A survey of US and Canadian hospitals' paediatric massive transfusion protocol policies
Bibliographic record
Abstract
BACKGROUND: Trauma is the leading cause of death in children >1 year of age, with haemorrhage as the most common cause of medically preventable deaths. While massive transfusion protocols (MTPs) have been investigated and used in adults to reduce death from haemorrhage, there are a paucity of published data on MTP practices and outcomes in children. This study aimed to survey current MTP policies and the frequency of activation at paediatric care centres. STUDY DESIGN AND METHODS: We conducted a survey of MTPs at hospitals in the United States and Canada, including children's general hospitals, children's specialty hospitals and children's units in general hospitals. We collected information on how the MTP is activated, what therapeutics are given, frequency of its use, and how it is audited for compliance. RESULTS: Forty-six survey responses were analysed. Physician discretion was the most common activation criteria (89%). A majority of sites (78%) targeted a 'high' (≥1 : 2) ratio of plasma to red blood cells (RBC). Fifteen percent of sites use antifibrinolytics in their MTPs. Eighty nine percent of sites have type-O RBC units and 48% of sites had thawed plasma units stored in an immediately available location. CONCLUSION: There is a wide variation in MTPs among paediatric hospitals with regard to both activation criteria and products administered. This underscores the need for future prospective studies to determine the most effective resuscitation methods for paediatric populations to improve outcomes and therapeutic safety for massive bleeding.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".