Dried plasma retains hemostatic function and thermal stability during Arctic military operations
Bibliographic record
Abstract
BACKGROUND: Dried plasma offers a practical alternative for remote damage control resuscitation, providing hemostatic support and volume replacement. The Arctic presents challenges that necessitate the need for blood-based resuscitation to extend the "golden hour." To address this, we evaluated the hemostatic and thermal stability of dried plasma following exposure during military Arctic operations. STUDY DESIGN AND METHODS: OctaplasLG powder kits were deployed with Canadian Armed Forces medical providers during three Arctic operations. Dried plasma was subjected to substantial temperature fluctuations (-35.2 to 26.5°C) and multiple freeze-thaw cycles. Upon return, dried plasma was reconstituted and evaluated using hemostatic/coagulation panels and differential scanning calorimetry (DSC). RESULTS: Arctic-exposed dried plasma retained visual integrity and protein concentration consistent with controls. Hemostatic function, including prothrombin time, activated partial thromboplastin time, fibrinogen, D-dimer, factor V, factor VIII, plasminogen, antithrombin III, protein C, ADAMTS13, and viscoelastic profiles remained within normal ranges, with protein S activity below the lower limit. However, von Willebrand factor antigen levels were elevated in both dried plasma groups, though distribution remained normal and unlikely to be clinically significant for resuscitation. DSC thermograms revealed five characteristic thermal transitions consistent with controls, indicating preserved structural integrity. Enthalpy analysis demonstrated a strong correlation with fibrinogen concentration, suggesting its role in plasma stability. CONCLUSION: Dried plasma retains its hemostatic and thermal stability following Arctic deployment, supporting remote damage control resuscitation in the absence of whole blood. Nonetheless, field implementation is challenged by the propensity of the diluent to freeze and the logistical requirement for warmed infusion.
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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 | 0.000 |
| 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".