Vagus Nerve Stimulation for Drug Resistant Epilepsy: Clinical Outcome, Adverse Events, and Potential Prognostic Factors in a Single Center Experience

Objective: Vagus nerve stimulation (VNS) has been used for adjunctive treatment in drug resistant epilepsy (DRE) for decades. Nevertheless, information is lacking on possible potential prognostic factors. Our study presents the efficacy and safety of VNS with a focus on prognostic factors in 45 patients with DRE. Methods: We retrospectively evaluated the clinical outcome of 45 consecutive patients with DRE undergoing VNS implantation in The First Affiliated Hospital of Anhui Medical University between November 2016 and August 2021. Medical records were aggregated across all patient visits. Cox proportional hazards regression was used to estimate the prognostic factors. Results: Significant decrease in seizure frequency was observed after intermittent stimulation of the vagus nerve. According to the modified McHugh classification, 11 patients (24.4%) were Class I, 11 patients (24.4%) were Class II, four patients (8.9%) were Class III, 10 patients (22.2%) were Class IV, and nine patients (20.0%) were Class V. Notably, 22 patients (48.9%) were responders and four patients (8.9%) were seizure-free at the final follow-up. No significant prognostic factors were found in this cohort. Furthermore, 37 patients reported improved quality of life. Of the patients, 22 (48.9%) experienced adverse events after surgery; hoarseness, discomfort at the surgical site, and coughing were the most common. Conclusion: The results confirmed the efficacy and safety of VNS. No prognostic factors were identified

Effects of Subthalamic Nucleus Deep Brain Stimulation on Depression in Patients with Parkinson’s Disease

Objective: In this study, we aimed to investigate the effects of STN-DBS on PD patients with different levels of depression and to identify predictors of the effects of STN-DBS on PD depression. Methods: We retrospectively collected data for 118 patients with PD depression who underwent STN-DBS at Beijing Tiantan Hospital. Neuropsychological, motor, and quality of life assessments were applied preoperatively and postoperatively. All patients were divided into two groups according to their HAM-D24 total scores (group I: mild depression; group Ⅱ: moderate depression). A mixed repeated-measure analysis of variance (ANOVA) was performed to investigate whether there were differences in depression scores before and after STN-DBS between the two groups. The changes in depression scores were also compared between groups using ANCOVA, adjusting for gender and preoperative HAMA scores. Logistic regression was performed to identify predictors of STN-DBS’s effects on PD depression. Results: Both groups showed significant improvement in depression symptoms after STN-DBS. Compared with patients in group I, patients in group Ⅱ showed greater reductions in their HAM-D24 total scores (p = 0.002) and in HAM-D24 subitems including cognitive disturbances (p = 0.026) and hopelessness symptoms (p = 0.018). Logistic regression indicated that gender (female) (p = 0.014) and preoperative moderate depression (p < 0.001) patients had greater improvements in depression after STN-DBS. Conclusions: Patients with moderate depression showed better improvement than patients with mild depression. Gender (female) and preoperative HAMA scores are predictors of STN-DBS’s effects on PD depression

Generalized sleep decoding with basal ganglia signals in multiple movement disorders.

Sleep disturbances profoundly affect the quality of life in individuals with neurological disorders. Closed-loop deep brain stimulation (DBS) holds promise for alleviating sleep symptoms, however, this technique necessitates automated sleep stage decoding from intracranial signals. We leveraged overnight data from 121 patients with movement disorders (Parkinsons disease, Essential Tremor, Dystonia, Essential Tremor, Huntingtons disease, and Tourettes syndrome) in whom synchronized polysomnograms and basal ganglia local field potentials were recorded, to develop a generalized, multi-class, sleep specific decoder - BGOOSE. This generalized model achieved 85% average accuracy across patients and across disease conditions, even in the presence of recordings from different basal ganglia targets. Furthermore, we also investigated the role of electrocorticography on decoding performances and proposed an optimal decoding map, which was shown to facilitate channel selection for optimal model performances. BGOOSE emerges as a powerful tool for generalized sleep decoding, offering exciting potentials for the precision stimulation delivery of DBS and better management of sleep disturbances in movement disorders