Accuracy of a Rapid-Response EEG's Automated Seizure-Burden Estimator: AccuRASE Study.

Background And Objectives: The use of rapid response EEG (rr-EEG) has recently expanded in limited-resource settings and as a supplement to conventional EEG to rapidly detect and treat nonconvulsive status epilepticus. The study objective was to test the accuracy of an rr-EEG's automated seizure burden estimator (ASBE).

Methods: This is a retrospective observational study using multiple blinded reviewers. All consecutive clinical rr-EEG procedures performed between November 2019 and February 2021 at Yale New Haven Hospital, one affiliated community hospital, and one affiliated inner-city regional hospital were included. Three reviewers blindly reviewed each EEG. The reference standard was 2/3 agreement. The co-primary outcome measures were the negative predictive value (NPV) of the ASBE for the detection of electrographic status epilepticus (ESE) or possible ESE (ESE/pESE) (to be used as a screening method to exclude ESE without the need for urgent expert review) and the positive predictive value (PPV, to be used for immediate treatment without requiring urgent expert review). These were assessed using a variety of seizure burden cutoffs determined by the algorithm (>1%, >10%, >20%, >50%, and >90%).

Results: In the first 2 hours, a >10% burden cutoff detected 86% (95% CI 42%-100%) of studies with ESE alone and 88% (68%-97%) with ESE/pESE; this >10% cutoff had a NPV of 99% (97%-100%) for ESE and 98% (95%-100%) for ESE/pESE. The specificity at this threshold was 79% (73%-84%) for ESE and 84% (79%-89%) for ESE/pESE, but the PPV was low at 11% (4%-23%) for ESE and 39% (26%-53%) for ESE/pESE. A >90% burden cutoff was 97% (94%-99%) specific for detecting ESE (PPV 33% [7%-70%]) and 99% (97%-100%) specific for detecting ESE/pESE [PPV 78% (40%-97%)], although the sensitivity dropped significantly to 29% (13%-51%) for ESE/pESE and 43% (10%-82%) for ESE at the >90% threshold.

Discussion: The ASBE has high specificity at >90% seizure burden threshold for detecting ESE and ESE/pESE, with good PPV for ESE/pESE, though with only low-to-moderate sensitivity; at this threshold, it can be used to help triage patients for immediate treatment/transfer, urgent expert review, and additional CEEG. A >10% threshold has a high sensitivity, detecting approximately 85% of patients with ESE; at this lower cutoff, it can be used as a screening tool to exclude ESE with >95% NPV.

Classification Of Evidence: This study provides Class II evidence that ASBE software can reliably exclude ESE (98% negative predictive value using a <10% burden cutoff) without expert review in most patients requiring rapid response EEG.