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Evaluation of inflammatory-thrombosis panel as a diagnostic tool for vascular Behçet's disease.

Publication ,  Journal Article
Zhan, H; Cheng, L; Chen, H; Liu, Y; Feng, X; Li, H; Li, Z; Li, Y
Published in: Clin Rheumatol
March 2025

OBJECTIVES: Vascular Behçet's disease (VBD) is prevalent in 40% of BD, but lacks laboratory biomarker for timely diagnosis. We aimed to establish a diagnostic panel for discerning VBD and non-VBD patients and identify hemostatic-thrombotic markers most related to VBD pathogenesis using machine learning algorithm. OBJECTIVES: A total of 338 BD patients comprising 123 VBD and 215 non-VBD were enrolled. Twenty-six clinical and laboratory features selected from LassoCV were included in multiple classifier to choose the optimal model for VBD differentiation. The Shapley Additive exPlanations (SHAP) was employed to interpret the contribution of model features for VBD prediction. Logistic regression analysis and nomogram were conducted to screen risk factors of VBD. RESULTS: Inflammatory (neutrophils%, NK cells, IL-6), hematological (hemoglobin, hemoglobin distribution width (HDW)) and thrombosis (activated partial thromboplastin clotting time (APTT), D-dimer) parameters were elevated in VBD. Then we chose top contributors from XGBoost model and performed ten-fold cross validation, the diagnostic accuracy of which exceeded 0.90. Utilizing SHAP method, we identified higher incidence of arterial thrombosis or aneurysm and deep vein thrombosis, upregulated NK cell count, HDW, APTT and D-dimer, downregulated reticulocyte%, B cell count, red blood cell distribution width, cellular hemoglobin (CH) and TNF-α would ultimately generate the phenotype of VBD. Severity, hemoglobin, mean corpuscular hemoglobin, CH, HDW, APTT and D-dimer were found as potential risk factors for vascular outcomes among BD. RESULTS: Our study developed a well-performed model leveraging clinical and laboratory parameters for differentiating VBD. Inflammatory and thrombotic risk factors are potential contributors to VBD. Key Points • Inflammatory (neutrophils%, NK cells, IL-6), hematological (HGB, HDW) and thrombosis (APTT, D-dimer) parameters were elevated in VBD. • We firstly developed an inflammatory-thrombosis model as a diagnostic tool for VBD. • HGB, MCH, CH, HDW, APTT and D-dimer are potential risk factors for VBD.

Duke Scholars

Published In

Clin Rheumatol

DOI

EISSN

1434-9949

Publication Date

March 2025

Volume

44

Issue

3

Start / End Page

1279 / 1291

Location

Germany

Related Subject Headings

  • Thrombosis
  • Risk Factors
  • Partial Thromboplastin Time
  • Middle Aged
  • Male
  • Machine Learning
  • Inflammation
  • Humans
  • Fibrin Fibrinogen Degradation Products
  • Female
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Zhan, H., Cheng, L., Chen, H., Liu, Y., Feng, X., Li, H., … Li, Y. (2025). Evaluation of inflammatory-thrombosis panel as a diagnostic tool for vascular Behçet's disease. Clin Rheumatol, 44(3), 1279–1291. https://doi.org/10.1007/s10067-025-07301-6
Zhan, Haoting, Linlin Cheng, Haizhen Chen, Yongmei Liu, Xinxin Feng, Haolong Li, Zhan Li, and Yongzhe Li. “Evaluation of inflammatory-thrombosis panel as a diagnostic tool for vascular Behçet's disease.Clin Rheumatol 44, no. 3 (March 2025): 1279–91. https://doi.org/10.1007/s10067-025-07301-6.
Zhan H, Cheng L, Chen H, Liu Y, Feng X, Li H, et al. Evaluation of inflammatory-thrombosis panel as a diagnostic tool for vascular Behçet's disease. Clin Rheumatol. 2025 Mar;44(3):1279–91.
Zhan, Haoting, et al. “Evaluation of inflammatory-thrombosis panel as a diagnostic tool for vascular Behçet's disease.Clin Rheumatol, vol. 44, no. 3, Mar. 2025, pp. 1279–91. Pubmed, doi:10.1007/s10067-025-07301-6.
Zhan H, Cheng L, Chen H, Liu Y, Feng X, Li H, Li Z, Li Y. Evaluation of inflammatory-thrombosis panel as a diagnostic tool for vascular Behçet's disease. Clin Rheumatol. 2025 Mar;44(3):1279–1291.
Journal cover image

Published In

Clin Rheumatol

DOI

EISSN

1434-9949

Publication Date

March 2025

Volume

44

Issue

3

Start / End Page

1279 / 1291

Location

Germany

Related Subject Headings

  • Thrombosis
  • Risk Factors
  • Partial Thromboplastin Time
  • Middle Aged
  • Male
  • Machine Learning
  • Inflammation
  • Humans
  • Fibrin Fibrinogen Degradation Products
  • Female