION:: Any type of study was eligible if studies were done in adult critically ill, applied any type of electroencephalography, and reported seizure rates. Case reports and case series were excluded.

DATA EXTRACTION

Data were extracted independently by two investigators. Separated pooling of prevalence of nonconvulsive seizure/nonconvulsive status epilepticus/epileptiform activity and odds ratio of detecting outcomes among different types of electroencephalography was performed using random-effect models. This meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and also adhered to the Meta-analyses Of Observational Studies in Epidemiology guidelines. Quality of evidence was assessed with the Newcastle-Ottawa Quality Assessment Scale for observational studies and Cochrane methods for randomized controlled trial studies.

DATA SYNTHESIS

A total of 78 (16,707 patients) and eight studies (4,894 patients) were eligible for pooling prevalence and odds ratios. For patients with mixed cause of admission, the pooled prevalence of nonconvulsive seizure, nonconvulsive status epilepticus, either nonconvulsive seizure or nonconvulsive status epilepticus detected by routine electroencephalography was 3.1%, 6.2%, and 6.3%, respectively. The corresponding prevalence detected by continuous electroencephalography monitoring was 17.9%, 9.1%, and 15.6%, respectively. In addition, the corresponding prevalence was high in post convulsive status epilepticus (33.5%, 20.2%, and 32.9%), CNS infection (23.9%, 18.1%, and 23.9%), and post cardiac arrest (20.0%, 17.3%, and 22.6%). The pooled conditional log odds ratios of nonconvulsive seizure/nonconvulsive status epilepticus detected by continuous electroencephalography versus routine electroencephalography from studies with paired data 2.57 (95% CI, 1.11-5.96) and pooled odds ratios from studies with independent data was 1.57 (95% CI, 1.00-2.47).

CONCLUSIONS

Prevalence of seizures detected by continuous electroencephalography was significantly higher than with routine electroencephalography. Prevalence was particularly high in post convulsive status epilepticus, CNS infection, and post cardiac arrest.

Clinical presentation, epidemiology, neurophysiological findings, treatment and outcome of nonconvulsive status epilepticus: a 3-year prospective, hospital-based study

Objective: This study reports the prevalence of Nonconvulsive Status Epilepticus (NCSE) in patients with altered mental status (AMS), and describes the clinical presentation, etiology, neurophysiological findings, neuroimaging, treatment, and outcome of NCSE in Qatar. Recording duration of continuous EEG monitoring was also discussed.

Methods: This was a 3-year, prospective, hospital-based study involving patients with AMS and continuous EEG monitoring admitted to the Emergency and ICUs of Hamad Hospital, Qatar. Patients with confirmed diagnosis of NCSE were compared to the patients who did not show EEG and clinical features compatible with NCSE. Descriptive statistics in terms of mean with standard deviation, as well as frequency and percentages for categorical variables, were calculated; Student’s t test as well as Chi-square tests or Fisher’s exact tests were applied. Logistic regressions NSCE was performed using significance level 0.05 for independent variables at univariate analysis.

Results: Number of patients with AMS and continuous EEG monitoring was 250. Number of patients with EEG compatible with NCSE: 65 (age range, 12–79 ys; m, 37; f, 28). Number of controls (defined as patients with EEG not compatible with NCSE): 185 (age range, 12–80 ys; m, 101; f, 84). Rate of occurrence of NCSE in patients with AMS: 26%. NCSE group was younger than controls (p < .001). Twenty patients with NCSE (31%) and 35 patients in the control group (19%) died. Death was more frequent in comatose NCSE compared to controls (p < .0007). NCSE proper and comatose NCSE had longer hospital stays than controls (p < .02 and p < .03, respectively). Complete recovery occurred in 26 NCSE patients (40%) and in 98 controls (53%) (p < .08). Twenty-one patients (31%) presented with refractory NCSE: 12 patients survived, 9 died.

Conclusion: This was the first prospective study reporting a high number of NCSE in Qatar, a small country in the MENA region. This prevalence (26%) was in the middle range. NCSE patients did not perform better than controls, outcome being worse with comatose NCSE. NCSE is an emergent condition warranting expedited diagnosis and management. Three days of continuous EEG monitoring were able to diagnose most cases of NCSE.

