Abstract
Vagus nerve stimulation (VNS) is an adjunctive treatment for drug-resistant epilepsy (DRE). However, it is still difficult to predict which patients will respond to VNS treatment and to what extent. We aim to explore the relationship between preoperative heart rate variability (HRV) and VNS outcome. 50 healthy control subjects and 63 DRE patients who had received VNS implants and had at least one year of follow up were included. The preoperative HRV were analyzed by traditional linear methods and heart rhythm complexity analyses with multiscale entropy (MSE). DRE patients had significantly lower complexity indices (CI) as well as traditional linear HRV measurements than healthy controls. We also found that non-responders0 had significantly lower preoperative CI including Area 1–5, Area 6–15 and Area 6–20 than those in the responders0 while those of the non-responders50 had significantly lower RMSSD, pNN50, VLF, LF, HF, TP and LF/HF than the responders50. In receiver operating characteristic (ROC) curve analysis, Area 6–20 and RMSSD had the greatest discriminatory power for the responders0 and non-responders0, responders50 and non-responders50, respectively. Our results suggest that preoperative assessment of HRV by linear and MSE analysis can help in predicting VNS outcomes in patients with DRE.
Highlights
Epilepsy, characterized by recurrent and unprovoked seizures, is one of the most common and serious, chronic neurological disorders that affects around 65 million people worldwide[1]
The present study aimed to investigate whether preoperative heart rate variability (HRV), as quantified by traditional linear measurements and non-linear heart rhythm complexity, are predictors for seizure reduction of Vagus nerve stimulation (VNS) treatment in patients with drug-resistant epilepsy (DRE)
Demographic data, clinical factors and physical activity of DRE patients and healthy control subjects are presented in Table 1 and Table S-1
Summary
Epilepsy, characterized by recurrent and unprovoked seizures, is one of the most common and serious, chronic neurological disorders that affects around 65 million people worldwide[1]. Prognostic biomarkers will be very useful for counselling patients and predicting the VNS seizure control outcome. Conventional linear algorithms are often applied to calculate measures of HRV, even though the modulation of the autonomic nervous system (ANS) on cardiac activity is considered to be a nonlinear physiological process with non-stationary property, and their prognostic values for VNS outcome in patients with DRE were unclear[10,11,12]. MSE analysis of heart rate dynamics in DRE patients and its association with VNS outcome have not been studied previously. The present study aimed to investigate whether preoperative HRV, as quantified by traditional linear measurements and non-linear heart rhythm complexity, are predictors for seizure reduction of VNS treatment in patients with DRE
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