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Classifying epilepsy pragmatically: Past, present, and future
The classification of epilepsy is essential for people with epilepsy and their families, healthcare providers, physicians and researchers. The International League Against Epilepsy proposed updated seizure and epilepsy classifications in 2017, while another four-dimensional epilepsy classification w...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7613525/ https://www.ncbi.nlm.nih.gov/pubmed/34174531 http://dx.doi.org/10.1016/j.jns.2021.117515 |
Sumario: | The classification of epilepsy is essential for people with epilepsy and their families, healthcare providers, physicians and researchers. The International League Against Epilepsy proposed updated seizure and epilepsy classifications in 2017, while another four-dimensional epilepsy classification was updated in 2019. An Integrated Epilepsy Classification system was proposed in 2020. Existing classifications, however, lack consideration of important pragmatic factors relevant to the day-to-day life of people with epilepsy and stakeholders. Despite promising developments, consideration of comorbidities in brain development, genetic causes, and environmental triggers of epilepsy remains largely user-dependent in existing classifications. Demographics of epilepsy have changed over time, while existing classification schemes exhibit caveats. A pragmatic classification scheme should incorporate these factors to provide a nuanced classification. Validation across disparate contexts will ensure widespread applicability and ease of use. A team-based approach may simplify communication between healthcare personnel, while an individual-centred perspective may empower people with epilepsy. Together, incorporating these elements into a modern but pragmatic classification scheme may ensure optimal care for people with epilepsy by emphasising cohesiveness among its myriad users. Technological advancements such as 7T MRI, next-generation sequencing, and artificial intelligence may affect future classification efforts. |
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