Authors
Timothy Scott, Alessandro Orlando, Harun Mazumder, Samir M Fakhry
Published in
The Journal of surgical research. Volume 328. Pages 12-22. Oct 09, 2026. Epub Oct 09, 2026.
Abstract
The Injury Severity Score (ISS) measures trauma severity using Abbreviated Injury Scale (AIS) scores, but ISS calculation is resource-intensive, typically requiring manual abstraction. Because International Classification of Diseases (ICD) codes are ubiquitous, ICD-to-AIS methods could automate AIS/ISS estimation. This study compares the accuracy of ICD-based tools (Association for the Advancement of Automotive Medicine, [AAAM] ICD-to-AIS crosswalk and International Classification of Diseases Programs for Injury Categorization in R [ICDPIC-R]) in estimating AIS and ISS.
This retrospective cohort study included adult (18-89 y) trauma patients from 2018 to 2023 Trauma Quality Program (TQP) Participant Use Files (PUFs). AIS body region severity scores were classified as originally defined (AISbr8) or used for ISS calculation (AISbr6). Injury severity was derived from three sources: TQP PUF dataset, AAAM ICD-to-AIS map, and ICDPIC-R package. PUF gold standard agreement was assessed using Cohen's weighted kappa and intraclass correlation.
In 5,793,422 patients, the AAAM crosswalk showed variable AISbr8-PUF agreement (Cohen's weighted kappa: 0.73-0.95), peaking in lower extremities and lowest agreement in the spine. ICDPIC-R lacks AISbr8 scores, which limits direct comparison. For AISbr6-PUF, AAAM demonstrated poor to excellent agreement for low-severity scores (1-3), but poor to fair agreement for high-severity scores (4-6). ICDPIC-R showed poor to fair agreement across most body regions (Cohen's weighted kappa: 0.04-0.58). Both tools misestimated cohort sizes by as much as -41% underestimation and +22% overestimation.
ICD-based tools showed variable accuracy for estimating AIS, particularly for high-severity injuries and cohort identification. These important limitations should be considered when using derived AIS/ISS for risk adjustment and cohort selection.
PMID:
42854558
Bibliographic data and abstract were imported from PubMed on 10 Oct 2026.
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