The SANTÉ study at 10 years of follow‐up: Effectiveness, safety, and sudden unexpected death in epilepsy

Salanova, Vicenta; Sperling, Michael R.; Gross, Robert E.; Irwin, Chris P.; Vollhaber, Jim A.; Giftakis, Jonathon E.; Fisher, Robert S.

doi:10.1111/epi.16895

Cited by 174 publications

(241 citation statements)

References 47 publications

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“…7,8 Intriguingly, a newly approved iteration of the Medtronic DBS device has the potential to provide closed-loop stimulation by recording ongoing thalamic background local field potential and triggering stimulation upon detection of a thalamic "signature" that relates to epileptiform activity. 9,10 While the study by Salanova et al 4 demonstrates that the efficacy of ANT DBS improves over time, with acceptable safety and tolerability, important questions remain unanswered. What are the optimum thalamic stimulation parameters?…”

Section: Commentarymentioning

confidence: 99%

“…Recently, the long-term efficacy and safety of ANT DBS of patients who were followed for at least 7 years and some for 10 years was reported. 4 Of the initial cohort of 110 patients, 73 were followed with office visits every 6 months along with monthly diary collection. Antiseizure drugs and neurostimulation settings could be changed at the discretion of the clinician, with only 1 subject remaining on the original SANTĖ settings, but with limitation on the charge density that could be delivered.…”

Section: Commentarymentioning

confidence: 99%

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Cheers for SANTĖ: Long Term Safety and Efficacy of Anterior Nucleus of the Thalamus DBS

King-Stephens¹

2021

Epilepsy Curr

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We evaluated the efficacy and safety of deep brain anterior thalamus stimulation after 7 and 10 years and report the incidence of sudden unexpected death in epilepsy (SUDEP) and overall mortality in adults in the Stimulation of the Anterior Nucleus of the Thalamus for Epilepsy (SANTÉ) study. Methods: After the 3-month blinded and 9-month unblinded phases, subjects continued to be assessed during long-term follow-up (LTFU) and later a continued therapy access phase (CAP), to further characterize adverse events and the incidence of SUDEP. Stimulus parameter and medication changes were allowed. Results: One hundred ten implanted subjects accumulated a total of 938 device-years of experience (69 subjects during the LTFU phase and 61 subjects in the CAP phase). Prior to study closure, 57 active subjects continued therapy at 14 study centers, with follow-up of at least 10 (maximum 14) years. At 7 years, median seizure frequency percent reduction from baseline was 75% (P< .001), with no outcome differences related to prior vagus nerve stimulation or resective surgery. The most severe seizure type, focal to bilateral tonic-clonic, was reduced by 71%. Adding new antiseizure medications did not impact the pattern of seizure reduction over time. There were no unanticipated serious adverse events in the study. The definite-plus-probable SUDEP rate, based on SANTÉ study experience (2 deaths in 938 years) and previous pilot studies (0 deaths in 76 years), indicated a rate of 2.0 deaths for 1000 person-years. Overall mortality was 6.9 deaths per 1000 person-years. Significance: The long-term efficacy and safety profiles of the deep brain stimulation (DBS) system for epilepsy are favorable and demonstrate stable outcomes. Improvement in frequency of the most severe seizure type may reduce SUDEP risk. The SUDEP rate with DBS (2.0) is comparable to other neuromodulation treatments (ie, vagus nerve stimulation, responsive neurostimulation) for drugresistant focal epilepsy.

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Section: Commentarymentioning

confidence: 99%

Section: Commentarymentioning

confidence: 99%

Cheers for SANTĖ: Long Term Safety and Efficacy of Anterior Nucleus of the Thalamus DBS

King-Stephens¹

2021

Epilepsy Curr

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“…Despite the potential impact of ANT stimulation on HPC-based sleep classification, we observed acceptable classifier performance during both high and low frequency ANT stimulation. Although 2 Hz EBS, corrupted the iEEG power spectrum at the stimulation frequency and its harmonics (2,4,6,Hz,etc), the average performance across all subjects was good (F1_ALL = 0.870). Awake (F1_Awake = 0.846) and NREM (F1_NREM=0.903) classification precision was superior to REM (F1_REM = 0.634).…”

Section: Assessment Of Automated Sleep Scoring From Hippocampal Ieeg During Low Frequency and High Frequency Electrical Brain Stimulationmentioning

confidence: 99%

Electrical Brain Stimulation and Continuous Behavioral State Tracking in Ambulatory Humans

