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Clinical Trial Summary

1. Accuracy of seizure diagnosis based on smartphone seizure semiology anaysis 2. Assess the factors that affect the diagnostic reliability of smartphone videos


Clinical Trial Description

E pilepsy has a substantial global burden of disease.1 Diagnosis is made clinically based on a historical recount of witnessed events and a laboratory assessment. Differential diagnosis for seizures is broad. Even seasoned clinicians can be misled when individuals lack medical knowledge or pertinent terminology to accurately represent witnessed seizure behavior.2Video electroencephalogram (EEG) monitoring (VEM) is recommended when there is diagnostic uncertainty in classifying seizure type or epilepsy syndrome.3 Video EEG monitoring provides objective evidence for definitive diagnosis4 ;Additionally, VEM may not be practical for some patients because of relative infrequency of events Geographic limitations, transportation constraints, and insurance coverage may also restrict access.2,4 While VEM is the criterion standard for seizure diagnosis, web-based smartphone use has become a popular means to augment clinical practice involving seizure reporting by people with epilepsy. However, smartphone videos are not recorded in a controlled environment in which the clinicians themselves are able to define when and how each spell is to be recorded,. As such, there are issues of focus, lighting, duration, and initiation that must be considered when interpreting homemade smartphone video recordings obtained by a lay population of caregivers to evaluate people with seizures on the other hand, it has been proven that discriminating seizure's semiology is a learned skill and requires specific neurologic training 11We hypothesize that outpatient smartphone videos predictive value in patients referred for evaluation of epilepsy is variable and depends on multiple factors such as seizure semiology, and interpreting physician . on the other hand, there is no consensus on quality standards and safety recommendation of smartphone videos. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT05574725
Study type Observational
Source Assiut University
Contact Hend Mohamed Abd El Moez eissa, Resident doctor
Phone 01094794071
Email hendelmahdy1995@gmail.com
Status Not yet recruiting
Phase
Start date October 20, 2022
Completion date October 20, 2023