Authors
Jiajian Peng, Minhua Kuang, Qixin Yu, Zhangrong Liang
Published in
Journal of the College of Physicians and Surgeons--Pakistan : JCPSP. Volume 36. Issue 8. Pages 1076-1080.
Abstract
To evaluate the predictive performance of combining serum D-Dimer levels with Injury Severity Score (ISS) for forecasting in-hospital mortality and unfavourable outcomes among trauma patients.
An analytical study. Place and Duration of the Study: Department of Emergency, Foshan Hospital of Traditional Chinese Medicine, Foshan, China, from January 2021 to April 2025.
Trauma patients were divided into a survival group (n = 250) and a death group (n = 35) based on in-hospital survival status. Whole-body CT examinations were performed upon admission, and general clinical data, serum D-Dimer levels, and ISS scores were compared between the two groups. ROC curves were generated to evaluate predictive performance. Logistic regression identified independent prognostic factors, which were then used to build a nomogram model using R software.
A total of 285 trauma patients were included, with a mortality rate of 12.3%. Logistic regression analysis revealed that D-Dimer (p <0.001), ISS score (p = 0.02), GCS (p = 0.06), and days of hospitalisation (p <0.001) were independent risk factors for in-hospital mortality. The AUC was 0.766 for D-dimer, 0.740 for the ISS score, and 0.811 for the combined model. The combined model demonstrated significantly better predictive performance than either individual predictor (p <0.05). The nomogram was constructed based on the results of the multivariate regression analysis and demonstrated good predictive performance.
D-Dimer levels and ISS scores were higher in trauma patients who died during hospitalisation.
Trauma, D-Dimer, Injury severity score.
PMID:
42563345
Bibliographic data and abstract were imported from PubMed on 07 Aug 2026.
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