Status epilepticus: an update

Monitoring the Burden of Seizures and Highly Epileptiform Patterns in Critical Care with a Novel Machine Learning Method

INTRODUCTION

Current electroencephalography (EEG) practice relies on interpretation by expert neurologists, which introduces diagnostic and therapeutic delays that can impact patients' clinical outcomes. As EEG practice expands, these experts are becoming increasingly limited resources. A highly sensitive and specific automated seizure detection system would streamline practice and expedite appropriate management for patients with possible nonconvulsive seizures. We aimed to test the performance of a recently FDA-cleared machine learning method (Claritγ, Ceribell Inc.) that measures the burden of seizure activity in real time and generates bedside alerts for possible status epilepticus (SE).

METHODS

We retrospectively identified adult patients (n = 353) who underwent evaluation of possible seizures with Rapid Response EEG system (Rapid-EEG, Ceribell Inc.). Automated detection of seizure activity and seizure burden throughout a recording (calculated as the percentage of ten-second epochs with seizure activity in any 5-min EEG segment) was performed with Claritγ, and various thresholds of seizure burden were tested (≥ 10% indicating ≥ 30 s of seizure activity in the last 5 min, ≥ 50% indicating ≥ 2.5 min of seizure activity, and ≥ 90% indicating ≥ 4.5 min of seizure activity and triggering a SE alert). The sensitivity and specificity of Claritγ's real-time seizure burden measurements and SE alerts were compared to the majority consensus of at least two expert neurologists.

RESULTS

Majority consensus of neurologists labeled the 353 EEGs as normal or slow activity (n = 249), highly epileptiform patterns (HEP, n = 87), or seizures [n = 17, nine longer than 5 min (e.g., SE), and eight shorter than 5 min]. The algorithm generated a SE alert (≥ 90% seizure burden) with 100% sensitivity and 93% specificity. The sensitivity and specificity of various thresholds for seizure burden during EEG recordings for detecting patients with seizures were 100% and 82% for ≥ 50% seizure burden and 88% and 60% for ≥ 10% seizure burden. Of the 179 EEG recordings in which the algorithm detected no seizures, seizures were identified by the expert reviewers in only two cases, indicating a negative predictive value of 99%.

DISCUSSION

Claritγ detected SE events with high sensitivity and specificity, and it demonstrated a high negative predictive value for distinguishing nonepileptiform activity from seizure and highly epileptiform activity.

CONCLUSIONS

Ruling out seizures accurately in a large proportion of cases can help prevent unnecessary or aggressive over-treatment in critical care settings, where empiric treatment with antiseizure medications is currently prevalent. Claritγ's high sensitivity for SE and high negative predictive value for cases without epileptiform activity make it a useful tool for triaging treatment and the need for urgent neurological consultation.

Correlation of serum S100B levels with brain magnetic resonance imaging abnormalities in children with status epilepticus

PURPOSE

To evaluate the association between elevated S100B levels with brain tissue damage seen in abnormalities of head magnetic resonance imaging (MRI; diffusion tensor imaging [DTI] sequence) in patients with status epilepticus (SE).

METHODS

An analytical observational study was conducted in children hospitalized at Dr Soetomo Hospital, Surabaya, from July to December 2016. The patients were divided into 2 groups: SE included all children with a history of SE; control included all children with febrile seizure. Blood samples of patients were drawn within 24 hours after admission. SE patients also underwent cranial MRI with additional DTI sequencing. The Mann-Whitney test and Spearman test were used for statistical analysis.

RESULTS

Fifty-three patients were enrolled the study. In the 24 children with SE who met the inclusion criteria, serum S100B and cranial MRI findings were assessed. Twenty-two children admitted with febrile seizures became the control group. Most patients were male (66.7%); the mean age was 35.8 months (standard deviation, 31.09). Mean S100B values of the SE group (3.430±0.141 μg/L) and the control group (2.998±0.572 μg/L) were significantly different (P<0.05). A significant difference was noted among each level of encephalopathy based on the cranial MRI results with serum S100B levels and the correlation was strongly positive with a coefficient value of 0.758 (P<0.001).

CONCLUSION

In SE patients, there is an increase of serum S100B levels within 24 hours after seizure, which has a strong positive correlation with brain damage seen in head MRI and DTI.

Brivaracetam, a selective high-affinity synaptic vesicle protein 2A (SV2A) ligand with preclinical evidence of high brain permeability and fast onset of action

OBJECTIVE

Rapid distribution to the brain is a prerequisite for antiepileptic drugs used for treatment of acute seizures. The preclinical studies described here investigated the high-affinity synaptic vesicle glycoprotein 2A (SV2A) antiepileptic drug brivara-cetam (BRV) for its rate of brain penetration and its onset of action. BRV was compared with levetiracetam (LEV).

METHODS

In vitro permeation studies were performed using Caco-2 cells. Plasma and brain levels were measured over time after single oral dosing to audiogenic mice and were correlated with anticonvulsant activity. Tissue distribution was investigated after single dosing to rat (BRV and LEV) and dog (LEV only). Positron emission tomography (PET) displacement studies were performed in rhesus monkeys using the SV2A PET tracer [11C]UCB-J. The time course of PET tracer displacement was measured following single intravenous (IV) dosing with LEV or BRV. Rodent distribution data and physiologically based pharmacokinetic (PBPK) modeling were used to compute blood-brain barrier permeability (permeability surface area product, PS) values and then predict brain kinetics in man.

RESULTS

In rodents, BRV consistently showed a faster entry into the brain than LEV; this correlated with a faster onset of action against seizures in audiogenic susceptible mice. The higher permeability of BRV was also demonstrated in human cells in vitro. PBPK modeling predicted that, following IV dosing to human subjects, BRV might distribute to the brain within a few minutes compared with approximately 1 h for LEV (PS of 0.315 and 0.015 ml/min/g for BRV and LEV, respectively). These data were supported by a nonhuman primate PET study showing faster SV2A occupancy by BRV compared with LEV.

SIGNIFICANCE

These preclinical data demonstrate that BRV has rapid brain entry and fast brain SV2A occupancy, consistent with the fast onset of action in the audiogenic seizure mice assay. The potential benefit of BRV for treatment of acute seizures remains to be confirmed in clinical studies.