To Wean or Not to Wean: Machine Learning to the Rescue

Abstract

Electrographic Predictors of Successful Weaning From Anaesthetics in Refractory Status Epilepticus Rubin DB, Angelini B, Shoukat M, Chu CJ, Zafar SF, Westover MB, Cash SS, Rosenthal ES. Brain. 2020;143(4):1143-1157. doi:10.1093/brain/awaa069 Intravenous third-line anesthetic agents are typically titrated in refractory status epilepticus to achieve either seizure suppression or burst suppression on continuous EEG. However, the optimum treatment paradigm is unknown and little data exist to guide the withdrawal of anesthetics in refractory status epilepticus. Premature withdrawal of anesthetics risks the recurrence of seizures, whereas the prolonged use of anesthetics increases the risk of treatment-associated adverse effects. This study sought to measure the accuracy of features of EEG activity during anesthetic weaning in refractory status epilepticus as predictors of successful weaning from intravenous anesthetics. We prespecified a successful anesthetic wean as the discontinuation of intravenous anesthesia without developing recurrent status epilepticus, and a wean failure as either recurrent status epilepticus or the resumption of anesthesia for the purpose of treating an EEG pattern concerning for incipient status epilepticus. We evaluated 2 types of features as predictors of successful weaning: spectral components of the EEG signal and spatial-correlation-based measures of functional connectivity. The results of these analyses were used to train a classifier to predict wean outcome. Forty-seven consecutive anesthetic weans (23 successes, 24 failures) were identified from a single-center cohort of patients admitted with refractory status epilepticus from 2016 to 2019. Spectral components of the EEG revealed no significant differences between successful and unsuccessful weans. Analysis of functional connectivity measures revealed that successful anesthetic weans were characterized by the emergence of larger, more densely connected, and more highly clustered spatial functional networks, yielding 75.5% (95% CI: 73.1%-77.8%) testing accuracy in a bootstrap analysis using a holdout sample of 20% of data for testing and 74.6% (95% CI: 73.2%-75.9%) testing accuracy in a secondary external validation cohort, with an area under the curve of 83.3%. Distinct signatures in the spatial networks of functional connectivity emerge during successful anesthetic liberation in status epilepticus; these findings are absent in patients with anesthetic wean failure. Identifying features that emerge during successful anesthetic weaning may allow faster and more successful anesthetic liberation after refractory status epilepticus.