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Published on: September 20, 2024
The language of seizure identification: A qualitative investigation
Jacob Pellinen1, Ellen Snyder1, Kelly G Knupp2
1Department of Neurology, University of Colorado School of Medicine, Aurora, CO, USA.
Objective:
Clinical history taking is often the most important factor in seizure recognition and the diagnosis of epilepsy. Apart from subspecialist evaluation, patients frequently present for initial evaluation of seizures in emergency departments, urgent care clinics, and primary care clinics. We utilized qualitative methods to assess the current approaches and language used by both subspecialist and non-specialist physicians when interviewing adult patients with suspected seizures to create a clinical tool to aid in seizure diagnosis.
Methods:
We carried out semi- structured interviews with 10 physicians spanning a range of specialties, practice locations, and clinical experience. This included epilepsy specialists and non-specialists in fields where evaluation of new-onset seizures is common: emergency medicine, internal medicine, and family medicine. Thematic analysis was used to develop a "Seizure Identifier" questionnaire, which was subsequently reviewed by five independent experts for content and face validity.
Results:
Our analysis revealed that across specialties and practice settings, physicians have a structured approach in evaluating patients who present with suspected seizures. Five key characteristics important for identifying seizures emerged across interviews: sudden-onset unprovoked symptoms, short-lasting symptoms, strange or difficult-to-describe symptoms, highly stereotyped symptoms, and postictal symptoms. After independent review, these were translated into an eight-question "Seizure Identifier" tool.
Significance:
This study highlights important concepts for clinical practice regarding seizure identification. Using themes from our analysis, we were able to create a tool that may aid non-specialists in the approach to history taking for adult patients who present with suspected seizures and may help improve time to subspecialist evaluation. Importantly, this tool can be tested in future research for improving seizure recognition and improving timely epilepsy diagnosis.
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