ArticleEpilepsy & behavior : E&B2022
Small cohort of patients with epilepsy showed increased activity on Facebook before sudden unexpected death.
Article in Epilepsy & behavior : E&B, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
5 citing papers in PubMed, 6 citations in OpenAlex.
- Chronic Stress Alters Dorsal Bed Nucleus of Stria Terminalis Synaptic Neurotransmission in a Dravet Syndrome Mouse Model.bioRxiv : the preprint server for biology · 2026Article
- The bed nucleus of the stria terminalis as a neuromodulatory target for refractory epilepsy.Frontiers in network physiology · 2026Review
- myAURA: a personalized health library for epilepsy management via knowledge graph sparsification and visualization.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Focused digital cohort selection from social media using the metric backbone of biomedical knowledge graphs.Journal of biomedical informatics · 2025Article
- Patient-centeredness-a cultural targeted survey among junior medical managers.International journal for equity in health · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 4 institutions in 3 countries.
Funding
Abstract
Sudden Unexpected Death in Epilepsy (SUDEP) remains a leading cause of death in people with epilepsy. Despite the constant risk for patients and bereavement to family members, to date the physiological mechanisms of SUDEP remain unknown. Here we explore the potential to identify putative predictive signals of SUDEP from online digital behavioral data using text and sentiment analysis tools. Specifically, we analyze Facebook timelines of six patients with epilepsy deceased due to SUDEP, donated by surviving family members. We find preliminary evidence for behavioral changes detectable by text and sentiment analysis tools. Namely, in the months preceding their SUDEP event patient social media timelines show: i) increase in verbosity; ii) increased use of functional words; and iii) sentiment shifts as measured by different sentiment analysis tools. Combined, these results suggest that social media engagement, as well as its sentiment, may serve as possible early-warning signals for SUDEP in people with epilepsy. While the small sample of patient timelines analyzed in this study prevents generalization, our preliminary investigation demonstrates the potential of social media data as complementary data in larger studies of SUDEP and epilepsy.
Indexed as
Identifiers
What OpenQuestion holds
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.