Mild-to-severe traumatic brain injury in children: altered cytokines reflect severity
Bibliographic record
Abstract
BACKGROUND: Paediatric traumatic brain injury (TBI) is recognised to have significant longer-term neurocognitive effects. Childhood is a time of high risk for head injury. Functional recovery is variable with a combination of any or all of physical, cognitive and emotional impairment. Immune activation and alteration in cytokine levels are present following TBI which may differ from adults. METHODS: Pro- and anti-inflammatory cytokines including Interleukin (IL)-2, IL-4, IL-6, IL-8, IL-10, IL-17A, Tumor Necrosis Factor (TNF)-α and Interferon (IFN)-γ were examined at baseline and following in vitro treatment with endotoxin of whole blood, in the following children: severe TBI (sTBI: initial Glasgow coma scale(GCS) ≤ 8), mild TBI (mTBI; GCS 14/15) at 0-4d and at 10-14d post-TBI and compared to healthy age-matched controls. RESULTS: The study enrolled 208 children, including 110 with TBI cohort (n = 104 mild; 6 severe) and controls (n = 98). At baseline all children with TBI had increased IL-6. The mTBI group had significantly increased IFN-γ versus controls. In sTBI at baseline, IFN-γ was decreased compared to controls. At baseline IL-8, IL-10, IL-17A, and TNF-α were decreased in mTBI compared to controls. This persisted at 2 week post-mTBI. The AUC for detecting mTBI was 0.801 CI (0.73-086) using IL6/IL10 ratio. mTBI showed a greater fold change in IL-8 and TNF-α in response to endotoxin stimulation, a response that persisted at 2 weeks. Children with sTBI did not have a significant IL-6 response to endotoxin, but did show an increase in IL-17A. CONCLUSION: Children with all TBI including mTBI show altered cytokine profiles and altered endotoxin responses. Although cytokines increased in sTBI especially in response to endotoxin, suppressed responses were found in mTBI coupled with persistent immune dysfunction post-injury.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".