This study was undertaken to identify clinical factors associated with seizure freedom after magnetic resonance-guided laser interstitial thermal therapy (MRgLiTT) in temporal lobe epilepsy patients with unilateral mesial temporal sclerosis (MTS). Methods: We identified 56 patients with magnetic resonance imaging-defined MTS who underwent MRgLiTT with at least 1 year of follow-up. Primary outcome was seizure freedom at 1 year. We examined the association of seizure freedom and the following clinical factors: age at surgery, gender, history of febrile seizures, history of focal to bilateral tonic-clonic seizures, duration of epilepsy at the time of surgery, frequency of interictal epileptiform discharges (IEDs), seizure frequency, and presence of bilateral IEDs.

Since the 1960s, EEG has been used to assess the neurologic function of patients in the hours and days after cardiac arrest. Accurate and reliable prognostication after cardiac arrest is vital for tailoring aggressive patient care for those with a high likelihood of recovery and setting appropriate goals of care for those who have a high likelihood of a poor outcome. Attempts to define EEG’s role in this process has evolved over the years. In this review, we provide important historical context about EEG’s use, it’s perceived unreliability in the post-cardiac arrest patient in the past and provide a detailed analysis of how this role has changed recently. A review of the 71 most recent and highest quality studies demonstrates that the introduction of a uniform classification and a timed approach to EEG analysis have positioned EEG as a complementary tool in the multimodal approach for prognostication. The review was created and intended for medical staff in the intensive care units and emphasizes EEG patterns and timing which portend both favorable and poor prognoses. Also, the review addresses the overall quality of the existing studies and discusses future directions to address the knowledge gaps in this field.

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Objective assessment of the brain’s responsiveness in comatose patients on Extracorporeal Membrane Oxygenation (ECMO) support is essential to clinical care, but current approaches are limited by subjective methodology and inter-rater disagreement. Quantitative electroencephalogram (EEG) algorithms could potentially assist clinicians, improving diagnostic accuracy. We developed a quantitative, stimulus-based algorithm to assess EEG reactivity features in comatose patients on ECMO support. Patients underwent a stimulation protocol of increasing intensity (auditory, peripheral, and nostril stimulation). A total of 129 20-s EEG epochs were collected from 24 patients (age [Formula: see text], 10 females, 14 males) on ECMO support with a Glasgow Coma Scale[Formula: see text]8. EEG reactivity scores ([Formula: see text]-scores) were calculated using aggregated spectral power and permutation entropy for each of five frequency bands ([Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text]. Parameter estimation techniques were applied to [Formula: see text]-scores to identify properties that replicate the decision process of experienced clinicians performing visual analysis. Spectral power changes from audio stimulation were concentrated in the [Formula: see text] band, whereas peripheral stimulation elicited an increase in spectral power across multiple bands, and nostril stimulation changed the entropy of the [Formula: see text] band. The findings of this pilot study on [Formula: see text]-score lay a foundation for a future prediction tool with clinical applications.