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Updated: Sep 25, 2025

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Predicting Mortality in Elderly Spine Trauma Patients.

Catherine R Carlile1, Andrew B Rees1, Jacob D Schultz1

  • 1Department of Orthopaedic Surgery, Vanderbilt University Medical Center, Nashville, TN.

Spine
|April 26, 2022
PubMed
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This study developed a clinical prediction model to identify elderly patients at high risk of 90-day mortality after traumatic spine injuries. The model, incorporating factors like age and hypotension, can personalize mortality risk assessment for better patient care.

Area of Science:

  • Geriatric Traumatology
  • Clinical Prediction Modeling
  • Spinal Injury Outcomes

Background:

  • Increasing incidence of traumatic spine injuries in the elderly population.
  • Challenges in assessing elderly trauma patients due to comorbidities and frailty.
  • Lack of predictive tools for survival in elderly patients with spinal trauma.

Purpose of the Study:

  • To construct a clinical prediction model for 90-day mortality in elderly patients with traumatic spine injuries.
  • To identify key predictors of mortality in this vulnerable patient group.

Main Methods:

  • Retrospective analysis of prospectively collected data from elderly patients (65+) with spine trauma (2010-2019).
  • Inclusion of 13 preselected variables in a multivariable logistic regression model.

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  • Model performance evaluated using concordance index and calibration plots; internally validated via bootstrap.

    • Main Results:

    • 1746 patients met inclusion criteria; 20.6% experienced 90-day mortality.
    • Key predictors of 90-day mortality identified: age, hypotension, closed head injury, max Abbreviated Injury Scale, and hematocrit.
    • An optimism-corrected C-index of 0.77 was achieved, leading to the creation of a personalized mortality risk calculator.

    Conclusions:

    • The developed predictive calculator is the first of its kind for elderly patients with traumatic spine injuries.
    • The model aids in personalizing mortality risk assessment, addressing a gap in current clinical practice.
    • Future prospective research is planned for external validation to confirm the model's predictive utility.