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CC BY 4.0 · Semin Thromb Hemost
DOI: 10.1055/a-2765-9437
Review Article

Machine Learning Prediction of Stress-Induced D-dimer Reactivity in Male Physicians with and without Burnout

Authors

  • Roland von Känel

    1   Department of Consultation-Liaison Psychiatry and Psychosomatic Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland

  • Marie Gronemeyer

    1   Department of Consultation-Liaison Psychiatry and Psychosomatic Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland

  • Claudia Zuccarella-Hackl

    1   Department of Consultation-Liaison Psychiatry and Psychosomatic Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland

  • Sarah A. Holzgang

    1   Department of Consultation-Liaison Psychiatry and Psychosomatic Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland

  • Sinthujan Sivakumar

    1   Department of Consultation-Liaison Psychiatry and Psychosomatic Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland

  • Aju P. Pazhenkottil

    1   Department of Consultation-Liaison Psychiatry and Psychosomatic Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland
    2   Department of Cardiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
    3   Cardiac Imaging, Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland

  • Diego Gomez Vieito

    1   Department of Consultation-Liaison Psychiatry and Psychosomatic Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland
    4   Institute of Molecular Cancer Research, University of Zurich, Zurich, Switzerland

  • Mary Princip

    1   Department of Consultation-Liaison Psychiatry and Psychosomatic Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland

Funding Information Financial support for this study was provided through an institutional grant from the University of Zurich, Switzerland, to R.v.K.
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Abstract

Acute emotional stress can trigger acute coronary syndrome (ACS), potentially via hypercoagulable states. Circulating D-dimer is an established marker of fibrin turnover and stress-related coagulation activation, yet predictors of D-dimer stress reactivity remain unclear, especially in high-risk groups such as male physicians with burnout. We examined predictors of D-dimer changes during acute stress and recovery in 60 male physicians with and without burnout. Participants underwent the Trier Social Stress Test, with D-dimer and other biomarkers assessed across four time points over 1 hour. The area under the curve (AUC) for D-dimer was calculated to capture overall reactivity. We applied the least absolute shrinkage and selection operator (LASSO) regression to identify relevant predictors among demographic, behavioral, psychosocial, and physiological variables, followed by traditional linear regression to estimate effect sizes. LASSO regression identified five key predictors of D-dimer stress reactivity: Prestress D-dimer, habitual alcohol consumption, prestress cortisol, stress-induced epinephrine (EPI) surge, and adverse childhood experiences (ACEs). In linear regression, all but prestress cortisol remained significant independent predictors, collectively explaining 50.4% of the variance in D-dimer AUC. Specifically, higher alcohol consumption (ΔR 2 = 0.117, p < 0.001), larger EPI surge (ΔR 2 = 0.081, p = 0.003), and more ACEs (ΔR 2 = 0.044, p = 0.026) were associated with heightened D-dimer responses, while higher prestress D-dimer was associated with attenuated reactivity (ΔR 2 = 0.208, p < 0.001). Our findings highlight the role of early adversity, alcohol consumption, and sympathoadrenal activation in stress-induced coagulation activation, as reflected by D-dimer reactivity. If validated, these predictors may help identify individuals at elevated risk for stress-triggered ACS and inform targeted prevention strategies.

Keywords

hypercoagulability - D-dimer - psychology - cardiology - atherothrombosis - thrombosis

Contributors' Statement

R.v.K. contributed to conceptualization, formal analysis, funding acquisition, methodology, resources, supervision, and both original drafting and review and editing of the manuscript. M.G. contributed to conceptualization, formal analysis, methodology, validation, and review and editing. C.Z.H. contributed to conceptualization, data curation, investigation, methodology, supervision, and review and editing. S.A.H. contributed to conceptualization, data curation, investigation, methodology, and review and editing. S.S. contributed to data curation, investigation, methodology, and review and editing. A.P.P. contributed to conceptualization, investigation, methodology, project administration, supervision, validation, and review and editing. D.G.V. contributed to data curation, investigation, methodology, validation, and review and editing. M.P. contributed to conceptualization, data curation, investigation, methodology, project administration, supervision, and review and editing.


Supplementary Material



Publication History

Received: 05 June 2025

Accepted: 27 October 2025

Accepted Manuscript online:
08 December 2025

Article published online:
19 December 2025

© 2025. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution 4.0 International License, permitting copying and reproduction so long as the original work is given appropriate credit (https://creativecommons.org/licenses/by/4.0/)

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