Kristen Sparrow • September 07, 2018
This article achieves something that has always been on the back burner of my HRV project. That is, can we tell something about people’s likelihood to respond to treatment before we treat them, by analyzing their HRV? In my earliest research, I saw a correlation with patients’ stress response (LF/HF) on the treatment table with likelihood of clinical response. This paper asks a different question. It is established that vagal nerve stimulators don’t work on everyone. So they are asking whether we can tell something about the patients’ propensity to respond to an indwelling vagal nerve stimulator by their baseline HRV. Keep in mind, that this would extremely useful since vagal nerve stimulators have side effects and require surgery to implant them. But I’ve wondered the same thing about TAVNS. Can we tell whether non-invasive vagal nerve stimulators would be effective beforehand looking at their baseline HRV? Obviously, the downsides of just trying TAVNS are much less than implanted vagal nerve stimulators.
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.