The prehospital use of younger age whole blood is associated with an improved arrival coagulation profile
Bibliographic record
Abstract
INTRODUCTION: Recent in vitro data have shown that the hemostatic profile of whole blood (WB) degrades significantly after 14 days, yet the optimal storage remains debated. We hypothesized that arrival coagulation studies would be improved in patients receiving younger WB in the prehospital setting. METHODS: This study was approved by our institutional institutional review board. We evaluated all trauma patients who received prehospital blood products by our helicopter service between July 2017 and July 2019. "Young" WB was defined as 14 days or less. Patients who received at least 1 U of young WB were classified as YOUNG, while the remainder was classified as OLD. Continuous data are presented as medians (25th-75th interquartile range) with comparisons performed using Wilcoxon rank sum. Assessments of clinical hemostatic potential included arrival platelet cell count and rapid thrombelastography. Multivariate regression analysis was also performed (Stata 12.1; College Station, TX). RESULTS: A total of 220 patients received prehospital WB during the study period. Of these, 153 patients received YOUNG WB, while 67 were transfused only OLD WB units. There were no differences in demographics, prehospital or arrival physiology, or Injury Severity Score among the two groups. The measures of clot initiation (activated clotting time) and kinetics (k time) were improved, as were the measures of clot acceleration/fibrinogen function (angle) and platelet function (maximum amplitude). As well, arrival platelet count was higher in the YOUNG cohort. No significant differences in postarrival transfusion were noted (p = 0.220). Multivariate analysis showed the greatest differences in maximum amplitude and α angle but failed to reach significance. CONCLUSION: Previous in vitro data have suggested deterioration of platelet function in cold-stored WB after 14 days. The current study demonstrated decreased global hemostasis by clinically available laboratory tests, especially related to fibrinogen and platelet interactions on univariate, but not multivariate analysis. This did not translate into increased transfusion requirements. Further studies are needed to determine the optimal storage duration for cold-stored WB for transfusion in the bleeding trauma patient, as well as rule out the presence of confounding variables. LEVEL OF EVIDENCE: Therapeutic, level IV.
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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 | 0.002 |
| 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) | 0.002 | 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".