ReviewInternational journal of molecular sciences2025
Blood-Based Biomarkers for Traumatic Brain Injury: A New Era in Diagnosis and Prognosis.
Review in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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
6 citing papers in PubMed.
- Post-Translational Modifications in Traumatic Brain Injury: Decoding the Proteomic Landscape and Molecular Mechanisms of Secondary Injury.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Review
- Pediatric Mild Traumatic Brain Injury and Concussion: Modern Pathophysiological Insights, Diagnostic Advances, and Active Management Protocols.Brain sciences · 2026Review
- Future Directions and Evolution Strategies for the Clinical Management of Traumatic Brain Injury.Journal of clinical medicine · 2026Article
- Blood-Based Biomarkers and Cognitive-Behavioral Assessment in Mild Traumatic Brain Injury: Current Evidence and Clinical Perspectives.Korean journal of neurotrauma · 2026Review
- Multi-dimensional plasma proteomic profiling elucidates molecular mechanisms and pathophysiological networks in pediatric severe traumatic brain injury.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026Article
- Early Risk Stratification of Severe Trauma in the Emergency Department: Integrating Clinical Scoring Systems, Dynamic Biomarkers, and Artificial Intelligence-A Narrative Review.Therapeutics and clinical risk management · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Traumatic brain injury (TBI) is a major global health concern and a leading cause of mortality and disability. Head computed tomography (CT) remains indispensable for the detection of intracranial hemorrhage; however, its indiscriminate use in mild trauma increases radiation exposure, cumulative oncogenic risk, and healthcare costs. Consequently, there is growing interest in tools capable of improving sensitivity in mild or early-stage TBI. Protein-based biomarkers are promising complements to conventional assessment. Molecules such as glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase L1 (UCH-L1), S100 calcium-binding protein B (S100B), and neurofilament light chain (NfL) reflect astroglial activation, neuronal injury, and axonal damage, enabling objective evaluation of neurotrauma. Beyond protein biomarkers, metabolomic and lipidomic approaches capture alterations associated with early metabolic distress, oxidative stress, mitochondrial dysfunction, and membrane disruption following TBI. High-resolution mass spectrometry studies have identified reproducible metabolite and lipid signatures correlating with injury severity and functional outcomes. Longitudinal profiling further reveals dynamic metabolic trajectories that distinguish secondary injury progression from stabilization, supporting predictive modeling and risk stratification. Together, these advances pave the way toward precision medicine in neurotrauma. Nevertheless, variability in assay performance and sampling timing continues to limit widespread clinical adoption. Future research should prioritize methodological standardization, analytical validation, and the integration of multi-omic data with machine learning-based predictive models.
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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.