Predicting and Communicating Geriatric Trauma Outcomes

Lydia R. Maurer, Joseph V. Sakran, Haytham M. Kaafarani

Research output: Contribution to journalReview articlepeer-review


Purpose of Review: To provide an overview of the most recent research in geriatric trauma outcomes, specifically highlighting advances in risk prediction for the elderly injured patient. Recent Findings: Geriatric-specific evidence and best practices continue to evolve for older adult trauma patients. There are a number of risk stratification systems that offer insights into prognosis for elderly patients, and newer models using machine learning methods show promise in this population as well. These non-linear models can provide useful prognostic information to guide communication with patients and families, including the incorporation of palliative care interventions and geriatric-specific pathways that have been shown to be of benefit to this patient population. Summary: Key aspects of care for geriatric trauma patients include knowing the best clinical practices for this population, along with up-to-date research on risk prediction in this group. While there has been some success with the use of risk stratification systems to guide implementation of palliative care interventions, further implementation-based research is needed on specific programs in order to make this more widespread.

Original languageEnglish (US)
JournalCurrent Trauma Reports
Issue number1
StatePublished - Mar 2021


  • Artificial intelligence
  • Geriatric trauma
  • Palliative care
  • Risk prediction
  • Trauma

ASJC Scopus subject areas

  • Surgery
  • Orthopedics and Sports Medicine
  • Rehabilitation


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