Ictal-interictal continuum: A proposed treatment algorithm

The ictal-interictal continuum (IIC) is characterized by periodic and/or rhythmic EEG patterns that occur with relative high frequency in critically ill patients. Several studies have reported that some patterns seen within the continuum are independently associated with poor outcome. However there is no consensus regarding when to treat them or how aggressive treatment should be. In this review we examine peer-reviewed original scientific articles, guidelines and reviews indexed in PubMed and summarize current knowledge related to the ictal-interictal continuum. A treatment algorithm to guide management of critically ill patients with EEG patterns that fall along the IIC is proposed. The algorithm-based on best current practice in adults-takes into account associated clinical events, risk factors for developing seizures, response to medication trials and biomarkers of neuronal injury.

Super-Refractory Status Epilepticus: Report of a Case and Review of the Literature

Super-refractory status epilepticus (SE; ie, SE continuing or recurring despite 24 hours of general anesthesia) is a severe condition with high percentage of mortality and morbidity. Usually, this condition occurs because of serious brain damage; nevertheless, some patients develop super-refractory SE without identifiable etiology. Although not uncommonly encountered in neurointensive care, scientific data on this condition are still lacking in terms of treatment and prognosis. Herein, we report a case of super-refractory SE with recovery after 50 days, despite electroencephalographic (EEG) and magnetic resonance imaging (MRI) signs traditionally related to poor prognosis. A review of the literature on super-refractory SE is also presented.

Incidence of recurrent seizures following hospital discharge in patients with LPDs (PLEDs) and nonconvulsive seizures recorded on continuous EEG in the critical care setting

PURPOSE

Continuous EEG (cEEG) has helped to identify nonconvulsive seizures (NCS) and nonconvulsive status epilepticus (NCSE) along with lateralized periodic patterns (LPDs or PLEDs) in ICU patients with much higher frequency than previously appreciated, but understanding their implications may be more complex. The aim of this study was to investigate the incidence of recurrent seizures after hospital discharge and their associated factors in patients with PLEDs and NCS in the critical care setting.

METHODS

After IRB approval, we used our EEG reporting database to find 200 consecutive patients who had PLEDs and/or NCSs on cEEG. Patients with less than 3 months of follow-up were excluded. Remaining patients were divided into three groups: PLEDs+Seizure (NCS/NCSE), PLEDs only, and Seizures (NCS/NCSE) only. Medical records were reviewed to gather demographical and clinical details. Univariate data analysis was done using JMP 9.0 (Marlow, Buckinghamshire, UK).

RESULTS

There were 51 patients in 'PLEDs+Seizure' group, 45 in 'PLEDs only' group, and 22 in 'Seizure only' group. Ischemic stroke, hemorrhage, and tumors were the top three etiologies. Nearly 47% of our study population had postdischarge seizures during a mean follow-up period of 11.9 (+/-6) months. We found that 24.4% of patients in the PLEDs only group had seizures after discharge, which increased to 60.7% if they had seizures as well during their ICU stay. Slightly more than 52% of patients had a postdischarge EEG, of which, 59% was in the form of inpatient cEEG during a rehospitalization, accounting for 30.5% of the total study population. It was an indicator of high readmission rates in this population.

CONCLUSION

Almost every other patient with PLEDs and/or NCS on cEEG had seizures after ICU discharge. A quarter of patients on cEEG in the ICU with PLEDs alone had seizures after discharge, and after excluding prior epilepsy, 17% of patients with PLEDs had seizures on follow-up. This was dramatically increased with the recording of PLEDs with NCS, with 60% of patients having seizures after discharge from the ICU and 48% of patients after excluding prior epilepsy. Patients with NCS on cEEG alone had 63% chance of seizure recurrence that dropped to 38% with exclusion of prior epilepsy. Future studies are needed to define the postdischarge outcomes including seizure recurrence in this patient population. This article is part of a Special Issue entitled "Status Epilepticus".

A Wavelet-Statistical Features Approach for Nonconvulsive Seizure Detection

The detection of nonconvulsive seizures (NCSz) is a challenge because of the lack of physical symptoms, which may delay the diagnosis of the disease. Many researchers have reported automatic detection of seizures. However, few investigators have concentrated on detection of NCSz. This article proposes a method for reliable detection of NCSz. The electroencephalography (EEG) signal is usually contaminated by various nonstationary noises. Signal denoising is an important preprocessing step in the analysis of such signals. In this study, a new wavelet-based denoising approach using cubical thresholding has been proposed to reduce noise from the EEG signal prior to analysis. Three statistical features were extracted from wavelet frequency bands, encompassing the frequency range of 0 to 8, 8 to 16, 16 to 32, and 0 to 32 Hz. Extracted features were used to train linear classifier to discriminate between normal and seizure EEGs. The performance of the method was tested on a database of nine patients with 24 seizures in 80 hours of EEG recording. All the seizures were successfully detected, and false positive rate was found to be 0.7 per hour.