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A Data-Driven Method to Discriminate Limb Salvage from Other Combat-Related Extremity Trauma
Stephen M Goldman1,2, Susan L Eskridge3,4, Sarah R Franco1,2
1DoD-VA Extremity Trauma and Amputation Center of Excellence, Bethesda, MD 20889, USA.
Journal of Clinical Medicine
|October 14, 2023
Summary
A new data-driven method accurately identifies limb salvage (LS) cases in US Service members with lower extremity trauma, enabling future outcome studies for this patient group.
Area of Science:
- Orthopedic Surgery
- Trauma Surgery
- Health Informatics
Background:
- Limb salvage (LS) is a crucial but poorly defined clinical pathway for lower extremity trauma.
- Existing medical codes lack specificity for identifying LS cases.
- Studying LS outcomes requires a reliable method for cohort identification.
Purpose of the Study:
- To develop and validate a data-driven approach for identifying limb salvage cases using medical codes.
- To establish a cohort of US Service members (SMs) with lower extremity trauma who underwent LS.
- To facilitate future retrospective studies on LS clinical outcomes.
Main Methods:
- Analyzed diagnosis and inpatient procedure codes to find those associated with LS.
- Defined a surrogate LS population based on secondary amputation after lower extremity trauma.
- Compared the data-driven cohort identification with expert military trauma surgeon opinions.
Main Results:
- Identified 2018 SMs (59.5%) undergoing LS from the combat-related lower extremity trauma population.
- Achieved 70% agreement between the data-driven method and expert panel validation.
- Demonstrated moderate agreement (κ = 0.55) with good specificity (87%) and moderate sensitivity (55.6%).
Conclusions:
- The data-driven approach effectively identifies limb salvage cases.
- This method enables high-throughput retrospective analysis of LS patient outcomes.
- Facilitates research on short- and long-term outcomes for underserved LS patients.