Mívalt

Kremen

Sladky

et al. 2021

Preprint

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Electrical brain stimulation (EBS) is an established treatment for patients with drug-resistant epilepsy. Sleep disorders are common in people with epilepsy and EBS therapies may actually further disturb normal sleep patterns and sleep quality. Novel devices capable of EBS and continuous intracranial EEG (iEEG) telemetry enable detailed assessments of therapy efficacy and tracking of sleep and comorbidities. Here, we investigate the feasibility of automated sleep classification using continuous iEEG data recorded from Papez's circuit in four patients with drug resistant mesial temporal lobe epilepsy using an investigational implantable sensing and stimulation device with electrodes implanted in bilateral hippocampus (HPC) and anterior nucleus of thalamus (ANT). The iEEG recorded from HPC are used to classify sleep during concurent ANT stimulation. Simultaneous polysomnography and HPC sensing was were used to train, validate and test an automated classifier for a range of ANT EBS frequencies (2 Hz, 7Hz, 100Hz, and 145 Hz). We show that it is possible to build a patient specific automated sleep staging classifier using power in band features extracted from one HPC sensing channel. The patient specific classifiers performed well under all thalamic EBS frequencies with an average F1-score 0.894, and provided viable classification into major sleep categories (Awake, NREM, REM). Within this project, we retrospectively analyzed classification performance with gold-standard polysomnography annotations, and then prospectively deployed the classifier on chronic continuous iEEG data spanning multiple months to characterize sleep patterns in ambulatory patients living in their home environment. The ability to continuously track behavioral state and fully characterize sleep should prove useful for optimizing EBS for epilepsy and associated sleep, cognitive and mood comorbidities.

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“…The optimization of stimulation is however difficult and long-term seizure freedom is rare (Bergey et al, 2015;Nair et al, 2020;Salanova et al, 2021). The relevance of circadian rhythmicity in epilepsy has been recognised (Khan et al, 2018) but due to technology limitations of neuromodulation devices to-date, few clinical studies have investigated the rhythmicity and periodicity of seizures and their associated epileptiform brain activity.…”

Section: Case Study 2 -Epilepsymentioning

confidence: 99%

Embedding Digital Chronotherapy into Bioelectronic Medicines

Denison

2021

Proceedings of the Neural Interfaces and Artificial Senses

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Biological rhythms permeate all living organisms at a variety of timescales. These rhythms are fundamental to physiological homeostasis, and their disruption is thought to play a key role in the initiation, progression, and expression of disease. In the last two decades, neuromodulation has been established as an effective adjunct therapy for medically refractory neurological disorders.To date, however, due to the limited sensing and algorithm capabilities of neuromodulation devices, exploring the influence of biological rhythms on therapy efficacy has not been feasible. However, with the development of new bioelectronic devices capable of long-term data recording and adaptive stimulation parameter adjustments, clinical neuroscience researchers are now gaining unprecedented insight into patient physiology across a variety of neurological diseases, including longitudinal rhythmic behavior. In this perspective, we propose that future bioelectronic devices 2 should integrate chronobiological considerations in their physiological control structure to maximize the benefits of therapy. We specifically highlight this need for deep brain stimulation (DBS) chronotherapy, where the DBS therapeutic dosage would be titrated based on the time-ofday and synchronized to each patient's individual chronotype/sleep-wake cycle. This is motivated by preliminary longitudinal data recorded from both patients with Parkinson's disease (PD) and epilepsy, which show periodic symptom biomarkers synchronized to sub-daily (ultradian), daily (circadian 1 ), and longer time scale (infradian) rhythms. In addition, considering side effects, tonic stimulation can undermine diurnal patterns and cause fragmentation of sleep-wake rhythms. Based on these observations, we suggest a control structure for future bioelectronic devices which incorporates anticipatory, time-based adaptation of stimulation control, locked to patient-specific biological rhythms, as an adjunct to classical feedforward and feedback control methods. Initial results from three case studies using chronotherapy-enabled prototypes will illustrate the concept.The proposed control architecture for a future bioelectronic implant mimics more closely the classical integration of adaptive, feedforward, and feedback control methods found in physiology, and could be useful as a general method for personalized therapy refinement.

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The SANTÉ study at 10 years of follow‐up: Effectiveness, safety, and sudden unexpected death in epilepsy

Cited by 174 publications

References 47 publications

Cheers for SANTĖ: Long Term Safety and Efficacy of Anterior Nucleus of the Thalamus DBS

Cheers for SANTĖ: Long Term Safety and Efficacy of Anterior Nucleus of the Thalamus DBS

Electrical Brain Stimulation and Continuous Behavioral State Tracking in Ambulatory Humans

Embedding Digital Chronotherapy into Bioelectronic Medicines

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