• Yu Lin Chen, Colin Wright, Anthony P Pietropaoli, Ayman Elbadawi, Joseph Delehanty, Bryan Barrus, Igor Gosev, David Trawick, Dhwani Patel, and Scott J Cameron.
• Department of Medicine, University of Rochester, Rochester, USA. Yulin_Chen@urmc.rochester.edu.
• J. Thromb. Thrombolysis. 2020 Jan 1; 49 (1): 34-41.

AbstractSeveral 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.

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