Background and Purpose-RTOG 0933 is a phase II clinical trial of hippocampal avoidance during whole-brain radiotherapy (HA-WBRT) to prevent radiation-induced neurocognitive decline. By quantifying baseline incidence of perihippocampal or hippocampal metastases, we sought to estimate the risk of developing metastases in the hippocampal avoidance region (the hippocampus plus 5mm margin).

IMPORTANCE Continuous electroencephalography (EEG) use in critically ill patients is expanding. There is no validated method to combine risk factors and guide clinicians in assessing seizure risk.OBJECTIVE To use seizure risk factors from EEG and clinical history to create a simple scoring system associated with the probability of seizures in patients with acute illness.

Objective Find the optimal continuous electroencephalographic (CEEG) monitoring duration for seizure detection in critically ill patients. Methods We analyzed prospective data from 665 consecutive CEEGs, including clinical factors and time-to-event emergence of electroencephalographic (EEG) findings over 72 hours. Clinical factors were selected using logistic regression. EEG risk factors were selected a priori. Clinical factors were used for baseline (pre-EEG) risk. EEG findings were used for the creation of a multistate survival model with 3 states (entry, EEG risk, and seizure). EEG risk state is defined by emergence of epileptiform patterns. Results The clinical variables of greatest predictive value were coma (31% had seizures; odds ratio [OR] = 1.8, p<0.01) and history of seizures, either remotely or related to acute illness (34% had seizures; OR = 3.0, p<0.001). If there were no epileptiform findings on EEG, the risk of seizures within 72 hours was between 9% (no clinical risk factors) and 36% (coma and history of seizures). If epileptiform findings developed, the seizure incidence was between 18% (no clinical risk factors) and 64% (coma and history of seizures). In the absence of epileptiform EEG abnormalities, the duration of monitoring needed for seizure risk of <5% was between 0.4 hours (for patients who are not comatose and had no prior seizure) and 16.4 hours (comatose and prior seizure). Interpretation The initial risk of seizures on CEEG is dependent on history of prior seizures and presence of coma. The risk of developing seizures on CEEG decays to <5% by 24 hours if no epileptiform EEG abnormalities emerge, independent of initial clinical risk factors.

Background Ictal-interictal continuum (IIC) continuous EEG (cEEG) patterns including periodic discharges and rhythmic delta activity are associated with poor outcome and in the appropriate clinical context, IIC patterns may represent “electroclinical” status epilepticus (SE). To clarify the significance of IIC patterns and their relationship to “electrographic” SE, we investigated FDG-PET imaging as a complementary metabolic biomarker of SE among patients with IIC patterns. Methods A single-center prospective clinical database was ascertained for patients undergoing FDG-PET during cEEG. Following MRI-PET co-registration, the maximum standardized uptake value in cortical and subcortical regions was compared to contralateral homologous and cerebellar regions. Consensus cEEG review and clinical rating of etiology and treatment response were performed retrospectively with blinding. Electrographic SE was classified as discrete seizures without interictal recovery or >3-Hz rhythmic IIC patterns. Electroclinical SE was classified as IIC patterns with electrographic and clinical response to anticonvulsants; clonic activity; or persistent post-ictal encephalopathy. Results Eighteen hospitalized subjects underwent FDG-PET during contemporaneous IIC patterns attributed to structural lesions (44 %), neuroinflammatory/neuroinfectious disease (39 %), or epilepsy (11 %). FDG-PET hypermetabolism was common (61 %) and predicted electrographic or electroclinical SE (sensitivity 79 % [95 % CI 53–93 %] and specificity 100 % [95 % CI 51–100 %]; p = 0.01). Excluding electrographic SE, hypermetabolism also predicted electroclinical SE (sensitivity 80 % [95 % CI 44–94 %] and specificity 100 % [95 % CI 51–100 %]; p = 0.01). Conclusions In hospitalized patients with IIC EEG patterns, FDG-PET hypermetabolism is common and is a candidate metabolic biomarker of electrographic SE or electroclinical SE.

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IMPORTANCESeizure risk stratification is needed to boost inpatient seizure detection and to improve continuous electroencephalogram (cEEG) cost-effectiveness. 2HELPS2B can address this need but requires validation. OBJECTIVE To use an independent cohort to validate the 2HELPS2B score and develop a practical guide for its use. DESIGN, SETTING, AND PARTICIPANTSThis multicenter retrospective medical record review analyzed clinical and EEG data from patients 18 years or older with a clinical indication for cEEG and an EEG duration of 12 hours or longer who were receiving consecutive cEEG at 6 centers from January 2012 to January 2019. 2HELPS2B was evaluated with the validation cohort using the mean calibration error (CAL), a measure of the difference between prediction and actual results. A Kaplan-Meier survival analysis was used to determine the duration of EEG monitoring to achieve a seizure risk of less than 5% based on the 2HELPS2B score calculated on first-hour (screening) EEG. Participants undergoing elective epilepsy monitoring and those who had experienced cardiac arrest were excluded. No participants who met the inclusion criteria were excluded. MAIN OUTCOMES AND MEASURESThe main outcome was a CAL error of less than 5% in the validation cohort. RESULTSThe study included 2111 participants (median age, 51 years; 1113 men [52.7%]; median EEG duration, 48 hours) and the primary outcome was met with a validation cohort CAL error of 4.0% compared with a CAL of 2.7% in the foundational cohort (P = .13). For the 2HELPS2B score calculated on only the first hour of EEG in those without seizures during that hour, the CAL error remained at less than 5.0% at 4.2% and allowed for stratifying patients into low-(2HELPS2B = 0; <5% risk of seizures), medium-(2HELPS2B = 1; 12% risk of seizures), and high-risk (2HELPS2B, Ն2; risk of seizures, >25%) groups. Each of the categories had an associated minimum recommended duration of EEG monitoring to achieve at least a less than 5% risk of seizures, a 2HELPS2B score of 0 at 1-hour screening EEG, a 2HELPS2B score of 1 at 12 hours, and a 2HELPS2B score of 2 or greater at 24 hours.CONCLUSIONS AND RELEVANCE In this study, 2HELPS2B was validated as a clinical tool to aid in seizure detection, clinical communication, and cEEG use in hospitalized patients. In patients without prior clinical seizures, a screening 1-hour EEG that showed no epileptiform findings was an adequate screen. In patients with any highly epileptiform EEG patterns during the first hour of EEG (ie, a 2HELPS2B score of Ն2), at least 24 hours of recording is recommended.

Highlights Cognitive impairment is a major comorbidity of temporal lobe epilepsy (TLE). Three discrete cognitive phenotypes of TLE are identified here. The phenotypes are linked to network, clinical, and socioeconomic characteristics. This taxonomy advances clinical and theoretical understanding of the cognitive complications of TLE.

Nodal-status and overall pathological-stage significantly affect the prognosis for patients with DA, while resection-status and adjuvant therapy may not. The role of adjuvant therapy requires prospective trials for elucidation.