The use of trauma transfusion pathways for blood component transfusion in the civilian population: a systematic review and meta‐analysis<sup>*</sup>
Bibliographic record
Abstract
This study was undertaken to determine if, amongst civilian trauma patients requiring massive transfusion (MT), the use of a formal trauma transfusion pathway (TTP), in comparison with transfusion without a TTP, is associated with a reduction in mortality, or changes in indices of coagulation, blood product utilisation and complications. A systematic review of three bibliographic databases, reference lists and conference proceedings was conducted. Studies were included if comparisons were made between patients receiving transfusion with and without a TTP. Data were extracted by two independent reviewers on population characteristics, transfusion strategies, blood product utilisation, indices of coagulation, clinical outcomes and complications. Data were pooled using a random effects model and heterogeneity explored. Seven observational studies met all eligibility criteria. Amongst 1801 patients requiring MT, TTPs were associated with a significant reduction in mortality (RR 0·69, 95% CI 0·55, 0·87). No significant increase in the mean number of PRBC transfused between TTP and control patients was seen (MD -1·17 95% CI -2·70, 0·36). When studies assessing only trauma patients were considered, TTPs were associated with a reduction in the mean number of units of plasma transfused (MD -2·63, 95% CI -4·24, -1·01). In summary, the use of TTPs appears to be associated with a reduction in mortality amongst trauma patients requiring MT without a clinically significant increase in the number of PRBC transfused and a potential reduction in plasma transfusion. Effects of TTPs on platelet transfusion, indices of coagulation and complications remain unclear. A randomised controlled trial is warranted.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.028 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".