Prehospital emergency anesthesia with intubation saves lives of trauma patients

Trauma patients urgently requiring a breathing tube are more likely to survive if the tube is inserted before arriving at hospital compared to insertion afterwards, suggests a modeling study led by researchers at University College London (UCL) and the Severn Major Trauma Network.

The researchers found that prehospital emergency intubation of high-risk trauma patients could improve 30-day survival by 10.3%, and could save 170 lives each year in the UK.

The findings of the new artificial intelligence (AI)-supported analysis, published in The Lancet Respiratory Medicine, provides the strongest evidence yet that prehospital emergency anesthesia with intubation saves lives when delivered to those who need it most.

Trauma is the leading cause of death in children and adults aged below 40 in England and Wales. But there is a lack of high-quality evidence on the best time to start certain types of care for major trauma patients, such as the insertion of breathing tubes.

Prehospital intubation needs to be administered by an advanced critical care team, specially trained and equipped to administer the anesthesia required to facilitate the insertion of breathing tubes. In the UK, that is currently provided only by the air ambulance services.

The researchers say their findings could inform policy discussions on funding specialist prehospital critical care teams, which could include public funding for air ambulances or funding additional training for ground ambulance teams, so that more high-risk major trauma patients can have breathing tubes inserted before arrival at hospital.

Joint first author Dr. Amy Nelson (UCL Queen Square Institute of Neurology and King's College London) said: "The airway is a top priority in major trauma, but the question of whether we should intubate before hospital arrival is unsettled because we cannot ethically conduct a randomised trial.

"Emergency care decisions made before hospital admission depend on the combination of many measurements taken under pressure. We used these measurements to answer the question in steps: we first built a machine learning model to identify high-risk patients, then we modelled the impact of early intubation in this group, which showed us that prehospital intubation saves lives."

For the study, researchers analysed data from 6,467 trauma patients treated at Southmead Hospital Major Trauma Centre, Bristol.

The researchers used AI-assisted modeling to predict both who would need intubation and who would likely survive – to isolate the impact that intubation had from other factors such as the injury severity. To facilitate their analysis, they developed a new machine learning model, called 'Intub-8', which predicted outcomes based on eight routinely collected prehospital measurements.

The researchers found that among high-risk patients who were identified by the model as needing intubation (229 patients), those who received it before arriving at hospital were 10.3% more likely to survive (within a 30-day period) compared with those who did not.

By scaling up their findings relative to national trauma incidence, the researchers estimate that if every trauma patient who needed prehospital intubation was given it, 170 lives could be saved each year in the UK – roughly one life saved every other day. 

Additionally, they conducted a cost-effectiveness analysis, finding that cost savings would be in the range of £101 million annually for the UK, due to reduced costs of further care and lives saved.

Professor Parashkev Nachev (UCL Queen Square Institute of Neurology), joint senior author, said: "In medicine, action and inaction are not morally asymmetric. When we cannot have randomised controlled trial evidence for an intervention, we must use the best available alternative: causal inference from real-world data, assisted by artificial intelligence, the only technology with the power to address the complexity of biological systems."

Until now, advanced air ambulance services across the world who respond to critically injured patients have struggled to conduct studies that assess the benefit and cost effectiveness of their life-saving interventions. The use of AI in this study has allowed us to analyse existing data in a totally new way. This reveals the huge impact that advanced care provides when delivered before arrival in hospital.

These findings may have a huge impact on how UK and international health services look after the most severely injured patients in our societies."

Associate Professor Julian Thompson, joint senior author and Clinical Director of the Severn Major Trauma Network

The authors note that the findings are specific to a mixed rural-urban UK setting where highly trained physician-paramedic teams perform all prehospital intubation. The survival benefit may differ in other healthcare systems or national contexts, and further research is needed to examine long-term outcomes and potential complications.

The study was funded by Wellcome and the National Institute for Health and Care Research UCLH Biomedical Research Centre.

Professor David Lockey, Immediate Past Chair, Faculty of Pre-hospital Care, Royal College of Surgeons of Edinburgh, who was not part of the research team, commented: "Using machine learning to model the effects of anaesthesia delivered at the scene of accidents, the authors of this study have provided high quality evidence that consistent provision of this intervention by pre-hospital teams not only saves many lives but does it in a cost effective manner. The study addresses an important issue which has been very difficult to address with conventional study techniques, and provides vital evidence to define what should be available to critically ill patients before they arrive in hospital."