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. 2025 Sep 26.
doi: 10.1007/s00277-025-06628-z. Online ahead of print.

Development and validation of deep vein thrombosis diagnostic model based on machine learning methods

Bin Yan  1   2   3 , Haijun Guo  4 , Tianxi Hu  1   2   3 , Yu Zhang  5 , Zhixin Zheng  5 , Weipeng Du  6   7   8 , Yuhan Gu  9
Affiliations

Development and validation of deep vein thrombosis diagnostic model based on machine learning methods

Bin Yan et al. Ann Hematol. .

Abstract

The D-Dimer testing has limited diagnostic value for patients with a deep venous thrombosis (DVT) probability based on clinical prediction rules. There are still patients with normal D-Dimer levels (< 500 ng/mL) diagnosed with DVT. Some new predictive marker may improve the predictive power of D-Dimer, especially in DVT patients with normal levels of D-Dimer. All subjects were from Nanyang Central Hospital. The demographic data and laboratory test data were collected. Multiple models were used to evaluate and calculate the importance rank. Multivariate logistics was used to establish a DVT diagnostic model. Compared to D-Dimer and other markers, this combined model has better performance. The von Willebrand factor Gain-of-function mutant GPIb binding assays (VWF: GPIbM) can improve the diagnostic capability of D-Dimer, which has higher diagnostic value and clinical benefits. In addition, the model still has good diagnostic capability in DVT patients with normal D-Dimer levels. The combined model has better diagnostic performance than D-Dimer, and it is valuable for some patients whose clinical prediction rules cannot be evaluated due to difficulties in obtaining medical history information. VWF: GPIbM can be used to assist in the diagnosis of DVT in the future.

Keywords: D-Dimer; Deep venous thrombosis; Von willebrand factor.

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Conflict of interest statement

Declarations. Informed consent: has been obtained from the patients and subjects. This study was approved by the Ethics Committee of Nanyang Central Hospital (KYLW-2025-0126). The rights and privacy of all patients and subjects are fully protected. Competing interests: The authors declare no competing interests.

References

    1. Duffett L (2022) Deep venous thrombosis. Ann Intern Med 175(9):ITC129–ITC144. https://doi.org/10.7326/AITC202209200 - DOI - PubMed
    1. Arshad N, Isaksen T, Hansen JB, Braekkan SK (2017) Time trends in incidence rates of venous thromboembolism in a large cohort recruited from the general population. Eur J Epidemiol 32(4):299–305. https://doi.org/10.1007/s10654-017-0238-y - DOI - PubMed
    1. Heit JA (2008) The epidemiology of venous thromboembolism in the community. Arterioscler Thromb Vasc Biol 28(3):370–372. https://doi.org/10.1161/ATVBAHA.108.162545 - DOI - PubMed - PMC
    1. Lutsey PL, Zakai NA (2023) Epidemiology and prevention of venous thromboembolism. Nat Rev Cardiol 20(4):248–262. https://doi.org/10.1038/s41569-022-00787-6 - DOI - PubMed
    1. Bagot CN, Arya R (2008) Virchow and his triad: a question of attribution. Br J Haematol 143(2):180–190. https://doi.org/10.1111/j.1365-2141.2008.07323.x - DOI - PubMed