A Trauma Transfusion Pathway Decreases Coagulopathy without Increasing Blood Product Utilization
Bibliographic record
Abstract
Abstract Background: Trauma patients often require massive transfusion and their resuscitation is commonly complicated by coagulopathy. Debate persists regarding optimal massive transfusion strategies, which have traditionally adopted 2 approaches: coagulation laboratory based therapy (LBT) versus fixed ratio trauma transfusion pathways (TTP). The proponents of a LBT strategy cite “rational use” and avoidance of over-transfusion. This system may not adequately address the dynamic trauma situation where a delay in coagulation results may be detrimental. A TTP more rapidly meets the needs of trauma patients but may increase blood product utilization. Objective: Retrospectively compare our preliminary early experience with a TTP compared to our previous LBT strategy. Method: Retrospective cohort study using our transfusion database comparing 14 patients who activated the TTP with 28 patients treated before the pathways introduction. Inclusion criteria included severe traumatic injury (Injury Severity Score (ISS) >12), massive transfusion (defined as >8 units of red blood cells (RBCs) in the first 24 hours). The TTP is activated by the trauma team and results in the immediate release of 4 units of uncrossmatched RBCs. Blood product is then issued in trauma packs (TPs). Each trauma pack contains 4 units of RBCs and 4 units of frozen plasma (FP) and every second pack contains one pool of platelets (PLTs). A dose of recombinant factor VIIa (rFVIIa) is made available after TP #3. Cryoprecipitate (CRYO) is issued only at the request of the trauma team. A CBC, INR, PTT, and fibrinogen is measured at TTP activation and after every other TP. Outcomes: Outcome variables included total blood product utilization (RBC, FP, CRYO, PLTs), time to first and second set of FP (time 0 is release of 1st RBC unit), number of RBC units issued until first and second set of FP, coagulopathy at presentation and highest INR during first 24 hours of resuscitation. Results: The results are summarized in the attached table. There was no difference in ISS between groups. The introduction of the TTP resulted in no difference in the amount of blood product utilization when compared to the pre-pathway control group. Significant differences included a much shorter time to first and second FP delivery and fewer RBC units before the first and second FP delivery. The majority of the patients were coagulopathic on presentation (defined as INR > 1.4) and the TTP group achieved a significantly lower peak INR during the first 24 hours of resuscitation compared to the pre-pathway group. Conclusion: This pilot study shows that the introduction of a trauma transfusion pathway significantly improves coagulopathy and reduces time to FP administration without increasing blood product utilization. Pre-Pathway (n=28) Trauma Transfusion Pathway (n=14) P-value Mean ISS 42.0 ± 12.5 34 ± 15.1 NS Mean RBC units used 23.4 ± 14.5 23.1 ± 10.7 NS Mean FP units used 13.4 ± 9.6 16.1 ± 8.3 NS Mean PLT pools used 1.8 ± 1.5 2.7 ± 1.8 NS Mean CRYO pools used 0.46 ± 0.64 0.71 ± 0.83 NS Mean time to 1stFP (min) 89.9 ± 55.5 55.4 ± 49.2 0.02 Mean time to 2ndFP (min) 237.0 ± 206.8 103.0 ± 59.4 0.0004 Mean #RBC units to 1st set FP 10.4 ± 9.0 7.8 ± 1.6 0.02 Mean #RBC units to 2nd set FP 17.6 ± 8.8 12.9 ± 3.4 0.016 # Patients coagulopathic on initial testing (INR>1.4) 12 (43%) 8 (62%) NS Mean initial INR 1.5 ± 0.55 1.7 ± 0.58 NS Mean of highest INR in first 24h 2.3 ± 1.70 1.4 ± 0.25 0.006 # Patients given rFVIIa 6 (21%) 5 (36%) NS
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.005 | 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".