Pupillary response to percutaneous auricular vagus nerve stimulation in alcohol withdrawal syndrome: A pilot trial.

BACKGROUND: Autonomic symptoms in alcohol withdrawal syndrome (AWS) are associated with a sympathetic-driven imbalance of the autonomic nervous system. To restore autonomic balance in AWS, novel neuromodulatory approaches could be beneficial. We conducted a pilot trial with percutaneous auricular vagus nerve stimulation (pVNS) in AWS and hypothesized that pVNS will enhance the parasympathetic tone represented by a reduction of pupillary dilation in a parasympatholytic pharmacological challenge. METHODS: Thirty patients suffering from alcohol use disorder, undergoing AWS, and stable on medication, were recruited in this open-label, single-arm pilot trial with repeated-measure design. Peripheral VNS (monophasic volt impulses of 1 msec, alternating polarity, frequency 1 Hz, amplitude 4 mV) was administered at the left cymba conchae for 72 h, followed by pupillometry under a tropicamide challenge. We assessed craving with a visual analog scale. We used pupillary mean as the dependent variable in a repeated-measures ANOVA (rmANOVA). RESULTS: A repeated-measures ANOVA resulted in a significant difference for pupillary diameter across time and condition (F(2,116) = 27.97, p < .001, ηp2 > .14). Tukey-adjusted post hoc analysis revealed a significant reduction of pupillary diameter after pVNS. Alcohol craving was significantly reduced after pVNS (p < .05, Cohen's d = 1.27). CONCLUSION: Our study suggests that pVNS activates the parasympathetic nervous system in patients with acute AWS, and that this activation is measurable by pupillometry. To this end, pVNS could be beneficial as a supportive therapy for AWS. Potential confounding effects of anti-craving treatment should be kept in mind.

Automatic multimodal detection for long-term seizure documentation in epilepsy.

OBJECTIVE: This study investigated sensitivity and false detection rate of a multimodal automatic seizure detection algorithm and the applicability to reduced electrode montages for long-term seizure documentation in epilepsy patients. METHODS: An automatic seizure detection algorithm based on EEG, EMG, and ECG signals was developed. EEG/ECG recordings of 92 patients from two epilepsy monitoring units including 494 seizures were used to assess detection performance. EMG data were extracted by bandpass filtering of EEG signals. Sensitivity and false detection rate were evaluated for each signal modality and for reduced electrode montages. RESULTS: All focal seizures evolving to bilateral tonic-clonic (BTCS, n=50) and 89% of focal seizures (FS, n=139) were detected. Average sensitivity in temporal lobe epilepsy (TLE) patients was 94% and 74% in extratemporal lobe epilepsy (XTLE) patients. Overall detection sensitivity was 86%. Average false detection rate was 12.8 false detections in 24h (FD/24h) for TLE and 22 FD/24h in XTLE patients. Utilization of 8 frontal and temporal electrodes reduced average sensitivity from 86% to 81%. CONCLUSION: Our automatic multimodal seizure detection algorithm shows high sensitivity with full and reduced electrode montages. SIGNIFICANCE: Evaluation of different signal modalities and electrode montages paces the way for semi-automatic seizure documentation systems.