A descriptive analysis of the Canadian prehospital and transport transfusion (CAN-PATT) network
Bibliographic record
Abstract
Objective: Out-of-hospital blood transfusion (OHBT) is becoming increasingly common across the prehospital environment, yet there is significant variability in OHBT practices. The Canadian Prehospital and Transport Transfusion (CAN-PATT) network was established to collaborate, standardize, and evaluate the effectiveness of out-of-hospital blood transfusion (OHBT) across Canada. The objectives of this study are to describe the setting and organizational characteristics of CAN-PATT member organizations and to provide a cross-sectional examination of the current OHBT practices of CAN-PATT organizations. Methods: This was a cross-sectional examination of all six critical care transport organizations that are involved in CAN-PATT network. Surveys were sent to identified leads from each organization. The survey focused on three main areas of interest: 1) critical care transport organizational service and coverage, 2) provider, and crew configurations, and 3) OHBT transfusion practices. Results: All six surveys were completed and returned. There are a total of 30 critical care transport bases (19 rotor-wing, 20 fixed-wing and 6 land) across Canada and 11 bases have a blood-on-board program. Crew configurations very between organizations as either dual paramedic or paramedic/nurse teams. Median transport times range from 30 to 46 minutes for rotor-wing assets and 64 to 90 minutes for fixed-wing assets. Half of the CAN-PATT organizations started their out-of-hospital blood transfusion programs within the last three years. Most organizations carry at least two units of O-negative, K-negative red blood cells and some organizations also carry group A thawed plasma, fibrinogen concentrate and/or prothrombin complex concentrate. All organizations advocate for early administration of tranexamic acid for injured patients suspected of bleeding. All organizations return un-transfused blood components to their local transfusion medicine laboratory within a predefined timeframe to reduce wastage. Conclusions: Variations in OHBT practices were identified and we have suggested considerations for standardization of transfusion practices and patient care as it relates to OHBT. This standardization will also enable a robust means of data collection to study and optimize outcomes of patients receiving OHBT. A fulsome description of the participating organizations within CAN-PATT should enhance interpretation of future OHBT studies that will be conducted by this network.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".