Prehospital Hypertonic Saline Resuscitation Attenuates the Activation and Promotes Apoptosis of Neutrophils in Patients With Severe Traumatic Brain Injury
Bibliographic record
Abstract
BACKGROUND: Activation of polymorphonuclear neutrophils (PMNs) is thought to contribute to traumatic brain injury (TBI). Since hypertonic fluids can inhibit PMN activation, we studied whether hypertonic fluid resuscitation can reduce excessive PMN activation in TBI patients. METHODS: Trauma patients with severe TBI were resuscitated with 250 mL of either 7.5% hypertonic saline (HS; n = 22), HS + 6% dextran-70 (HSD; n = 22), or 0.9% normal saline (NS; n = 39), and blood samples were collected on hospital admission and 12 and 24 h after resuscitation. Polymorphonuclear neutrophil activation (CD11b, CD62L, CD64) and degranulation (CD63, CD66b, CD35) markers and oxidative-burst activity, as well as spontaneous PMN apoptosis were measured by flow cytometry. RESULTS: Relative to healthy controls, TBI patients showed increased PMN activation and decreased apoptosis of PMNs. In the HS group, but not in the HSD group, markers of PMN adhesion (CD11b, CD64) and degranulation (CD35, CD66b) were significantly lower than those in the NS group. These effects were particularly pronounced 12 h after resuscitation. Treatment with HS and HSD inhibited PMN oxidative burst responses compared with NS-treated patients. Hypertonic saline alone partially restored delayed PMN apoptosis. Despite these differences, the groups did not differ in clinical outcome parameters such as mortality and Extended Glasgow Outcome Scale. CONCLUSIONS: This study demonstrates that prehospital resuscitation with HS can partially restore normal PMN activity and the apoptotic behavior of PMNs, whereas resuscitation with HSD was largely ineffective. Although the results are intriguing, additional research will be required to translate these effects of HS into treatment strategies that improve clinical outcome in TBI patients.
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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) | 0.001 | 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) | 0.001 | 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".