Advanced interventions in the pre-hospital resuscitation of patients with non-compressible haemorrhage after penetrating injuries
Bibliographic record
Abstract
Early haemorrhage control and minimizing the time to definitive care have long been the cornerstones of therapy for patients exsanguinating from non-compressible haemorrhage (NCH) after penetrating injuries, as only basic treatment could be provided on scene. However, more recently, advanced on-scene treatments such as the transfusion of blood products, resuscitative thoracotomy (RT) and resuscitative endovascular balloon occlusion of the aorta (REBOA) have become available in a small number of pre-hospital critical care teams. Although these advanced techniques are included in the current traumatic cardiac arrest algorithm of the European Resuscitation Council (ERC), published in 2021, clear guidance on the practical application of these techniques in the pre-hospital setting is scarce. This paper provides a scoping review on how these advanced techniques can be incorporated into practice for the resuscitation of patients exsanguinating from NCH after penetrating injuries, based on available literature and the collective experience of several helicopter emergency medical services (HEMS) across Europe who have introduced these advanced resuscitation interventions into routine practice.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".