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    Oral Communication

    Venous Thromboembolism

    Diagnosis of Venous Thromboembolism

    OC 11.1 - Development and validation of a clinical prediction model for the diagnostic management of acute pulmonary embolism: an individual participant data meta-analysis

    Sunday, June 25, 2023
    10:45 – 11:00 ET
    Room: 516
    Session Available As: Live-Stream and On-Demand

      Presenting Author(s)

    • Nick van Es, MD PhD (he/him/his)

      MD
      Department of Vascular Medicine, Amsterdam University Medical Center, Amsterdam, The Netherlands
      Amsterdam, Noord-Holland, Netherlands

      • Co-Author(s)

    • TT

      Toshihiko Takada

      Associate Professor
      Department of General Medicine, Shirakawa Satellite for Teaching And Research (STAR), Fukushima Medical University
      Fukushima, Aichi, Japan

    • NK

      Noémie Kraaijpoel

      MD
      Department of Vascular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
      Amsterdam, Noord-Holland, Netherlands

    • Erik Klok, MD, PhD, FESC

      Leiden University Medical Center

    • Milou AM Stals, MD

      Resident internal medicine
      Department of Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands and Dutch Thrombosis Network Netherlands.
      Leiden, Zuid-Holland, Netherlands

    • HB

      Harry R. Büller

      MD
      Department of Vascular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
      Amsterdam, Noord-Holland, Netherlands

    • MC

      Mark Courtney

      Professor of Emergency Medicine
      Department of Emergency Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.
      Texas, Texas, United States

    • YF

      Yonathan Freund

      Professor of Emergency Medicine
      Sorbonne University, Emergency Department, Hôpital Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, Paris, France
      Paris, Alsace, France

    • Gregoire Le Gal, MD PhD

      MD, PhD
      Ottawa Hospital Research Institute, University of Ottawa, Canada
      Ottawa, Ontario, Canada

    • WG

      Waleed Ghanima

      MD, PhD
      Departments of Oncology, Medicine and Research Ostfold Hospital Trust
      Kalnes, Ostfold, Norway

    • MH

      Menno V. Huisman

      MD, PhD
      Department of Medicine - Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands
      Leiden, Zuid-Holland, Netherlands

    • JK

      Jeffrey Kline

      Adjunct Professor of Emergency Medicine
      Department of Emergency Medicine, Wayne State University School of Medicine, Detroit, MI, USA
      Detroit, Missouri, United States

    • CM

      Carl Moons

      Professor of Clinical Epidemiology
      Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
      Utrecht, Utrecht, Netherlands

    • Marc Righini, MD

      MD
      Division of Angiology and Hemostasis, Geneva University Hospital and Faculty of Medicine, Geneva, Switzerland
      Geneve, Geneve, Switzerland

    • SP

      Sameer Parpia

      Associate Professor and Biostatistician
      Department of Health Research Methods, Evidence, & Impact, McMaster University
      Hamilton, Ontario, Canada

    • Pierre-Marie Roy, MD, PhD (he/him/his)

      MD, PhD
      Service des urgences, Centre Hospitalo-Universitaire d’Angers, Institut MITOVASC, EA 3860, Université d'Angers, Angers, FCRIN INNOVTE, France.
      Angers, Pays de la Loire, France

    • PW

      Philip S. Wells

      MD, MSc
      Department of Medicine, Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Canada.
      Ottawa, Ontario, Canada

    • Kerstin de Wit, MBChB, MSc, MD, MRCP, FRCEM, FRCPC

      Associate Professor
      Department of Emergency Medicine, Queen’s University
      Kingston, Ontario, Canada

    • Mv

      Maarten van Smeden

      PhD
      Julius Center for HealthSciences and Primary Care, University Medical Center Utrecht, Utrecht University
      Utrecht, Utrecht, Netherlands

    • Geert-Jan Geersing, MD, PhD

      Associate Professor
      Department General Practice, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
      Utrecht, Utrecht, Netherlands

    Background: Risk stratification is used for decisions about imaging in patients with clinically suspected acute pulmonary embolism (PE).

    Aims: To develop a clinical prediction model that provides an individualized, accurate probability estimate for acute pulmonary embolism (PE) based on readily available clinical items and D-dimer concentrations.

    Methods: An individual participant data meta-analysis was performed based on sixteen studies with data from 28,305 adult patients with clinically suspected PE from various clinical settings. A multilevel logistic regression model was built and validated including ten a priori defined objective candidate predictors to predict PE at baseline or during follow-up of 30-90 days. Multiple imputation was used for missing data. Backward elimination was performed with a P-value < 0.10. Discrimination (c-statistic with 95% CI and prediction intervals [PI]) and calibration (outcome:expected [O:E] ratio and calibration plot) were evaluated based on internal-external cross-validation. The accuracy of the model was compared to algorithms based on the Wells score and D-dimer testing.

    Results: The final model included age (in years), sex, previous VTE, recent surgery/immobilization, hemoptysis, cancer, clinical signs of DVT, inpatient status, D-dimer (in µg/L), and an interaction term between age and D-dimer. The pooled c-statistic was 0.87 (95%-CI, 0.85-0.89; 95%-PI, 0.77-0.93) and overall calibration was very good (pooled O:E ratio, 0.99; 95% CI, 0.87-1.14; 95% PI, 0.55-1.79). In the lower range of probabilities, the model slightly overestimated VTE probability. Discrimination of the current model in the validation data sets was better than that of the Wells score combined with a D-dimer threshold based on age (c-statistic 0.73; 95%-CI, 0.70-0.75) or structured clinical pretest probability (c-statistic 0.79; 95%-CI, 0.76-0.81).

    Conclusion(s): The present model provides an absolute, individualized probability of PE presence in a broad population of patients with suspected PE, with very good discrimination and calibration. Its clinical utility needs to be evaluated in a prospective management or impact study.

    Learning Objectives:

    • Upon completion, participants will be able to describe predictors of presence of pulmonary embolism among patients with clinically suspected pulmonary embolism
    • Upon completion, participants will understand the advantages of individualizd probability estimates for presence of pulmonary embolism compared to traditional risk classification
    • Upon completion, participants will be able to understand in which clinical settings or scenarios the new prediction model has an advantage over traditional diagnostic algorithms for patients with suspected pulmonary embolism