Improving epilepsy diagnosis across the lifespan: approaches and innovations.

Journal: The Lancet. Neurology
PMID:

Abstract

Epilepsy diagnosis is often delayed or inaccurate, exposing people to ongoing seizures and their substantial consequences until effective treatment is initiated. Important factors contributing to this problem include delayed recognition of seizure symptoms by patients and eyewitnesses; cultural, geographical, and financial barriers to seeking health care; and missed or delayed diagnosis by health-care providers. Epilepsy diagnosis involves several steps. The first step is recognition of epileptic seizures; next is classification of epilepsy type and whether an epilepsy syndrome is present; finally, the underlying epilepsy-associated comorbidities and potential causes must be identified, which differ across the lifespan. Clinical history, elicited from patients and eyewitnesses, is a fundamental component of the diagnostic pathway. Recent technological advances, including smartphone videography and genetic testing, are increasingly used in routine practice. Innovations in technology, such as artificial intelligence, could provide new possibilities for directly and indirectly detecting epilepsy and might make valuable contributions to diagnostic algorithms in the future.

Authors

  • Jacob Pellinen
    Department of Neurology, University of Colorado School of Medicine, Aurora, CO, USA. Electronic address: Jacob.Pellinen@cuanschutz.edu.
  • Emma C Foster
    Department of Neurosciences, Central Clinical School, Monash University, Melbourne, VIC, Australia.
  • Jo M Wilmshurst
    Red Cross War Memorial Children's Hospital and University of Cape Town Neuroscience Institute, Cape Town, South Africa.
  • Sameer M Zuberi
    Royal Hospital for Children and University of Glasgow School of Health & Wellbeing, Glasgow, UK.
  • Jacqueline French
    Comprehensive Epilepsy Center, Department of Neurology, School of Medicine, New York University, New York, USA.