Ross Davenport

Introduction: Delivering balanced blood resuscitation at the point of injury remains a significant logistical challenge in prehospital trauma care. To inform optimal transfusion strategies in austere environments, we conducted a simulation-based study comparing the operational demands of three prehospital transfusion approaches. Methods: Three doctor–paramedic teams (six clinicians) undertook a crossover simulation of traumatic haemorrhage, completing all three arms in random order: two units red-cells-in-plasma (RCP), two units red blood cells plus two units thawed fresh frozen plasma (RBC+FFP), and two units red cells plus two units lyophilised plasma (RBC+LyoP). Outcomes were flow time (defined as time from decision-to-transfuse to completion of transfusion of all units), touch time (hands-on time) and process burden (steps, equipment, checks, personnel), timed in real-time and verified on video. A postscenario questionnaire captured user perceptions. Results: All scenarios were completed without missing data. RCP consistently required the least time and operational effort. Median flow times (min:s) were 06:31 (RCP), 12:20 (RBC+FFP) and 16:29 (RBC+LyoP) (p=0.019). Median touch times (min:s) were 02:31 (RCP), 05:21 (RBC+FFP) and 13:03 (RBC+LyoP) (p=0.017). Touch/flow ratios were lowest for RCP (0.39), indicating reduced cognitive and physical load. Standardised process mapping identified 26 steps for RCP versus 46 for RBC+FFP and 52 for RBC+LyoP, reflecting a single set-up and one repetition for RCP compared with multiple repetitions and added reconstitution steps for LyoP. Equipment (4, 10, 12), checks (8, 16, 16) and personnel required (2, 2, 3) followed the same efficiency gradient. Five of six participants rated RCP as optimal for the patient, and all six for the crew; LyoP was unanimously judged as the most demanding. Conclusions: In a simulated trauma scenario, a combined RCP component was delivered more quickly and with substantially less process burden than separate components. These operational gains support combined-component strategies for prehospital haemorrhage resuscitation in both military and civilian settings.

Background: Early intervention in patients with major traumatic injuries is critical. Decision support can improve clinicians’ ability to identify high-risk patients. The aim of this study was to compare the performance of a machine-learning (ML) decision support system to that of expert clinicians and to assess the ML system’s impact on augmenting human risk prediction after injury in the prehospital phase of care. Methods: This early clinical evaluation study compared a ML risk prediction system to expert clinicians in assessing a patient’s risk of trauma-induced coagulopathy (TIC). The study was conducted between 1 January 2019 and 31 June 2019 at two air ambulance sites in the south of England. The ML system used a Bayesian Network algorithm to predict TIC. Comparisons in predictive performance were made first between expert clinicians and the ML system and second, between expert clinicians and expert clinicians exposed to the ML system’s outputs. Results: Overall, 51 expert clinicians were enrolled in the study and 184 patient assessments from 135 patients were analysed. The median age of included patients was 31 years old (IQR 23, 47), 75% were male and median Injury Severity Score 17 (IQR 9, 34). 62 patients (46%) received blood within 4 hours of injury and 26 patients (19%) developed TIC. The ML system did not outperform expert clinicians in discriminating between patients with and without TIC (area under the curve (AUC) ML: 0.87 (95% CI 0.79, 0.95) vs AUC clinician: 0.83 (95% CI 0.74, 0.92), p=0.330)). Calibration and overall accuracy of the ML system were superior. Expert clinicians’ risk prediction, when augmented by the ML system, showed potential for improvement compared with unassisted human performance. Conclusions: Early after injury, an ML system performs well compared with expert prehospital clinicians in the prediction of TIC and blood transfusion. The study suggests that ML systems may augment clinical risk prediction in trauma.

Purpose of review: The management of noncompressible haemorrhage (NCH) remains a critical challenge in trauma care, with early mortality rates persistently high despite advances in trauma systems. Resuscitative Endovascular Balloon Occlusion of the Aorta (REBOA) has emerged as a potential intervention to address severe haemorrhage in prehospital and hospital settings. This review examines the role of REBOA in remote damage control resuscitation, focusing on the ‘golden hour’ and the ‘platinum 5 minutes’ concepts that underscore the urgency of timely interventions. Recent findings: Evidence from the UK-REBOA trial and related studies highlights the complexity of implementing REBOA in prehospital settings, emphasising the importance of early deployment, appropriate patient selection, and minimisation of delays. Technological innovations, including AI-assisted decision-making and automated partial REBOA systems, offer promising avenues for optimising REBOA’s application. Furthermore, the concept of damage control prehospital care prioritises essential interventions tailored to individual patient needs, advocating for a streamlined approach to reduce on-scene time. Summary: The integration of REBOA with advanced prehospital strategies holds the potential for reducing preventable deaths from traumatic haemorrhage, but further research is needed to refine protocols and enhance outcomes in this high-stakes domain.

