PurposeNeurosurgery appears to be a reasonable alternative in carefully selected patients with refractory status epilepticus (RSE) and super-refractory status epilepticus (SRSE). We discuss the optimal timing of the surgery and the use of previous stereoelectroencephalography (SEEG) invasive evaluation.MethodsWe identified 3 patients (two pediatric and one adult) who underwent epilepsy surgery because of RSE or SRSE from our epilepsy surgery database, one of them with previous SEEG.ResultsStatus epilepticus resolved acutely in all of them with no mortality and no substantial morbidity. At follow-up (median: 2 years), 1 patient was seizure-free, and 2 had significant improvement.ConclusionSurgery should be considered in all cases of RSE and SRSE early in the course of the evolution of the disease.

Introduction: Pandemics pose a major challenge for public health preparedness, requiring a coordinated international response and the development of solid containment plans. An early and accurate identification of high-risk patients in the course of the actual COVID-19 pandemic is vital for planning and for making proper use of available resources. Objective: The purpose of this study was to identify the key variables to create a predictive model that could be used effectively for triage. Method: A narrative literature review of 651 articles was conducted to assess clinical, laboratory and imaging findings of COVID-19 confirmed cases. After screening, 10 articles met the inclusion criteria and a list of suggested variables was gathered. A modified Delphi process analysis was performed to consult experts in order to generate a final list of variables for the creation of the predictive model. Results: The modified Delphi process analysis identified 44 predictive variables that were used for building a severity prediction score, the COVID-19 Severity Index. Conclusion: Specifically designed for current COVID-19 pandemic, COVID-19 Severity Index could be used as a reliable tool for strategic planning, organization and administration of resources by easily identifying hospitalized patients with higher risk of transfer to Intensive Care Unit (ICU).

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