Resuscitation with Hypertonic Saline–Dextran Reduces Serum Biomarker Levels and Correlates with Outcome in Severe Traumatic Brain Injury Patients
Bibliographic record
Abstract
In the treatment of severe traumatic brain injury (TBI), the choice of fluid and osmotherapy is important. There are practical and theoretical advantages to the use of hypertonic saline. S100B, neuron-specific enolase (NSE), and myelin-basic protein (MBP) are commonly assessed biomarkers of brain injury with potential utility as diagnostic and prognostic indicators of outcome after TBI, but they have not previously been studied in the context of fluid resuscitation. This randomized controlled trial compared serum concentrations of S100B, NSE, and MBP in adult severe TBI patients resuscitated with 250 mL of 7.5% hypertonic saline plus 6% dextran70 (HSD; n = 31) versus 0.9% normal saline (NS; n = 33), and examined their relationship with neurological outcome at discharge. Blood samples drawn on admission (≤3 h post-injury), and at 12, 24, and 48 h post-resuscitation were assayed by ELISA for the selected biomarkers. Serial comparisons of biomarker concentrations were made by ANOVA, and relationships between biomarkers and outcome were assessed by multiple regression. On admission, mean (±SEM) S100B and NSE concentrations were increased 60-fold (0.73 ± 0.08 μg/L) and sevenfold (37.0 ± 4.8 μg/L), respectively, in patients resuscitated with NS, compared to controls (0.01 ± 0.01 and 6.2 ± 0.6, respectively). Compared with NS resuscitation, S100B and NSE were twofold and threefold lower in HSD-treated patients and normalized within 12 h. MBP levels were not significantly different from controls in either treatment arm until 48 h post-resuscitation, when a delayed increase (0.58 ± 0.29 μg/L) was observed in NS-treated patients. Biomarkers were elevated in the patient group showing an unfavorable outcome. HSD-resuscitated patients with favorable outcomes exhibited the lowest serum S100B and NSE concentrations, while maximal levels were found in NS-treated patients with unfavorable outcomes. The lowest biomarker levels were seen in survivors resuscitated with HSD, while maximal levels were in NS-resuscitated patients with fatal outcome. Pre-hospital resuscitation with HSD is associated with a reduction in serum S100B, NSE, and MBP concentrations, which are correlated with better outcome after 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) | 0.001 | 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) | 0.000 | 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".