Background: Early resuscitation is based on platelet‐poor components such as red blood cells and plasma (RBC + P), contributing to platelet dilution and worsening of trauma‐induced coagulopathy (TIC). We aimed to compare the ability of cold‐stored whole blood (WB) versus RBC + P as a single component to correct TIC.Study Design and Methods: Blood samples were collected on admission from trauma patients who required activation of the major hemorrhage protocol at a single UK major trauma center in 2021/2022. Samples were spiked ex vivo with volumes equivalent to two, four, or eight units of WB or RBC + P stored for a maximum of 2 weeks. Thromboelastometry, platelet counting, and multiple electrode aggregometry (MEA) were performed.Results: Samples from 20 adult trauma patients were analyzed. Median age was 32 years (27–42), 89% were male, 70% had platelet dysfunction (tissue factor–activated ROTEM [EXTEM]–tissue factor–activated ROTEM with cytochalasin D [FIBTEM] clot amplitude at 5 min [A5] ≤ 30 mm), 65% were coagulopathic (EXTEM A5 ≤ 40 mm), and 42% died. EXTEM–FIBTEM A5 was higher following spiking with WB than RBC + P (33 mm, 26–33, vs. 27 mm, 24–30, p < .001). WB‐spiking corrected platelet dysfunction in 2 patient samples out of 20, whereas RBC + P increased the frequency of platelet dysfunction (1/20 sample) and TIC (4/20 samples). RBC + P was associated with a dose‐dependent deterioration in rotational thromboelastometry (ROTEM) clot strength and dynamics, platelet count, and aggregation in response to multiple agonists compared with WB‐spiking, which maintained or partially corrected these abnormalities.Conclusion: Compared with RBC + P, WB better preserves ex vivo platelet‐related ROTEM parameters, platelet count, and aggregation, but does not fully correct these common derangements of TIC.

Background: The relationship between early cardiovascular dysfunction (CVD) in isolated traumatic brain injury (iTBI) and outcome has not been fully described. We aimed to (1) determine the prevalence and phenotype of CVD after iTBI in the hyper-acute phase and (2) compare treatment and outcomes in those with CVD vs non-CVD. Methods: An observational cohort database study of severe iTBI patients (Head AIS 3+) at a level 1 trauma centre (2008–2019) and physician-led air ambulance service (2019–2020). CV dysfunction was defined as tachycardia or bradycardia, with hypotension. Physiology, laboratory results, 24-hour transfusion, and computer-topography (CT) findings were recorded. Outcomes were 28-day mortality and Glasgow Outcome Score (GOS). Results: A total of 168 patients met inclusion criteria, average age 46 years (IQR 30–61), 77% male, median ISS 25 (IQR 17–29) with 51% Head AIS 5. Time from injury to pre-hospital assessment was 31 minutes (IQR 20–42) with 20% demonstrating CVD on initial observations. The CVD group were more shocked (lactate 6.1 (1.7–10.9) vs. 2.4 (1.4–3.3), P < 0.001) and coagulopathic (43% vs. 15%, P = 0.001). There was no difference in Head AIS or CT findings between groups, except frequency of hypoxic ischemic encephalopathy (HIE) (CVD: 21% vs. non-CVD: 1%, P < 0.001). 24-hour transfusion was higher in CVD patients: 3 (0–8) vs. 0 (0–0) units, P< 0.001. Mortality was greater in CVD vs non-CVD iTBI (61% vs. 31%, P = 0.002), but in patients with AIS 5 there was no difference (P = 0.262). One-third of CVD survivors (13/33) were discharged home, and 4/18 patients with recorded GOS had good neurological outcome. Conclusion: One in five patients with severe iTBI develop early CVD, associated with increased mortality, coagulopathy, and HIE. However, mortality and neurological outcome is highly variable in those with CVD across the iTBI severity spectrum. Further research is needed to define the pathophysiology and optimal treatment to improve outcomes for this subgroup of iTBI.