Articles

Survival effect of prehospital emergency anaesthesia with intubation in risk-stratified patients with major trauma: a causal modelling study

Amy PK Nelson, Nick Dodds, Mohamad Zeina, et al

Lancet Respir Med Available online 11 February 2026

https://doi.org/10.1016/S2213-2600(25)00370-4

Summary

Background

Trauma is among the top 10 most common causes of disability worldwide, accounting for more than 100 million disability-adjusted life-years (DALYs) per year. Although the value of prompt management in severe injury is undisputed, the benefit of prehospital emergency anaesthesia with intubation remains uncertain. We aimed to estimate the causal effect of prehospital intubation on survival using doubly robust joint modelling of outcome and allocation, a task facilitated by machine learning.

Methods

For this causal modelling study we analysed the prehospital clinical characteristics of 6467 patients admitted to a UK major trauma centre for the periods Feb 23, 2012, to March 31, 2017 (n=3882), and April 1, 2017, to Nov 13, 2019 (n=2585). We built machine-learning models to predict survival and stratify patients by propensity for early anaesthesia and intubation. To estimate the causal survival effect of prehospital intubation, we used doubly robust estimation with inverse probability weighting by predicted intubation.

Findings

Early intubation and 30-day mortality were highly predictable from early prehospital data alone (AUCs 0·943 and 0·867, respectively). Patients who were predicted to require prehospital intubation but did not receive it showed substantially lower survival than those who were not (66·8% [95% CI 61·3–71·7] vs 93·6% [92·5–94·6], log-rank p<0·0001). The conditional average treatment effect of prehospital intubation was –0·103 (95% CI –0·119 to –0·087), corresponding to a 10·3% reduction in 30-day mortality. Scaled UK-wide, this policy is estimated to prevent 170 (95% CI 148 to 191) deaths per year, an effect comparable to the benefit of major trauma centres in England, with an annual cost-effectiveness value of £101 million (95% CI 93 to 111).

Interpretation

Guiding prehospital intubation by a machine-learning stratification model of prehospital data is predicted to improve 30-day survival of major trauma patients. This is, to our knowledge, the highest level of evidence to date on prehospital intubation efficacy in major trauma and could inform policy discussions on funding specialist prehospital critical care teams to consider improving access to this intervention.

Funding

Wellcome Trust and the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre.