# A Nomogram to Predict Seizure Outcomes after Resective Epilepsy Surgery

> **NIH NIH R01** · CLEVELAND CLINIC LERNER COM-CWRU · 2020 · $308,248

## Abstract

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.

## Key facts

- **NIH application ID:** 10181321
- **Project number:** 3R01NS097719-04S1
- **Recipient organization:** CLEVELAND CLINIC LERNER COM-CWRU
- **Principal Investigator:** Lara Jehi
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $308,248
- **Award type:** 3
- **Project period:** 2020-07-01 → 2023-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10181321

## Citation

> US National Institutes of Health, RePORTER application 10181321, A Nomogram to Predict Seizure Outcomes after Resective Epilepsy Surgery (3R01NS097719-04S1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10181321. Licensed CC0.

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