EMTRAS: EMergency TRAuma Score - Evidencio
EMTRAS: EMergency TRAuma Score
The EMTRAS model estimates the seriousness of the condition of patients with trauma. The model is easy to use, using simple parameters that are available within 30 minutes. 
Research authors: Marcus R. Raum, Maarten W.N. Nijsten, Mathijs Vogelzang, Frank Schuring, Rolf Lefering, Bertil Bouillon, Dieter Rixen, Edmund A.M. Neugebauer, Henk J. ten Duis.
Version: 1.23
  • Public
  • Emergency medicine
  • {{ modelType }}
  • Details
  • Validate algorithm
  • Save input
  • Load input
Display
Units

{{section.title}}

Calculate the result

Set more parameters to perform the calculation

The EMTRAS score is: points

{{ resultSubheader }}
{{ chart.title }}
Result interval {{ additionalResult.min }} to {{ additionalResult.max }}

Conditional information

How this model should be used:
The EMTRAS accurately predicts mortality. The determination of the EMTRAS will inform caregivers of the seriousness of patients with trauma at an early stage. Despite the fact that it only uses four items that can be determined early, it compared favorably with other (more complex) scores.

Model performance:
The EMTRAS demonstrated very good discrimination upon validation, with AUROCs of 0.94 (0.93-0.96) and 0.92 (0.90-0.94) for external validation cohorts consisting of 3,001 and 1,417 patients, respectively. In the orginal publication by Raum et al,  an AUROC of 0.83 (0.79-0.87) was found in the validation cohort consisting of 3314 patients.

Sources:

  1. Raum MR, Nijsten MW, Vogelzang M, et al. Emergency trauma score: an instrument for early estimation of trauma severity. Crit Care Med. 2009;37(6):1972-7.
  2. Joosse P, de Jong WJ, Reitsma JB, et al. External validation of the Emergency Trauma Score for early prediction of mortality in trauma patients. Crit Care Med. 2014;42(1):83-9.

{{ file.classification }}
PRO
Note
Notes are only visible in the result download and will not be saved by Evidencio

This algorithm is provided for educational, training and information purposes. It must not be used to support medical decision making, or to provide medical or diagnostic services. Read our full disclaimer.

Underlying algorithms Part of
Comments
Comment
Please enter a comment
Comments are visible to anyone

Algorithm feedback

No feedback yet 1 Comment {{ model.comments.length }} Comments
On {{ comment.created_at }} {{ comment.user.username }} a no longer registered author wrote:
{{ comment.content }}
logo

Please sign in to enable Evidencio print features

In order to use the Evidencio print features, you need to be logged in.
If you don't have an Evidencio Community Account you can create your free personal account at:

https://www.evidencio.com/registration

Printed results - Examples {{ new Date().toLocaleString() }}

Evidencio Community Account Benefits

With an Evidencio Community account you can:

  • Create and publish your own prediction algorithms.
  • Share your prediction algorithms with your colleagues, research group, organization or the world.
  • Review and provide feedback on algorithms that have been shared with you.
  • Validate your algorithms and validate algorithms from other users.
  • Find algorithms based on Title, Keyword, Author, Institute, or MeSH classification.
  • Use and save prediction algorithms and their data.
  • Use patient specific protocols and guidelines based on sequential algorithms and decision trees.
  • Stay up-to-date with new algorithms in your field as they are published.
  • Create your own lists of favorite algorithms and topics.

A personal Evidencio account is free, with no strings attached!
Join us and help create clarity, transparency, and efficiency in the creation, validation, and use of medical prediction algorithms.

Disclaimer: Calculations alone should never dictate patient care, and are no substitute for professional judgement.
Terms & Conditions | Privacy Policy | Disclaimer | Contact | Refuse cookies |
Evidencio v3.35 © 2015 - 2025 Evidencio. All Rights Reserved