ArticleeLife2018
Prognostication of chronic disorders of consciousness using brain functional networks and clinical characteristics.
Article in eLife, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 1 of them a synthesis 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
56 citing papers in PubMed, 1 synthesis or guideline pooled it, 90 citations in OpenAlex.
- Prediction models for functional outcomes in prolonged disorders of consciousness: a systematic review and meta-analysis.Journal of neuroengineering and rehabilitation · 2025Pooled it
- Multimodal Assessment of Consciousness with Brain-Computer Interfaces and Artificial Intelligence: From Acquired Brain Injury to Neurodegenerative Disease.Journal of clinical medicine · 2026Review
- Neuroimaging of Disorder of Consciousness: From Brain Network Mechanisms to Clinical Translation.Journal of clinical neurology (Seoul, Korea) · 2026Review
- Prognostic factors in prolonged disorders of consciousness: a narrative review.Reviews in the neurosciences · 2026Review
- Prognosis prediction of patients with disorders of consciousness based on digital twin brain models.Journal of neuroengineering and rehabilitation · 2026Article
- PET in conjunction with resting-state functional MRI for the study of chronic disorders of consciousness.Brain communications · 2026Article
- Artificial intelligence-quantified fundus tessellated density and its association with myopia severity in Chinese children: a cross-sectional study.Frontiers in cell and developmental biology · 2026Article
- A shared central thalamus mechanism underlying diverse recoveries in disorders of consciousness.Nature communications · 2025Article
- Detecting rs-fMRI Networks in Disorders of Consciousness: Improving Clinical Interpretability.Annals of clinical and translational neurology · 2025Article
- Functional neuroimaging in disorders of consciousness: towards clinical implementation.Brain : a journal of neurology · 2025Review
- Extracerebral Normalization ofNeurocritical care · 2025Article
- Thalamic burst and tonic firing selectively indicate patients' consciousness level and recovery.Innovation (Cambridge (Mass.)) · 2025Article
- Analysis of the microstates of prolonged disorders of consciousness.Frontiers in neurology · 2025Article
- Classifying disorders of consciousness using a novel dual-level and dual-modal graph learning model.Journal of translational medicine · 2024Article
- Prognostic Evaluation of Disorders of Consciousness by Using Resting-State fMRI: A Systematic Review.Journal of clinical medicine · 2024Review
- Article
- Neuroimaging in Disorders of Consciousness and Recovery.Physical medicine and rehabilitation clinics of North America · 2024Review
- Establishment and validation of a bad outcomes prediction model based on EEG and clinical parameters in prolonged disorder of consciousness.Frontiers in human neuroscience · 2024Article
- Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Neuroimaging.Neurocritical care · 2023Article
- Long-term functional outcomes improved with deep brain stimulation in patients with disorders of consciousness.Stroke and vascular neurology · 2023Article
Corrections and comments
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Authors and funding
15 authors at 4 institutions in 2 countries.
Funding
Abstract
Disorders of consciousness are a heterogeneous mixture of different diseases or injuries. Although some indicators and models have been proposed for prognostication, any single method when used alone carries a high risk of false prediction. This study aimed to develop a multidomain prognostic model that combines resting state functional MRI with three clinical characteristics to predict one year-outcomes at the single-subject level. The model discriminated between patients who would later recover consciousness and those who would not with an accuracy of around 88% on three datasets from two medical centers. It was also able to identify the prognostic importance of different predictors, including brain functions and clinical characteristics. To our knowledge, this is the first reported implementation of a multidomain prognostic model that is based on resting state functional MRI and clinical characteristics in chronic disorders of consciousness, which we suggest is accurate, robust, and interpretable.
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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.