Use of Sympatho-vagal balance derived from Heart Rate Variability during cardiac recordings to establish ""Signatures"" of different causes of seizures.
Abstract number :
3.089
Submission category :
1. Translational Research: 1D. Devices, Technologies, Stem Cells
Year :
2015
Submission ID :
2325096
Source :
www.aesnet.org
Presentation date :
12/7/2015 12:00:00 AM
Published date :
Nov 13, 2015, 12:43 PM
Authors :
Paul Cooper, N Virag, A Anwar, Suzanne Crampton, M de Melis, R Sutton, A Fitzpatrick
Rationale: We believe that analysis of cardiac derived parameters immediately before and during a blackout may define distinct patterns, or ""signatures"", which can be used to distinguish syncope, epilepsy and psychogenic attacks, the three most common causes of blackouts. There are recognized difficulties in the diagnosis of the cause of a blackout. Routine EEG recordings are often unhelpful and may be misleading. Only small numbers of patients can be admitted for prolonged monitoring, and it is unrealistic to record EEG for more than a couple of days, without hospital admission. Our hypothesis is that sufficient information can be extracted by signal processing of the ECG, allowing ECG recordings to establish the diagnosis without a prolonged Epilepsy Monitoring Unit (EMU) admission.Methods: All patients admitted to the EMU were considered for the study. Patients were selected for analysis if they experienced loss of consciousness with associated loss of posture; that is blackouts with or without convulsive movements that would result in a fall. For comparison patients with tilt-induced reflex syncope, assessed in the Syncope Clinic, had the same analysis. RR intervals were extracted from the ECG signal after de-noising. Then 2 signals were computed: the percentage of marginal RR intervals, and the sympatho-vagal balance based on heart-rate variability analysis (HRV). Marginal RR intervals were defined as the percentage of RR values outside a confidence interval (window size of 40 beats) determined during 10 minute baseline recording. HRV was analyzed using a parametric spectral estimation with a sliding analysis window of 60-240s, shifted by 5-20s increments. The sympatho-vagal balance was the ratio of low frequency components (LF: 0.04 Hz-0.15Hz, sympathetic activity) versus high frequency components (HF: 0.15-0.4 Hz, parasympathetic activity).Results: A total of 45 patients were analyzed: In EMU patients video-EEG confirmed that 17 had an epileptic seizures and 8 psychogenic attacks. The 20 syncope patients all had vasovagal syncope Sympatho-vagal balance alone did not show to be significant discrimination between the 3 types of blackouts. However we found RR marginality discriminant with values over 30% during epileptic seizures, 10% in psychogenic attacks and almost zero in reflex syncope.Conclusions: An EMU admission is a limited and costly resource, and furthermore it may not be possible to capture a habitual episode in a short admission. Implantable technology can however record ECG over many months, with minimal inconvenience to the patient, allowing capture of spontaneous episodes. This preliminary study suggests that data extracted from the ECG captured during typical episodes may provide a signature that can reliably discriminate between common causes of blackouts, without the need for inconvenience and cost of admission.
Translational Research