ArticleNeuroImage. Clinical2020
Somatosensory evoked fields predict response to vagus nerve stimulation.
Article in NeuroImage. Clinical, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 37 citations in OpenAlex.
- Prognostic factors in vagus nerve stimulation for drug-resistant epilepsy. Results from a systematic review and meta-analysis of the literature.Neurosurgical review · 2026Pooled it
- Factors predicting the response to vagus nerve stimulation (VNS) in pediatric patients with drug- resistant epilepsy: a systematic review and meta-analysis.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2025Pooled it
- Magnetoencephalography in human neuroscience research: planning, piloting, implementation and quality assurance.Nature protocols · 2026Review
- A deep representation learning model to predict response to vagus nerve stimulation.Nature communications · 2026Article
- Article
- Predicting response to neuromodulation therapies in drug-resistant epilepsy using machine learning models: a meta-analysis and systematic review.Bioelectronic medicine · 2025Review
- Article
- Invasive Neurostimulation for the Treatment of Epilepsy.Seminars in neurology · 2025Review
- Bioelectronic Therapeutics: A Revolutionary Medical Practice in Health Care.Bioelectricity · 2025Review
- Vagus nerve stimulation for epilepsy: A narrative review of factors predictive of response.Epilepsia · 2024Review
- Optimized microburst VNS elicits fMRI responses beyond thalamic-specific response from standard VNS.Annals of clinical and translational neurology · 2024Article
- Review
- Research progress on the electrophysiological indicators to predict the efficacy of vagus nerve stimulation for drug-refractory epilepsy.Acta epileptologica · 2024Review
- Brain functional connectivity-based prediction of vagus nerve stimulation efficacy in pediatric pharmacoresistant epilepsy.CNS neuroscience & therapeutics · 2023Article
- Article
- Brainstem Associated Somatosensory Evoked Potentials and Response to Vagus Nerve Stimulation: An Investigation of the Vagus Afferent Network.Frontiers in neurology · 2021Article
- Evolution of the Vagus Nerve Stimulation (VNS) Therapy System Technology for Drug-Resistant Epilepsy.Frontiers in medical technology · 2021Review
- Preoperative Heart Rate Variability During Sleep Predicts Vagus Nerve Stimulation Outcome Better in Patients With Drug-Resistant Epilepsy.Frontiers in neurology · 2021Article
- Neuromodulation for Refractory Epilepsy.Epilepsy currentsArticle
Corrections and comments
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Authors and funding
15 authors at 3 institutions in 2 countries.
Funding
Abstract
There is an unmet need to develop robust predictive algorithms to preoperatively identify pediatric epilepsy patients who will respond to vagus nerve stimulation (VNS). Given the similarity in the neural circuitry between vagus and median nerve afferent projections to the primary somatosensory cortex, the current study hypothesized that median nerve somatosensory evoked field(s) (SEFs) could be used to predict seizure response to VNS. Retrospective data from forty-eight pediatric patients who underwent VNS at two different institutions were used in this study. Thirty-six patients ("Discovery Cohort") underwent preoperative electrical median nerve stimulation during magnetoencephalography (MEG) recordings and 12 patients ("Validation Cohort") underwent preoperative pneumatic stimulation during MEG. SEFs and their spatial deviation, waveform amplitude and latency, and event-related connectivity were calculated for all patients. A support vector machine (SVM) classifier was trained on the Discovery Cohort to differentiate responders from non-responders based on these input features and tested on the Validation Cohort by comparing the model-predicted response to VNS to the known response. We found that responders to VNS had significantly more widespread SEF localization and greater functional connectivity within limbic and sensorimotor networks in response to median nerve stimulation. No difference in SEF amplitude or latencies was observed between the two cohorts. The SVM classifier demonstrated 88.9% accuracy (0.93 area under the receiver operator characteristics curve) on cross-validation, which decreased to 67% in the Validation cohort. By leveraging overlapping neural circuitry, we found that median nerve SEF characteristics and functional connectivity could identify responders to VNS.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.