bioRxivBiochemistryPreprint
Categorical Assignment of Pulmonary Embolism is a Simple and More Accurate Indicator of Right Ventricular Dysfunction and Short Team Mortality
Y. L. Chen, C. Wright, A. Pietropaoli, A. Elbadawi, J. Delehanty, B. Barrus, I. Gosev, D. Trawick, D. Patel, S. Cameron
Abstract
Several risk stratification tools are available to predict short-term mortality in patients with acute pulmonary embolism (PE). Right ventricular (RV) dysfunction, which is common to intermediate and high risk PE, is an independent predictor of mortality and may be a faster and simpler way to assess patient risk in acute care settings. We evaluated 571 patients presenting with acute PE as the primary diagnosis, stratifying them by the Pulmonary Embolism Severity Index (PESI), by the BOVA score, or categorically as low risk (no RV dysfunction by imaging), intermediate risk (RV dysfunction by imaging), or high risk PE (RV dysfunction by imaging with sustained hypotension). Using imaging data to firstly define the presence of RV dysfunction, and plasma cardiac troponin T (cTnT) and NT-proBNP as additional evidence for myocardial strain, we evaluated the PESI and BOVA scoring systems compared to categorical assignment of PE as low risk, submassive, and massive PE. 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% C.I. 0.73 - 0.95, p< 0.0001), and 0.88 (95% C.I. 0.79-0.97, p< 0.0001), respectively, and low risk from massive PE with an area under the curve (AUC) of 0.89 (95% C.I. 0.78 - 1.00, p< 0.0001), and 0.89 (95% C.I. 0.82-0.95, p< 0.0001), respectively. Predicted short-term mortality by PESI score or BOVA stage was lower than the observed mortality for submassive PE by a two-fold order of magnitude. These data suggest the presence of RV dysfunction in the context of acute PE is sufficient for the purposes of risk stratification, while more complicated risk stratification algorithms may under-estimate short-term mortality risk.
- organism: human
- assay: clinical cohort / trial
- research focus: host-pathogen & immune response
- approach: statistical model
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