Optimizing drug-resistant epilepsy identification in the Veterans Health Administration
Our optimal algorithm for DRE identification is like previously published algorithms that determined the importance of number and duration of ASMs. However, it differs in the particular combination of factors that best identified DRE. These differences highlight the importance of fine-tuning algorithms for specific care settings. Further validation in a larger, more heterogenous cohort are needed to determine our algorithm's applicability and potential impact.
Authors
- Rizwana Rehman (ORCID: https://orcid.org/0000-0003-3988-458X)
- Omar Khan (ORCID: https://orcid.org/0000-0003-2879-8790)
- Marissa Kellogg (ORCID: https://orcid.org/0000-0001-7809-7082)
- Maria Lopez (ORCID: https://orcid.org/0000-0003-2421-5682)
- Marcella A Coutts
- Andrea Hildebrand (ORCID: https://orcid.org/0000-0002-1277-1588)
- Zulfi Haneef (ORCID: https://orcid.org/0000-0002-0720-1417)
- Sruthi Gopinath Karicheri
- Stephan J. Eisenschenk (ORCID: https://orcid.org/0000-0002-5778-1755)
Institutions
- Michael E. DeBakey VA Medical Center (US)
- Oregon Health & Science University (US)
- Malcom Randall VA Medical Center (US)
- Bruce W. Carter VA Medical Center (US)
- Durham VA Health Care System (US)
- VA Portland Health Care System (US)
- VA Maryland Health Care System (US)
Publication Details
- Journal
- Epilepsy Research
- Published
- 2025-04-22
- DOI
- https://doi.org/10.1016/j.eplepsyres.2025.107568
- Primary Topic
- Epilepsy research and treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00