A Nomogram to Predict Seizure Outcomes after Resective Epilepsy Surgery

Project Summary: The full spectrum of neurological manifestations of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has not been clarified. Previous studies have been limited to case series and have describedonly neurological complications observed in patients hospitalized with COVID-19 or admitted to intensive careunits. While these studies provide important information, they do not clarify the range of neurologicalmanifestations in individuals showing different severities of symptoms during infection, the long-term neurologicaleffects of the disease, and they do not provide any understanding of the pathophysiology of the disease.In our current project (1R01NS097719-04-A1), we have constructed a large data and biospecimen infrastructureto develop statistical models for individualized prediction of epileptic seizure-freedom and cognitive outcomesafter resective brain surgery for drug resistant seizures. In this competitive revision application, we propose topair our infrastructure (predictive modeling and genomic expertise) with institutional resources (Cleveland ClinicCOVID-19 Registry and Biobank) to advance the epidemiological and mechanistic understanding of neurologicalcomplications of COVID-19, particularly epilepsy, stroke, and delirium, and to generate nomograms and onlinerisk calculators for the relevant neurological COVID-19 complications.The objectives of this revised proposal are to characterize the incidence and manifestation phenotype of newonset seizures, stroke, and delirium in all patients diagnosed as COVID+ (3,177 as of May 7) in our healthcaresystem, to build and validate prediction models to identify individuals at risk of neurological complications, andto identify systematically disease modules (molecular determinants of disease pathobiology/physiology) forCOVID-19 that can reveal novel underlying mechanisms for SARS-CoV-2 associated neurologicalmanifestations.Older age, smoking, diabetes, hypertension, cardiovascular disease, kidney disease, chronic lung disease, andcancer correlate with progression to severe disease in patients hospitalized with COVID-19. We hypothesize thatthese factors are similarly associated with a higher risk of neurological complications. However, these "riskfactors" are not specific, occur in various combinations, and have limited value as isolated indicators of specificneurological complications. Our team's expertise will be used to generate nomograms and online risk calculatorsfor the relevant neurological complications observed in the CCHS COVID-19 registry cohort, to exploreunderlying mechanisms of these neurological complications using innovative human protein-protein analyses,and to generate tools that can guide decisions in clinical care.