Trial reportPloS one2017
Uncovering precision phenotype-biomarker associations in traumatic brain injury using topological data analysis.
Trial report in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01565551 (Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot), which is not on this map. Cited by 60 papers, 7 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.
Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot
Who cites it
60 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Genetic and peripheral biomarkers of comorbid posttraumatic stress disorder and traumatic brain injury: a systematic review.Frontiers in neurology · 2025Pooled it
- Exploring alternative approaches to precision medicine through genomics and artificial intelligence - a systematic review.Frontiers in medicine · 2023Pooled it
- Apolipoprotein E4 Polymorphism and Outcomes from Traumatic Brain Injury: A Living Systematic Review and Meta-Analysis.Journal of neurotrauma · 2021Pooled it
- Genetic Influences on Patient-Oriented Outcomes in Traumatic Brain Injury: A Living Systematic Review of Non-Apolipoprotein E Single-Nucleotide Polymorphisms.Journal of neurotrauma · 2021Pooled it
- A global collaboration to study intimate partner violence-related head trauma: The ENIGMA consortium IPV working group.Brain imaging and behavior · 2021Pooled it
- Toward a global and reproducible science for brain imaging in neurotrauma: the ENIGMA adult moderate/severe traumatic brain injury working group.Brain imaging and behavior · 2021Pooled it
- Genetic Variants and Persistent Impairment Following Mild Traumatic Brain Injury: A Systematic Review.The Journal of head trauma rehabilitationPooled it
- Topology-enhanced machine learning for speech signal processing.Nature communications · 2026Article
- Neurofilament Light Protein: A Marker for Injury Severity, Clinical Course, and Outcome Following Moderate to Severe Traumatic Brain Injury.Neurocritical care · 2026Article
- Persistent homology of blood gene co-expression networks reveals reduced cycle structure in autism spectrum disorder: a multi-cohort analysis.Mammalian genome : official journal of the International Mammalian Genome Society · 2026Article
- Phenotype discovery of traumatic brain injury segmentations from heterogeneous multi-site data.Proceedings of SPIE--the International Society for Optical Engineering · 2026Article
- Traumatic Brain Injury: Advances in Diagnostic Techniques and Treatment Modalities.Journal of clinical medicine · 2025Review
- Distinct clinical phenotypes and their neuroanatomic correlates in chronic traumatic brain injury.medRxiv : the preprint server for health sciences · 2025Article
- Distinct clinical phenotypes and their neuroanatomic correlates in chronic traumatic brain injury.Brain communications · 2025Article
- Article
- Multimodal Data Hybrid Fusion and Natural Language Processing for Clinical Prediction Models.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024Article
- The role of artificial intelligence for the application of integrating electronic health records and patient-generated data in clinical decision support.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024Article
- Simplicial complex entropy for time series analysis.Scientific reports · 2023Article
- Data-driven distillation and precision prognosis in traumatic brain injury with interpretable machine learning.Scientific reports · 2023Article
- Increasing Rigor of Preclinical Research to Maximize Opportunities for Translation.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
Abstract
backgroundTraumatic brain injury (TBI) is a complex disorder that is traditionally stratified based on clinical signs and symptoms. Recent imaging and molecular biomarker innovations provide unprecedented opportunities for improved TBI precision medicine, incorporating patho-anatomical and molecular mechanisms. Complete integration of these diverse data for TBI diagnosis and patient stratification remains an unmet challenge. METHODS AND
findingsThe Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) Pilot multicenter study enrolled 586 acute TBI patients and collected diverse common data elements (TBI-CDEs) across the study population, including imaging, genetics, and clinical outcomes. We then applied topology-based data-driven discovery to identify natural subgroups of patients, based on the TBI-CDEs collected. Our hypothesis was two-fold: 1) A machine learning tool known as topological data analysis (TDA) would reveal data-driven patterns in patient outcomes to identify candidate biomarkers of recovery, and 2) TDA-identified biomarkers would significantly predict patient outcome recovery after TBI using more traditional methods of univariate statistical tests. TDA algorithms organized and mapped the data of TBI patients in multidimensional space, identifying a subset of mild TBI patients with a specific multivariate phenotype associated with unfavorable outcome at 3 and 6 months after injury. Further analyses revealed that this patient subset had high rates of post-traumatic stress disorder (PTSD), and enrichment in several distinct genetic polymorphisms associated with cellular responses to stress and DNA damage (PARP1), and in striatal dopamine processing (ANKK1, COMT, DRD2).
conclusionsTDA identified a unique diagnostic subgroup of patients with unfavorable outcome after mild TBI that were significantly predicted by the presence of specific genetic polymorphisms. Machine learning methods such as TDA may provide a robust method for patient stratification and treatment planning targeting identified biomarkers in future clinical trials in TBI patients.
trial registrationClinicalTrials.gov Identifier NCT01565551.
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.