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A clinical evaluation of a novel algorithm in the reliable detection of epileptic seizures.
Brotherstone, Ruth; McLellan, Ailsa; Graham, Catriona; Fisher, Katie.
Afiliación
  • Brotherstone R; Department of Clinical Neurophysiology, Department of Clinical Neurosciences, OPD15, Little France, Edinburgh, UK. Electronic address: ruth.brotherstone@nhslothian.scot.nhs.uk.
  • McLellan A; Department of Paediatric Neurosciences, Royal Hospital for Sick Children, Edinburgh, UK.
  • Graham C; Edinburgh Clinical Research Facility, University of Edinburgh, Western General Hospital, Edinburgh, UK.
  • Fisher K; Royal Hospital for Sick Children, Edinburgh, UK.
Seizure ; 82: 109-117, 2020 Nov.
Article en En | MEDLINE | ID: mdl-33068957
PURPOSE: Undetected and prolonged epileptic seizures can result in hypoxic brain damage or death and occur most often when the victim is in bed alone or unsupervised. Sudden unexpected death in epilepsy may not always be preventable but it is believed that timely assistance with rescue medication and body re-positioning may overcome respiratory compromise in some cases. A novel algorithm based on a real time moving 9 s epoch, calculating 25 % percentage heart rate change and/or an oxygen saturation trigger level of <85 % was developed using photoplethysmography and incorporated into a prototype data storage device. METHODS: The algorithm was clinically evaluated in this multicentre trial in the detection of clinically significant epileptic seizures. A range of epileptic seizures and normal physiological events were recorded and classified by reference standard EEG Videotelemetry and time-synchronised event data recorded by the prototype device incorporating the pre-specified cut-off points prospectively and retrospective analysis of all events. RESULTS: 119 participants who were attending electroencephalographic (EEG) videotelemetry as part of their clinical management of their epilepsy consented to take part in the trial. 683 epileptic seizures (77 clinically significant seizures) and 2648 normal physiological events were captured. When using pre-specified cut-off point 25 % heart rate change and/or oxygen desaturation <85 % on the basis of one/other, the device showed a sensitivity of 87 % for detecting clinically significant seizures. False Alarm Rate 4.5 (24 h FAR), detection latency of 58 s using heart rate percentage change. CONCLUSIONS: The results indicate that the novel algorithm can be used in detecting clinically significant seizures.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Convulsiones / Algoritmos / Epilepsia Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies Límite: Humans Idioma: En Revista: Seizure Asunto de la revista: NEUROLOGIA Año: 2020 Tipo del documento: Article Pais de publicación: Reino Unido
Texto completo
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XML
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Convulsiones / Algoritmos / Epilepsia Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies Límite: Humans Idioma: En Revista: Seizure Asunto de la revista: NEUROLOGIA Año: 2020 Tipo del documento: Article Pais de publicación: Reino Unido