Blood Biomarkers in Moderate-To-Severe Traumatic Brain Injury: Potential Utility of a Multi-Marker Approach in Characterizing Outcome
Bibliographic record
Abstract
BACKGROUND: Blood biomarkers are valuable tools for elucidating complex cellular and molecular mechanisms underlying traumatic brain injury (TBI). Profiling distinct classes of biomarkers could aid in the identification and characterization of initial injury and secondary pathological processes. This study characterized the prognostic performance of a recently developed multi-marker panel of circulating biomarkers that reflect specific pathogenic mechanisms including neuroinflammation, oxidative damage, and neuroregeneration, in moderate-to-severe TBI patients. MATERIALS AND METHODS: Peripheral blood was drawn from 85 isolated TBI patients (n = 60 severe, n = 25 moderate) at hospital admission, 6-, 12-, and 24-h post-injury. Mortality and neurological outcome were assessed using the extended Glasgow Outcome Scale. A multiplex platform was designed on MULTI-SPOT(®) plates to simultaneously analyze human plasma levels of s100 calcium binding protein beta (s100B), glial fibrillary acidic protein (GFAP), neuron specific enolase (NSE), brain-derived neurotrophic factor (BDNF), monocyte chemoattractant protein (MCP)-1, intercellular adhesion molecule (ICAM)-5, and peroxiredoxin (PRDX)-6. Multivariable logistic regression and area under the receiver-operating characteristic curve (AUC) were used to evaluate both individual and combined predictive abilities of these markers for 6-month neurological outcome and mortality after TBI. RESULTS: Unfavorable neurological outcome was associated with elevations in s100B, GFAP, and MCP-1. Mortality was related to differences in six of the seven markers analyzed. Combined admission concentrations of s100B, GFAP, and MCP-1 were able to discriminate favorable versus unfavorable outcome (AUC = 0.83), and survival versus death (AUC = 0.87), although not significantly better than s100B alone (AUC = 0.82 and 0.86, respectively). CONCLUSION: The multi-marker panel of TBI-related biomarkers performed well in discriminating unfavorable and favorable outcomes in the acute period after moderate-to-severe TBI. However, the combination of these biomarkers did not outperform s100B alone.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".