Skip to main content

Advertisement

SpringerLink
Log in

Right ventricular dysfunction is superior and sufficient for risk stratification by a pulmonary embolism response team

  • Published:
Journal of Thrombosis and Thrombolysis Aims and scope Submit manuscript

Abstract

Several risk stratification tools are available to predict short-term mortality in patients with acute pulmonary embolism (PE). The presence of right ventricular (RV) dysfunction is an independent predictor of mortality and may be a more efficient way to stratify risk for patients assessed by a Pulmonary Embolism Response Team (PERT). We evaluated 571 patients presenting with acute PE, then stratified them by the pulmonary embolism severity index (PESI), by the BOVA score, or categorically as low risk (no RV dysfunction by imaging), intermediate risk/submassive (RV dysfunction by imaging), or high risk/massive PE (RV dysfunction with sustained hypotension). Using imaging data to firstly define the presence of RV strain, and plasma cardiac biomarkers as additional evidence for myocardial dysfunction, we evaluated whether PESI, BOVA, or RV strain by imaging were more appropriate for determining patient risk by a PERT where rapid decision making is important. Cardiac biomarkers poorly distinguished between PESI classes and BOVA stages in patients with acute PE. Cardiac TnT and NT-proBNP easily distinguished low risk from submassive PE with an area under the curve (AUC) of 0.84 (95% CI 0.73–0.95, p < 0.0001), and 0.88 (95% CI 0.79–0.97, p < 0.0001), respectively. Cardiac TnT and NT-proBNP easily distinguished low risk from massive PE with an area under the curve (AUC) of 0.89 (95% CI 0.78–1.00, p < 0.0001), and 0.89 (95% CI 0.82–0.95, p < 0.0001), respectively. In patients with RV dysfunction, the predicted short-term mortality by PESI score or BOVA stage was lower than the observed mortality by a two-fold order of magnitude. The presence of RV dysfunction alone in the context of acute PE is sufficient for the purposes of risk stratification. More complicated risk stratification tools which require the consideration of multiple clinical variables may under-estimate short-term mortality risk.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Wood KE (2002) Major pulmonary embolism: review of a pathophysiologic approach to the golden hour of hemodynamically significant pulmonary embolism. Chest 121(3):877–905

    Article  Google Scholar 

  2. Friedman T et al (2018) Patient assessment: clinical presentation, imaging diagnosis, risk stratification, and the role of pulmonary embolism response team. Semin Intervent Radiol 35(2):116–121

    Article  Google Scholar 

  3. Jimenez D et al (2007) Prognostic models for selecting patients with acute pulmonary embolism for initial outpatient therapy. Chest 132(1):24–30

    Article  Google Scholar 

  4. Aujesky D et al (2005) Derivation and validation of a prognostic model for pulmonary embolism. Am J Respir Crit Care Med 172(8):1041–1046

    Article  Google Scholar 

  5. Aujesky D et al (2006) Validation of a model to predict adverse outcomes in patients with pulmonary embolism. Eur Heart J 27(4):476–481

    Article  Google Scholar 

  6. Aujesky D et al (2007) Validation of a clinical prognostic model to identify low-risk patients with pulmonary embolism. J Intern Med 261(6):597–604

    Article  CAS  Google Scholar 

  7. Masotti L et al (2009) Prognostic stratification of acute pulmonary embolism: focus on clinical aspects, imaging, and biomarkers. Vasc Health Risk Manag 5(4):567–575

    Article  CAS  Google Scholar 

  8. Bova C et al (2014) Identification of intermediate-risk patients with acute symptomatic pulmonary embolism. Eur Respir J 44(3):694–703

    Article  Google Scholar 

  9. Bikdeli B et al (2018) Early use of echocardiography in patients with acute pulmonary embolism: findings from the RIETE registry. J Am Heart Assoc 7(17):e009042

    Article  Google Scholar 

  10. Kucher N et al (2005) Prognostic role of echocardiography among patients with acute pulmonary embolism and a systolic arterial pressure of 90 mm Hg or higher. Arch Intern Med 165(15):1777–1781

