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Computer Modelling Using Prehospital Vitals Predicts Transfusion and Mortality.

Zachary D W Dezman, Eric Hu, Peter F Hu

    Prehospital Emergency Care
    |March 18, 2016
    PubMed
    Summary

    A new model using prehospital vital signs accurately predicts trauma patient outcomes, including transfusion needs and intensive care unit stays. This computer-assisted approach enhances early triage and resource allocation for critically injured individuals.

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    Area of Science:

    • Trauma surgery
    • Emergency medicine
    • Medical informatics

    Background:

    • Prehospital vital signs are crucial for assessing trauma patient severity.
    • Current methods for predicting outcomes like transfusion needs or intensive care unit (ICU) stay are limited.
    • Computer-assisted modeling offers potential to improve prediction accuracy.

    Purpose of the Study:

    • To evaluate a computer-assisted modeling technique using prehospital vital signs.
    • To predict emergency transfusion requirements, ICU length of stay, and mortality in injured patients.
    • To compare the model's predictive performance against individual vital signs alone.

    Main Methods:

    • Retrospective analysis of 17,988 trauma patients (2006-2012).
    • Development and internal validation of a regression model (PH-VS) using standard prehospital vital signs (heart rate, blood pressure, shock index, respiratory rate).
    Keywords:
    mortalityprehospital caretransfusionvital signs

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  • Evaluation using area under the receiver operating curve (AUROC); data on transfusion, ICU stay, and mortality were collected from registries.

    • Main Results:

    • The PH-VS model significantly outperformed individual vital signs across all outcomes (average AUROC = 0.82).
    • The model accurately predicted transfusion needs within 2 and 6 hours of admission for 65.9% and 62.3% of patients, respectively.
    • Study outcomes included 4% mortality, 12.6% requiring ≥3 ICU days, and 6.5% requiring transfusions.

    Conclusions:

    • Computer-assisted modeling significantly enhances the predictive ability of prehospital vital signs for trauma outcomes.
    • This model can support prehospital triage decisions.
    • Improved triage facilitates matching critically injured patients with appropriate resources, minimizing delays.