A Data-Driven Method to Discriminate Limb Salvage from Other Combat-Related Extremity Trauma

Stephen M. Goldman, Susan L. Eskridge, Sarah R. Franco, Jason M. Souza, Scott M. Tintle, Thomas C. Dowd, Joseph Alderete, Benjamin K. Potter, Christopher L. Dearth

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Introduction: The aim of this study was to address and enhance our ability to study the clinical outcome of limb salvage (LS), a commonly referenced but ill-defined clinical care pathway, by developing a data-driven approach for the identification of LS cases using existing medical code data to identify characteristic diagnoses and procedures, and to use that information to describe a cohort of US Service members (SMs) for further study. Methods: Diagnosis code families and inpatient procedure codes were compiled and analyzed to identify medical codes that are disparately associated with a LS surrogate population of SMs who underwent secondary amputation within a broader cohort of 3390 SMs with lower extremity trauma (AIS > 1). Subsequently, the identified codes were used to define a cohort of all SMs who underwent lower extremity LS which was compared with the opinion of a panel of military trauma surgeons. Results: The data-driven approach identified a population of n = 2018 SMs who underwent LS, representing 59.5% of the combat-related lower extremity (LE) trauma population. Validation analysis revealed 70% agreement between the data-driven approach and gold standard SME panel for the test cases studied. The Kappa statistic (κ = 0.55) indicates a moderate agreement between the data-driven approach and the expert opinion of the SME panel. The sensitivity and specificity were identified as 55.6% (expert range of 51.8–66.7%) and 87% (expert range of 73.9–91.3%), respectively. Conclusions: This approach for identifying LS cases can be utilized to enable future high-throughput retrospective analyses for studying both short- and long-term outcomes of this underserved patient population.

Original languageEnglish (US)
Article number6357
JournalJournal of Clinical Medicine
Issue number19
StatePublished - Oct 2023
Externally publishedYes


  • Abbreviated Injury Scale
  • amputation
  • military medicine
  • musculoskeletal injuries
  • wound and injuries

ASJC Scopus subject areas

  • General Medicine


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