Admission immune-inflammatory biomarker profiles for trauma severity stratification: an externally validated machine learning study
4 affiliations
- 1Department of Clinical Laboratory Medicine, First Affiliated Hospital, Army Medical University
- 2Department of Clinical Laboratory Medicine, Chongqing Banan Traditional Chinese Medicine Hospital
- 3Health Management Center, First Affiliated Hospital, Army Medical University
- 4Department of Respiratory and Critical Care Medicine, First Affiliated Hospital, Army Medical University
Abstract
Background: Traumatic injury induces rapid systemic immune-inflammatory alterations, but whether routinely measurable admission biomarkers can provide an early biological estimate of anatomical injury burden remains uncertain. This study aimed to characterize trauma-associated immune-inflammatory profiles across trauma severity levels defined by injury severity score (ISS) and evaluate their combined value for early severity stratification.
Methods: This two-center retrospective study included healthy participants as a physiological reference group, non-trauma acute-care patients as a clinically relevant comparator, and trauma patients classified as mild (ISS <16), moderate (ISS 16–25), or severe (ISS >25). Nineteen admission laboratory biomarkers and demographic variables were evaluated in a development cohort of 775 participants and an independent external validation cohort of 349 participants. Multinomial least absolute shrinkage and selection operator regression was used to identify severity-associated biomarkers. Ten classifiers were compared on the same predefined trauma-only development split, and the selected model was evaluated in an independent external trauma cohort.
Results: A 10-feature panel was retained following feature selection and collectively defined an immune-inflammatory profile associated with increasing trauma severity. Increasing injury burden was associated with heterogeneous and partly nonlinear inflammatory and hematologic alterations, including changes in neutrophil-related indices, lymphocyte-related measures, and albumin. The multinomial logistic regression model achieved the best overall performance, with an accuracy of 0.941 and 0.973 in the internal holdout and external validation cohorts, respectively, with an external macro-AUC of 0.993. Model interpretation consistently identified neutrophil count and RDW-CV as major contributors to severity stratification.
Conclusion: Admission-stage blood biomarkers capture reproducible immune-inflammatory alterations associated with increasing anatomical injury severity. Their combined analysis may provide a complementary approach for early biological assessment of injury burden and supports further investigation of clinically accessible biomarkers of trauma-associated immune-inflammatory dysregulation.
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BibTeX
@article{dai2026admission,
title = {{Admission immune-inflammatory biomarker profiles for trauma severity stratification: an externally validated machine learning study}},
author = {Xianling Dai and Ligai Zhang and Zhiyu Wu and Hanqing Xu and Bin Chen and Yang Zhou and Ye Xiao and Yu Wu and Shiqing Xiang and Jian He and Jing Bao and Yuting Huang},
journal = {Frontiers in Immunology},
year = {2026},
month = oct,
doi = {10.3389/fimmu.2026.1950721},
url = {https://www.frontiersin.org/articles/10.3389/fimmu.2026.1950721/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Admission immune-inflammatory biomarker profiles for trauma severity stratification: an externally validated machine learning study
AU - Xianling Dai
AU - Ligai Zhang
AU - Zhiyu Wu
AU - Hanqing Xu
AU - Bin Chen
AU - Yang Zhou
AU - Ye Xiao
AU - Yu Wu
AU - Shiqing Xiang
AU - Jian He
AU - Jing Bao
AU - Yuting Huang
PY - 2026
DA - 2026/10/14
JO - Frontiers in Immunology
DO - 10.3389/fimmu.2026.1950721
UR - https://www.frontiersin.org/articles/10.3389/fimmu.2026.1950721/full
AB - Background: Traumatic injury induces rapid systemic immune-inflammatory alterations, but whether routinely measurable admission biomarkers can provide an early biological estimate of anatomical injury burden remains uncertain. This study aimed to characterize trauma-associated immune-inflammatory profiles across trauma severity levels defined by injury severity score (ISS) and evaluate their combined value for early severity stratification. Methods: This two-center retrospective study included healthy participants as a physiological reference group, non-trauma acute-care patients as a clinically relevant comparator, and trauma patients classified as mild (ISS <16), moderate (ISS 16–25), or severe (ISS >25). Nineteen admission laboratory biomarkers and demographic variables were evaluated in a development cohort of 775 participants and an independent external validation cohort of 349 participants. Multinomial least absolute shrinkage and selection operator regression was used to identify severity-associated biomarkers. Ten classifiers were compared on the same predefined trauma-only development split, and the selected model was evaluated in an independent external trauma cohort. Results: A 10-feature panel was retained following feature selection and collectively defined an immune-inflammatory profile associated with increasing trauma severity. Increasing injury burden was associated with heterogeneous and partly nonlinear inflammatory and hematologic alterations, including changes in neutrophil-related indices, lymphocyte-related measures, and albumin. The multinomial logistic regression model achieved the best overall performance, with an accuracy of 0.941 and 0.973 in the internal holdout and external validation cohorts, respectively, with an external macro-AUC of 0.993. Model interpretation consistently identified neutrophil count and RDW-CV as major contributors to severity stratification. Conclusion: Admission-stage blood biomarkers capture reproducible immune-inflammatory alterations associated with increasing anatomical injury severity. Their combined analysis may provide a complementary approach for early biological assessment of injury burden and supports further investigation of clinically accessible biomarkers of trauma-associated immune-inflammatory dysregulation.
SN - 1664-3224
ER -