Association of Brain Injury Biomarkers and Circulatory Shock Following Moderate-Severe Traumatic Brain Injury: A TRACK-TBI Study
Bibliographic record
Abstract
INTRODUCTION: Early circulatory shock following traumatic brain injury (TBI) is a multifactorial process; however, the impact of brain injury biomarkers on the risk of shock has not been evaluated. We examined the association between neuronal injury biomarker levels and the development of circulatory shock following moderate-severe TBI. METHODS: In this retrospective cohort study, we examined adults with moderate-severe TBI (Glasgow Coma Scale score <13) enrolled in the TRACK-TBI study, an 18-center prospective TBI cohort study. The exposures were day-1 levels of neuronal injury biomarkers (glial fibrillary acidic protein, ubiquitin C-terminal hydrolase-L1 [UCH-L1], S100 calcium-binding protein B [S100B], neuron-specific enolase), and of an inflammatory biomarker (high-sensitivity C-reactive protein). The primary outcome was the development of circulatory shock, defined as cardiovascular Sequential Organ Failure Assessment Score ≥2 within 72 hours of admission. Association between day-1 biomarker levels and the development of circulatory shock was assessed with regression analysis. RESULTS: The study included 392 subjects, with a mean age of 40 years; 314 (80%) were male and 165 (42%) developed circulatory shock. Median (interquartile range) day-1 levels of UCH-L1 (994.8 [518.7 to 1988.2] pg/mL vs. 548.1 [280.2 to 1151.9] pg/mL; P <0.0001) and S100B (0.47 μg/mL [0.25 to 0.88] vs. 0.27 [0.16 to 0.46] μg/mL; P <0.0001) were elevated in those who developed early circulatory shock compared with those who did not. In multivariable regression, there were associations between levels of both UCH-L1 (odds ratio, 1.63 [95% confidence interval, 1.25-2.12]; P <0.0005) and S100B (odds ratio, 1.73 [95% confidence interval 1.27-2.36]; P <0.0005) with the development of circulatory shock. CONCLUSION: Neuronal injury biomarkers may provide the improved mechanistic understanding and possibly early identification of patients at risk for early circulatory shock following moderate-severe TBI.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".