Can heart rate variability identify a high-risk state of upcoming seizure?
Epilepsy Res
; 197: 107232, 2023 11.
Article
en En
| MEDLINE
| ID: mdl-37783038
ABSTRACT
Heart rate variability (HRV) is an accessible and convenient means to assess the sympathetic/parasympathetic balance. Autonomic dysfunctions may reflect a pro-ictal state and occur before the seizure onset. Previous studies have reported HRV-based models to identify preictal states in continuous electrocardiogram (EKG) monitoring. Here, we evaluated the ability of HRV metrics extracted from daily single resting-state periods to estimate the risk of upcoming seizure(s) using probabilistic forecasts. Daily standardized 10-min vigilance-controlled EKG periods were recorded in 15 patients with drug-resistant focal epilepsy who underwent intracerebral electroencephalography (EEG). Analyses of a total of 156 periods, based on machine learning approaches, suggested that HRV features can identify preictal states with a median AUC of 0.75 [0.68;0.99]. Pseudoprospective daily forecasts yielded a median Brier score of 0.3 [0.18;0.48]. About 60% of preictal days were correctly forecasted, while false positive predictions were noticed in 24% of interictal days. Daily resting HRV seems to capture information on autonomic variations that may reflect a pro-ictal state. The method could be embedded in an ambulatory clinical seizure prediction device, but additional modalities (prodromes, EEG-based features, etc.) should be associated to improve its performance.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Enfermedades del Sistema Nervioso Autónomo
/
Epilepsia Refractaria
Tipo de estudio:
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Epilepsy Res
Asunto de la revista:
CEREBRO
/
NEUROLOGIA
Año:
2023
Tipo del documento:
Article