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BackgroundPost-traumatic epilepsy (PTE) is a severe complication of traumatic brain injury (TBI). Electroencephalography aids early post-traumatic seizure diagnosis, but its optimal utility for PTE prediction remains unknown. We aim to evaluate the contribution of quantitative electroencephalograms to predict first-year PTE (PTE1).MethodsWe performed a multicentre, retrospective case–control study of patients with TBI. 63 PTE1patients were matched with 63 non-PTE1patients by admission Glasgow Coma Scale score, age and sex. We evaluated the association of quantitative electroencephalography features with PTE1using logistic regressions and examined their predictive value relative to TBI mechanism and CT abnormalities.ResultsIn the matched cohort (n=126), greater epileptiform burden, suppression burden and beta variability were associated with 4.6 times higher PTE1risk based on multivariable logistic regression analysis (area under the receiver operating characteristic curve, AUC (95% CI) 0.69 (0.60 to 0.78)). Among 116 (92%) patients with available CT reports, adding quantitative electroencephalography features to a combined mechanism and CT model improved performance (AUC (95% CI), 0.71 (0.61 to 0.80) vs 0.61 (0.51 to 0.72)).ConclusionsEpileptiform and spectral characteristics enhance covariates identified on TBI admission and CT abnormalities in PTE1prediction. Future trials should incorporate quantitative electroencephalography features to validate this enhancement of PTE risk stratification models.

Traditional review of EEG for seizure detection requires time and the expertise of a trained neurophysiologist; therefore, it is time- and resource-intensive. Quantitative EEG (qEEG) encompasses a variety of methods to make EEG review more efficient and allows for nonexpert review. Literature supports that qEEG is commonly used by neurophysiologists and nonexperts in clinical practice. In this review, the different types of qEEG trends and spectrograms used for seizure detection in adults, from basic concepts to clinical applications, are discussed. The merits and drawbacks of the most common qEEG trends are detailed. The authors detail the retrospective literature on qEEG sensitivity, specificity, and false alarm rate as interpreted by experts and nonexperts alike. Finally, the authors discuss the future of qEEG as a useful screening tool and speculate on the trajectory of future investigations in the field.

IMPORTANCE: Seizure 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 PARTICIPANTS: This 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 MEASURES: The main outcome was a CAL error of less than 5% in the validation cohort. RESULTS: The 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, ≥2; 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 ≥2), at least 24 hours of recording is recommended.

BackgroundElevated systolic blood pressure (SBP) after mechanical thrombectomy (MT) correlates with worse outcome. However, the association between SBP reduction (SBPr) and outcome after successful reperfusion with MT is not well established.ObjectiveTo investigate the association between SBPr in the first 24 hours after successful reperfusion and the functional and safety outcomes of MT.MethodsA multicenter retrospective study, which included 10 comprehensive stroke centers, was carried out. Patients with acute ischemic stroke and anterior circulation large vessel occlusions who achieved successful reperfusion via MT were included. SBPr was calculated using the formula 100×([admission SBP−mean SBP]/admission SBP). Poor outcome was defined as a modified Rankin Scale (mRS) score of 3–6 at 90 days. Safety endpoints included symptomatic intracerebral hemorrhage, mortality, and requirement for hemicraniectomy during admission. A generalized mixed linear model was used to study the association between SBPr and outcomes.ResultsA total of 1361 patients were included in the final analysis. SBPr as a continuous variable was inversely associated with poor outcome (OR=0.97; 95% CI 0.95 to 0.98; p<0.001) but not with the safety outcomes. Subanalysis based on reperfusion status showed that SBPr was associated with lower odds of poor outcome only in patients with complete reperfusion (modified Thrombolysis in Cerebral Infarction (mTICI 3)) but not in patients with incomplete reperfusion (mTICI 2b). When SBPr was divided into categories (<1%, 1%–10%, 11%–20%, >20%), the rate of poor outcome was highest in the first group.ConclusionSBPr in the first 24 hours after successful reperfusion was inversely associated with poor outcome. No association between SBPr and safety outcome was found.

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Purpose:To describe our population of primary brain tumor (PBT) patients, a subgroup of cancer patients whose intensive care unit (ICU) outcomes are understudied. Methods:Retrospective analysis of PBT patients admitted to an ICU between 2013 to 2018 for an unplanned need. Using descriptive analyses, we characterized our population and their outcomes. Results:Fifty-nine PBT patients were analyzed. ICU mortality was 19% (11/59). The most common indication for admission was seizures (n = 16, 27%). Conclusion:Our ICU mortality of PBT patients was comparable to other solid tumor patients and the general ICU population and better than patients with hematological malignancies. Further study of a larger population would inform guidelines for triaging PBT patients who would most benefit from ICU-level care.

Purpose:To describe our population of primary brain tumor (PBT) patients, a subgroup of cancer patients whose intensive care unit (ICU) outcomes are understudied. Methods:Retrospective analysis of PBT patients admitted to an ICU between 2013 to 2018 for an unplanned need. Using descriptive analyses, we characterized our population and their outcomes. Results:Fifty-nine PBT patients were analyzed. ICU mortality was 19% (11/59). The most common indication for admission was seizures (n = 16, 27%). Conclusion:Our ICU mortality of PBT patients was comparable to other solid tumor patients and the general ICU population and better than patients with hematological malignancies. Further study of a larger population would inform guidelines for triaging PBT patients who would most benefit from ICU-level care.