    Article  Google Scholar 

  11. Cho JH et al (2014) Right ventricular dysfunction as an echocardiographic prognostic factor in hemodynamically stable patients with acute pulmonary embolism: a meta-analysis. BMC Cardiovasc Disord 14:64

    Article  Google Scholar 

  12. Darwish OS et al (2018) Cardiac troponins in low-risk pulmonary embolism patients: a systematic review and meta-analysis. J Hosp Med 13(10):706–712

    PubMed  Google Scholar 

  13. Kearon C et al (2016) Antithrombotic therapy for VTE disease: chest guideline and expert panel report. Chest 149(2):315–352

    Article  Google Scholar 

  14. Konstantinides SV et al (2014) ESC guidelines on the diagnosis and management of acute pulmonary embolism. Eur Heart J 35(43):3033–3069

    Article  CAS  Google Scholar 

  15. Rosovsky R et al (2019) Changes in treatment and outcomes after creation of a pulmonary embolism response team (PERT), a 10-year analysis. J Thromb Thrombolysis 47(1):31–40

    Article  Google Scholar 

  16. Xenos ES et al (2019) The implementation of a pulmonary embolism response team in the management of intermediate- or high-risk pulmonary embolism. J Vasc Surg Venous Lymphat Disord 7(4):493–500

    Article  Google Scholar 

  17. Mahar JH et al (2018) A pulmonary embolism response team (PERT) approach: initial experience from the Cleveland Clinic. J Thromb Thrombolysis 46(2):186–192

    Article  CAS  Google Scholar 

  18. Elbadawi A et al (2018) The impact of a multi-specialty team for high risk pulmonary embolism on resident and fellow education. Vasc Med 23(4):372–376

    Article  Google Scholar 

  19. Secemsky E et al (2018) Contemporary management and outcomes of patients with massive and submassive pulmonary embolism. Am J Med 131(12):1506–1514

    Article  Google Scholar 

  20. Jaff MR et al (2011) Management of massive and submassive pulmonary embolism, iliofemoral deep vein thrombosis, and chronic thromboembolic pulmonary hypertension: a scientific statement from the American Heart Association. Circulation 123(16):1788–1830

    Article  Google Scholar 

  21. Sanchez O et al (2008) Prognostic value of right ventricular dysfunction in patients with haemodynamically stable pulmonary embolism: a systematic review. Eur Heart J 29(12):1569–1577

    Article  Google Scholar 

  22. Chan CM, Woods CJ, Shorr AF (2012) Comparing the pulmonary embolism severity index and the prognosis in pulmonary embolism scores as risk stratification tools. J Hosp Med 7(1):22–27

    Article  Google Scholar 

  23. Vanderheyden M et al (2010) B-type natriuretic peptide as a marker of heart failure: new insights from biochemistry and clinical implications. Biomark Med 4(2):315–320

    Article  CAS  Google Scholar 

  24. Mair J (2008) Biochemistry of B-type natriuretic peptide–where are we now? Clin Chem Lab Med 46(11):1507–1514

    Article  CAS  Google Scholar 

  25. Goetze JP (2004) Biochemistry of pro-B-type natriuretic peptide-derived peptides: the endocrine heart revisited. Clin Chem 50(9):1503–1510

    Article  CAS  Google Scholar 

  26. Semenov AG, Seferian KR (2011) Biochemistry of the human B-type natriuretic peptide precursor and molecular aspects of its processing. Clin Chim Acta 412(11–12):850–860

    Article  CAS  Google Scholar 

  27. Panteghini M, Clerico A (2004) Understanding the clinical biochemistry of N-terminal pro-B-type natriuretic peptide: the prerequisite for its optimal clinical use. Clin Lab 50(5–6):325–331

    PubMed  CAS  Google Scholar 

  28. Arbustini E et al (1990) Expression of natriuretic peptide in ventricular myocardium of failing human hearts and its correlation with the severity of clinical and hemodynamic impairment. Am J Cardiol 66(12):973–980

