Feasibility and transport of packed red blood cells into Special Forces operational conditions
Bibliographic record
Abstract
BACKGROUND: Transfusing packed red blood cells (PRBCs) into Special Forces may provide a survival advantage from hemorrhage-induced battlefield injuries; however, the effect of the unique operational stressors on RBC integrity is not known. METHODS: Pooled PRBCs (20 U) (7 days old), stored in Golden Hour containers, were exposed to the following simulated operational stressors: High-Altitude Low-Opening parachute descent from 30,000 ft, followed by a simulated soldier presence patrol in a climatic chamber set to 48 °C and 9% humidity for 12 hours (test). Biochemical (pH, lactate, potassium, and adenosine triphosphate) and biomechanical (percent hemolysis, deformability, and morphology) were measured to determine the integrity of PRBCs. RESULTS: The simulated parachute descent significantly raised pH (p = 0.025) and potassium (p = 0.014) levels compared with the control; however, this was not clinically significant. Lactate (mmol/L) and adenosine triphosphate levels (0 μmol/g Hgb) were unaffected (p > 0.05). Potassium and pH levels increased with time but not significantly compared with controls. Lactate levels were unaffected with time.Mechanical agitation of PRBCs from the simulated soldier presence patrol did not significantly affect the biochemical (p ≥ 0.08) or biomechanical (p ≥ 0.33) parameters compared with control.Hemolysis was found to be less than 0.8% at the end of 12 hours. No significant difference in RBC morphology and RBC deformability were noted. CONCLUSION: Carrying PRBCs into the austere Special Forces environment is feasible as biochemical and biomechanical markers of RBC stress remain within published transfusion safety parameters when PRBCs were stored in new cold technology containers for 12 hours at 48°C during a simulated Special Forces operation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".