A Nomogram to Predict Seizure Outcomes after Resective Epilepsy Surgery

点击翻译按钮获取中文摘要

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 described only neurological complications observed in patients hospitalized with COVID-19 or admitted to intensive care units. While these studies provide important information, they do not clarify the range of neurological manifestations in individuals showing different severities of symptoms during infection, the long-term neurological effects 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 infrastructure to develop statistical models for individualized prediction of epileptic seizure-freedom and cognitive outcomes after resective brain surgery for drug resistant seizures. In this competitive revision application, we propose to pair our infrastructure (predictive modeling and genomic expertise) with institutional resources (Cleveland Clinic COVID-19 Registry and Biobank) to advance the epidemiological and mechanistic understanding of neurological complications of COVID-19, particularly epilepsy, stroke, and delirium, and to generate nomograms and online risk calculators for the relevant neurological COVID-19 complications. The objectives of this revised proposal are to characterize the incidence and manifestation phenotype of new onset seizures, stroke, and delirium in all patients diagnosed as COVID+ (3,177 as of May 7) in our healthcare system, to build and validate prediction models to identify individuals at risk of neurological complications, and to identify systematically disease modules (molecular determinants of disease pathobiology/physiology) for COVID-19 that can reveal novel underlying mechanisms for SARS-CoV-2 associated neurological manifestations. Older age, smoking, diabetes, hypertension, cardiovascular disease, kidney disease, chronic lung disease, and cancer correlate with progression to severe disease in patients hospitalized with COVID-19. We hypothesize that these factors are similarly associated with a higher risk of neurological complications. However, these “risk factors” are not specific, occur in various combinations, and have limited value as isolated indicators of specific neurological complications. Our team's expertise will be used to generate nomograms and online risk calculators for the relevant neurological complications observed in the CCHS COVID-19 registry cohort, to explore underlying mechanisms of these neurological complications using innovative human protein-protein analyses, and to generate tools that can guide decisions in clinical care.