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Thieme Gruppe, Thrombosis and Haemostasis, 04(115), p. 827-834, 2016

DOI: 10.1160/th15-09-0761

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Effectiveness of prognosticating pulmonary embolism using the ESC algorithm and the Bova score:

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

SummaryThe prognostic value of the European Society of Cardiology (ESC) 2014 algorithm and the Bova score has lacked adequate validation. According to the ESC 2014 guidelines and the Bova score, we retrospectively risk stratified normotensive patients with PE who were enrolled in the PROTECT study. This study used a complicated course (which consisted of death from any cause, haemodynamic collapse, or recurrent PE) as the primary endpoint, and follow-up occurred through 30 days after the PE diagnosis. Of 848 patients, 37 % had a sPESI of 0 and 5 (1.6 %; 95 % confidence interval [CI], 0.5-3.7 %) experienced a complicated course. Of 143 patients with a sPESI of 0 points and negative computed tomographic pulmonary angiography (CTPA) for right ventricle (RV) dysfunction, three (2.1 %; 95 % CI, 0.4-6.0 %) experienced a complicated course. Four hundred seventy-eight (56 %) patients with a sPESI ≥ 1 had echocardiographic evidence of RV dysfunction or elevated troponin level or none, and 48 (10 %, 95 % CI, 7.5-13.1 %) experienced a complicated course. Fifty-seven (6.7 %) patients with a sPESI ≥ 1 had echocardiographic RV dysfunction and elevated troponin level, and 10 (17.5 %; 95 % CI, 8.8-29.9 %) experienced a complicated course, compared to 21.6 % (8 of 37 patients, 21.6 %; 95 % CI, 9.8-38.2 %) in Bova risk class III. In conclusion, the ESC 2014 prognostic algorithm is effective in the risk stratification of normotensive patients with PE. Use of CTPA did not improve the ability for identification of low-risk PE. Bova risk scoring did not significantly improve identification of intermediate-high risk PE.Jiménez et al. Validation of the ESC 2014 prognostication algorithm