Faculty Bibliography

PURPOSE/OBJECTIVE:A phase I feasibility study to determine the accuracy of identifying seizures based on audio recordings. METHODS:We systematically generated 166 audio clips of 30 s duration from 83 patients admitted to an epilepsy monitoring unit between 1/2015 and 12/2016, with one clip during a seizure period and one clip during a non-seizure control period for each patient. Five epileptologists performed a blinded review of the audio clips and rated whether a seizure occurred or not, and indicated the confidence level (low or high) of their rating. The accuracy of individual and consensus ratings were calculated. RESULTS:The overall performance of the consensus rating between the five epileptologists showed a positive predictive value (PPV) of 0.91 and a negative predictive value (NPV) of 0.66. The performance improved when confidence was high (PPV of 0.96, NPV of 0.70). The agreement between the epileptologists was moderate with a kappa of 0.584. Hyperkinetic (PPV 0.92, NPV 0.86) and tonic-clonic (PPV and NPV 1.00) seizures were most accurately identified. Seizures with automatisms only and non-motor seizures could not be accurately identified. Specific seizure-related sounds associated with accurate identification included disordered breathing (PPV and NPV 1.00), rhythmic sounds (PPV 0.93, NPV 0.80), and ictal vocalizations (PPV 1.00, NPV 0.97). CONCLUSION/CONCLUSIONS:This phase I feasibility study shows that epileptologists are able to accurately identify certain seizure types from audio recordings when the seizures produce sounds. This provides guidance for the development of audio-based seizure detection devices and demonstrate which seizure types could potentially be detected.

There are no functional imaging based biomarkers for pharmacological treatment response in temporal lobe epilepsy (TLE). In this study, we investigated whether there is an association between resting state functional brain connectivity (RsFC) and seizure control in TLE. We screened a large database containing resting state functional magnetic resonance imaging (Rs-fMRI) data from 286 epilepsy patients. Patient medical records were screened for seizure characterization, EEG reports for lateralization and location of seizure foci to establish uniformity of seizure localization within patient groups. Rs-fMRI data from patients with well-controlled left TLE, patients with treatment-resistant left TLE, and healthy controls were analyzed. Healthy controls and cTLE showed similar functional connectivity patterns, whereas trTLE exhibited a significant bilateral decrease in thalamo-hippocampal functional connectivity. This work is the first to demonstrate differences in neural network connectivity between well-controlled and treatment-resistant TLE. These differences are spatially highly focused and suggest sites for the etiology and possibly treatment of TLE. Altered thalamo-hippocampal RsFC thus is a potential new biomarker for TLE treatment resistance.

Background/UNASSIGNED:It is unknown whether postanoxic cortical and subcortical myoclonus are distinct entities with different prognoses. Methods/UNASSIGNED:In this retrospective cohort study of 604 adult survivors of cardiac arrest over 8.5 years, we identified 111 (18%) patients with myoclonus. Basic demographics and clinical characteristics of myoclonus were collected. EEG reports, and, when available, raw video EEG, were reviewed, and all findings adjudicated by 3 authors blinded to outcomes. Myoclonus was classified as cortical if there was a preceding, time-locked electrographic correlate and otherwise as subcortical. Outcome at discharge was determined using Cerebral Performance Category. Results/UNASSIGNED:Patients with myoclonus had longer arrests with less favorable characteristics compared to patients without myoclonus. Cortical myoclonus occurred twice as often as subcortical myoclonus (59% vs 23%, respectively). Clinical characteristics during hospitalization did not distinguish the two. Rates of electrographic seizures were higher in patients with cortical myoclonus (43%, vs 8% with subcortical). Survival to discharge was worse for patients with myoclonus compared to those without (26% vs 39%, respectively), but did not differ between subcortical and cortical myoclonus (24% and 26%, respectively). Patients with cortical myoclonus were more likely to be discharged in a comatose state than those with subcortical myoclonus (82% vs 33%, respectively). Among survivors, good functional outcome at discharge was equally possible between those with cortical and subcortical myoclonus (12% and 16%, respectively). Conclusions/UNASSIGNED:Cortical and subcortical myoclonus are seen in every sixth patient with cardiac arrest and cannot be distinguished using clinical criteria. Either condition may have good functional outcomes.

Introduction: Post-anoxic myoclonus is seen in up to 20% of patients who remain comatose, and historically was felt to be a poor prognostic sign. Little distinction has been made in the literature between epileptic (cortical) versus subcortical myoclonus. Methods: 604 cardiac arrest patients in a nine year period that did not return to baseline were admitted to an ICU. We identified 18% (N = 111) with clinical myoclonus. Demographics and characteristics of the arrest were collected and EEG reports were analyzed. Raw EEG including video was reviewed by two epilepsy-trained neurologists, whenever available. Myoclonus was categorized into subcortical and cortical based on presence of a preceding EEG correlate. Patients with cortical myoclonus sufficiently frequent to meet criteria for myoclonic status epilepticus were included. Results: The average age was 63 +/- 17 years, and 29% (N = 32) survived to discharge. 23% of patients had subcortical, 59% cortical, 5% had both subcortical and cortical myoclonus, and in 13% it was impossible to clearly determine the subcategory of myoclonus. Among patients that underwent TTM (n = 99), onset of myoclonus was seen during initiation of cooling in 52%, while at target temperature in 35%, during rewarming in 9%, after fully rewarmed in 1%, and timing was unclear in 3%. Timing of myoclonus did not differ between those with subcortical and cortical myoclonus. No arrest characteristics were associated with each subtype. Survival to discharge did not differ between subcortical and cortical myoclonus (24% and 26%, respectively). Among survivors, 16% of those with subcortical and 18% with cortical myoclonus had a good functional outcome at discharge (Cerebral Performance Category 1-2). One of six patients with both subcortical and cortical myoclonus had a good outcome. Conclusion: Cortical myoclonus is twice as common as subcortical myoclonus, and both can be associated with good outcome

We report a case with therapeutic hypothermia after cardiac arrest where meaningful recovery far exceeded anticipated negative endpoints following cardiac arrest with loss of brainstem reflexes and subsequent status epilepticus. This man survived and recovered after an out-of-hospital cardiac arrest followed by a 6-week coma with absent motor responses and 5 weeks of burst suppression. Standard criteria suggested no chance of recovery. His recovery may relate to the effect of burst-suppression on EEG to rescue neurons near neuronal cell death. Further research to understand the mechanisms of therapeutic hypothermia and late restoration of neuronal functional capacity may improve prediction and aid end-of-life decisions after cardiac arrest.