    Article  CAS  Google Scholar 

  29. Klok FA, Mos IC, Huisman MV (2008) Brain-type natriuretic peptide levels in the prediction of adverse outcome in patients with pulmonary embolism: a systematic review and meta-analysis. Am J Respir Crit Care Med 178(4):425–430

    Article  Google Scholar 

  30. Jimenez D et al (2009) Troponin-based risk stratification of patients with acute nonmassive pulmonary embolism: systematic review and metaanalysis. Chest 136(4):974–982

    Article  Google Scholar 

  31. Becattini C, Vedovati MC, Agnelli G (2007) Prognostic value of troponins in acute pulmonary embolism: a meta-analysis. Circulation 116(4):427–433

    Article  CAS  Google Scholar 

  32. Ferrando-Castagnetto F et al (2017) Atrial arrhythmias and scintigraphic “D-shape” sign in pulmonary artery hypertension. World J Nucl Med 16(1):75–77

    Article  Google Scholar 

  33. Movahed MR (2014) D-shaped left ventricle seen on gated single-photon emission computed tomography is suggestive of right ventricular overload: the so-called Movahed’s sign. Am J Med 127(12):e37

    Article  Google Scholar 

  34. Lodato JA, Ward RP, Lang RM (2008) Echocardiographic predictors of pulmonary embolism in patients referred for helical CT. Echocardiography 25(6):584–590

    Article  Google Scholar 

Download references

Funding

The following financial funding agencies provided financial support: National Institutes of Health (NIH) grants NIH 3K08HL128856, and HL12020 to Dr. Cameron

Author information

Authors and Affiliations

  1. Department of Medicine, University of Rochester, Rochester, USA

    Yu Lin Chen, Colin Wright, Anthony P. Pietropaoli, Ayman Elbadawi, David Trawick & Scott J. Cameron

  2. Department of General Medicine, University of Rochester, Rochester, USA

    Yu Lin Chen & Dhwani Patel

  3. Department of Cardiology, University of Rochester, Aab CVRI, Box CVRI, Box 601 Elmwood Ave, Rochester, NY, 14624, USA

    Colin Wright, Joseph Delehanty & Scott J. Cameron

  4. Pulmonary Medicine and Critical Care, University of Rochester, Rochester, USA

    Anthony P. Pietropaoli & David Trawick

  5. Department of Cardiovascular Medicine, University of Texas Medical Branch, Galveston, TX, USA

    Ayman Elbadawi

  6. Department of Surgery, Cardiac Surgery, University of Rochester, Rochster, USA

    Bryan Barrus, Igor Gosev & Scott J. Cameron

Authors
  1. Yu Lin Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Colin Wright
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Anthony P. Pietropaoli
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ayman Elbadawi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Joseph Delehanty
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Bryan Barrus
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Igor Gosev
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. David Trawick
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Dhwani Patel
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Scott J. Cameron
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Study concept, design, and development (YC, CW, AE, JD, AP, DP, DT, IG, BB, and SC), data acquisition (YC, AE, CW, DP, and SC), statistical analysis and interpretation (YC and SC), drafting of the manuscript (YC and SC).

Corresponding author

Correspondence to Yu Lin Chen.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Figure 1 Clinical variables determining PESI Class (TIFF 1522 kb)

Supplementary Figure 2 Clinical variables determining BOVA Group (TIFF 1522 kb)

Supplementary Figure 3 Radiographic determinants of RV dysfunction (TIFF 1522 kb)

11239_2019_1922_MOESM4_ESM.tiff

Supplementary Figure 4 Inclusion criteria for patients screened by ICD-9 Code and stratification according to category, PESI Class, or Bova Stage (TIFF 1522 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, Y.L., Wright, C., Pietropaoli, A.P. et al. Right ventricular dysfunction is superior and sufficient for risk stratification by a pulmonary embolism response team. J Thromb Thrombolysis 49, 34–41 (2020). https://doi.org/10.1007/s11239-019-01922-w

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11239-019-01922-w

Keywords

Search

Navigation