Midline and Parasagittal Seizures are Rare in Adult Patients

BACKGROUND

For decades, half of the electrodes used in traditional electroencephalography (EEG) have been dedicated to midline and parasagittal coverage. Recently, newer EEG devices have used fewer electrodes without direct coverage over the midline or parasagittal regions. However, no systematic study to date has explored the prevalence of midline parasagittal seizures, and as such the risk of missing such seizures with only ten electrodes remains unknown.

METHODS

We reviewed retrospective EEG data from a cohort of 300 patients at Stanford University Medical Center and determined the frequency of seizures localized to the midline parasagittal regions. We then compiled previously reported EEG cohorts that reported the prevalence of midline parasagittal seizures to validate our findings.

RESULTS

In our cohort, only two EEGs (0.66%) were identified with a midline or parasagittal seizure focus. In a subsequent study, we compiled literature evidence from 169510 EEGs and found that the prevalence of midline or parasagittal epileptic spikes/seizures was similarly less than 1%.

CONCLUSIONS

Our study serves as the first to systematically explore the scope of EEG abnormalities captured exclusively by midline or parasagittal electrodes and document their very low prevalence.

Emergency electroencephalogram: Usefulness in the diagnosis of nonconvulsive status epilepticus by the on-call neurologist

INTRODUCTION

We aim to describe the use of emergency electroencephalogram (EmEEG) by the on-call neurologist when nonconvulsive status epilepticus (NCSE) is suspected, and in other indications, in a tertiary hospital.

SUBJECTS AND METHODS

Observational retrospective cohort study of emergency EEG (EmEEG) recordings with 8-channel systems performed and analysed by the on-call neurologist in the emergency department and in-hospital wards between July 2013 and May 2015. Variables recorded were sex, age, symptoms, first diagnosis, previous seizure and cause, previous stroke, cancer, brain computed tomography, diagnosis after EEG, treatment, patient progress, routine control EEG (rEEG), and final diagnosis. We analysed frequency data, sensitivity, and specificity in the diagnosis of NCSE.

RESULTS

The study included 135 EEG recordings performed in 129 patients; 51.4% were men and their median age was 69 years. In 112 cases (83%), doctors ruled out suspected NCSE because of altered level of consciousness in 42 (37.5%), behavioural abnormalities in 38 (33.9%), and aphasia in 32 (28.5%). The EmEEG diagnosis was NCSE in 37 patients (33%), and this was confirmed in 35 (94.6%) as the final diagnosis. In 3 other cases, NCSE was the diagnosis on discharge as confirmed by rEEG although the EmEEG missed this condition at first. EmEEG performed to rule out NCSE showed 92.1% sensitivity, 97.2% specificity, a positive predictive value of 94.6%, and a negative predictive value of 96%.

CONCLUSIONS

Our experience finds that, in an appropriate clinical context, EmEEG performed by the on-call neurologist is a sensitive and specific tool for diagnosing NCSE.

StatNet Electroencephalogram: A Fast and Reliable Option to Diagnose Nonconvulsive Status Epilepticus in Emergency Setting

BACKGROUND

The StatNet electrode set is a system that can be applied by a non-electroencephalogram (EEG) technologist after minimal training. The primary objectives of this study are to assess the quality and reliability of the StatNet recordings in comparison to the conventional EEG.

METHODS

Over 10 months, 19 patients with suspected nonconvulsive status epilepticus were included from university hospital emergency settings. Each patient received a StatNet EEG by a trained epilepsy fellow and a conventional EEG by registered technologists. We compared the studies in a blinded fashion, for the timeframe from EEG order to the setup time, start of acquisition, amount of artifact, and detection of abnormalities. The nonparametric Mann-Whitney two-sample t test was used for comparisons. The kappa score was used to assess reliability.

RESULTS

Mean age of patients was 61±16.3 (25-93) years. The inter-observer agreement for detection of abnormal findings was 0.83 for StatNet and 0.75 for conventional EEG. Nonconvulsive status epilepticus was detected in 10% (2/19) in both studies. The delay from the time of EEG requisition to acquisition was shorter in the StatNet (22.4±2.5 minutes) than the conventional EEG (217.7±44.6 minutes; p<0.0001). The setup time was also shorter in the StatNet (9.9±0.8 minutes) compared with the conventional EEG (17.8±0.8 minutes; p<0.0001). There was no difference in the percentage of artifact duration between the two studies (p=0.89).

CONCLUSION

This study demonstrates that StatNet EEG is a practical and reliable tool in the emergency setting, which reduces the delay of testing compared with conventional EEG, without significant compromise of study quality.