Serum Levels of Biochemical Markers of Traumatic Brain Injury
Bibliographic record
Abstract
Background . A biomarker would be valuable in the diagnosis, risk stratification and prognosis of patients with traumatic brain injury (TBI). Methods . We measured serum levels of S-100β, neuron specific enolase (NSE) and myelin basic protein (MBP) in 50 TBI subjects, and 50 age and gender matched controls. Patients were recruited within 6 hours of the initial injury, they had an initial Glasgow Coma Scale (GCS) score of 14 or less, or a GCS score of 15 with witnessed loss of consciousness (LOC) or amnesia. Results . S-100β, NSE and MBP levels were significantly higher in TBI subjects than in control subjects (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>P</mml:mi><mml:mo><</mml:mo><mml:mn>0.001</mml:mn></mml:math>for S-100β and NSE;<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>P</mml:mi><mml:mo>=</mml:mo><mml:mn>0.009</mml:mn></mml:math>for MBP). Initial S-100β levels were significantly higher in TBI subjects who had not retuned to normal activities 2 weeks following their injury than in TBI subjects who had retuned to normal activities (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>P</mml:mi><mml:mo>=</mml:mo><mml:mn>0.022</mml:mn></mml:math>). MBP levels were higher in TBI subjects with positive findings on the baseline CT scan than in CT-negative subjects (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>P</mml:mi><mml:mo>=</mml:mo><mml:mn>0.007</mml:mn></mml:math>). Conclusions . S-100β, NSE and MBP may be present in the sera of TBI subjects in elevated quantities relative to controls. S-100β may aid in predicting short-term outcome in TBI subjects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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 teacher head, 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".