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Record W4416258220 · doi:10.1111/trf.70003

Dried plasma retains hemostatic function and thermal stability during Arctic military operations

2025· article· en· W4416258220 on OpenAlexafffundabout
Kanwal Singh, Aron A. Shoara, Henry T. Peng, Viktor Prifti, Katy Moes, Cerys McGuinness, Tristan Bonnici, Maria Y. Shiu, Sushmaa Chandralekha Selvakumar, Peter Andrisani, Pierre‐Marc Dion, Damien Miller, S. Vuong, Colin A. Kretz, Phillip J. Wallace, Shawn G. Rhind, Wendy Sullivan‐Kwantes, Andrew Beckett

Bibliographic record

VenueTransfusion · 2025
Typearticle
Languageen
FieldMedicine
TopicTrauma, Hemostasis, Coagulopathy, Resuscitation
Canadian institutionsMcGill UniversityThrombosis and Atherosclerosis Research InstituteCanadian Blood ServicesHamilton Health SciencesUniversity of TorontoNational Defence Medical CentreDefence Research and Development CanadaMcMaster UniversityUniversité de SherbrookeDepartment of National DefenceSt. Michael's Hospital
FundersNational Institutes of HealthCanadian Institutes of Health ResearchHospital for Sick ChildrenCanadian Blood ServicesDefence Research and Development Canada
KeywordsDiluentArcticPlasmaThermal stabilityStability (learning theory)Function (biology)Hemostasis

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.016
GPT teacher head0.255
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes3
Has abstractyes

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