Management of post-traumatic severe hemorrhage remains a challenge to any trauma care system. Studying integrated and innovative tools designed to predict the risk of early severe hemorrhage (ESH) and resource needs could offer a promising option to improve clinical decisions and then shorten the time of intervention in the context of pre-hospital severe trauma. As evidence seems to be lacking to address this issue, this ambispective validation study proposes to assess on an independent cohort the predictive performance of a newly developed machine learning-based model, as well as the feasibility of its clinical deployment under real-time healthcare conditions.
Age range
18 Years
Sex
ALL
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.
Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.
A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
Fβ-score, with β = 4
Timeframe: 18 months