PURPOSE: Untreated epilepsy is a major global public health problem with more than 20 million people not being treated for an easily treatable disease. In part this is due to a lack of trained doctors. There are many more non-medical health workers than doctors and they could have an important role in diagnosis and treatment of epilepsy if they had some tools. We have previously described such a tool to distinguish epileptic episodes from other causes of altered consciousness and here present its validation in three new populations. METHODS: The tool was presented as a phone app where the answers to 11 questions provided a probability score which indicated whether episodes might be due to epilepsy or not. It was applied either by non-medical volunteers, health workers, or inexperienced doctors to 132 patients in three separate populations in India and Nepal and compared with the "gold standard" diagnosis of a neurologist with expertise in epilepsy. RESULTS: There was good agreement between the app score and the neurologists' diagnoses (weighted kappa=75.3%). An app score of 90 or greater had a sensitivity of 88% and a specificity of 100% for diagnosing epilepsy. The app was easy to use with little training and took about 5min to administer. CONCLUSION: A tool presented as a phone app can be used by non-medical health workers to identify episodes as epileptic or not with good accuracy. It needs to be evaluated more widely but has the potential to play a part in reducing the epilepsy treatment gap.
PURPOSE: Untreated epilepsy is a major global public health problem with more than 20 million people not being treated for an easily treatable disease. In part this is due to a lack of trained doctors. There are many more non-medical health workers than doctors and they could have an important role in diagnosis and treatment of epilepsy if they had some tools. We have previously described such a tool to distinguish epileptic episodes from other causes of altered consciousness and here present its validation in three new populations. METHODS: The tool was presented as a phone app where the answers to 11 questions provided a probability score which indicated whether episodes might be due to epilepsy or not. It was applied either by non-medical volunteers, health workers, or inexperienced doctors to 132 patients in three separate populations in India and Nepal and compared with the "gold standard" diagnosis of a neurologist with expertise in epilepsy. RESULTS: There was good agreement between the app score and the neurologists' diagnoses (weighted kappa=75.3%). An app score of 90 or greater had a sensitivity of 88% and a specificity of 100% for diagnosing epilepsy. The app was easy to use with little training and took about 5min to administer. CONCLUSION: A tool presented as a phone app can be used by non-medical health workers to identify episodes as epileptic or not with good accuracy. It needs to be evaluated more widely but has the potential to play a part in reducing the epilepsy treatment gap.
Authors: Christopher B Eaton; Rhys H Thomas; Khalid Hamandi; Gareth C Payne; Michael P Kerr; David E J Linden; Michael J Owen; Adam C Cunningham; Ullrich Bartsch; Siske S Struik; Marianne B M van den Bree Journal: Epilepsia Date: 2020-03-02 Impact factor: 6.740
Authors: Guillermo Molina Recio; Laura García-Hernández; Rafael Molina Luque; Lorenzo Salas-Morera Journal: Biomed Eng Online Date: 2016-07-15 Impact factor: 2.819