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Dataset on the prognostic value of cardiac biomarkers used in clinical routine in patients with severe aortic stenosis undergoing valve replacement

Authors :
Fabian Barbieri
Thomas Senoner
Agne Adukauskaite
Stephan Dobner
Johannes Holfeld
Severin Semsroth
Thomas Lambert
David Zweiker
Thomas Theurl
Peter Rainer
Albrecht Schmidt
Gudrun Feuchtner
Clemens Steinwender
Uta Hoppe
Florian Hintringer
Axel Bauer
Silvana Müller
Michael Grimm
Bernhard Pfeifer
Wolfgang Dichtl
Source :
Data in Brief, Vol 29, Iss , Pp - (2020)
Publication Year :
2020
Publisher :
Elsevier, 2020.

Abstract

Hereby, the supplemental data of the research article “Long-Term Prognostic Value of High-Sensitivity Troponin T added to N-Terminal Pro Brain Natriuretic Peptide Plasma Levels before Valve Replacement for Severe Aortic Stenosis” are presented [1]. It offers enhanced input on the predictive value of these biomarkers considering the influence of the presence of concomitant coronary artery disease (CAD) in various severities as well as an additional cox proportional hazard model on cardiovascular mortality. Furthermore, the receiver operating characteristic (ROC) curves are shown as figures. The material described increases therefore the understanding of the predictive value of these already routinely available biomarkers and reduces the risk of potential bias due to possible confounding factors. It also underlines the urge for a multi-factorial approach in diagnostics to detect the optimal point for referral to valve replacement other than just symptomatic status, an observed reduction in left ventricular ejection fraction or the presence of CAD with the necessity for coronary artery bypass grafting (CABG) [2]. The data of the 3595 patients were gathered retrospectively at a consortium of four university hospital centers in Austria and combined with prospectively collected data on cardiovascular and all-cause mortality. Keywords: High sensitivity troponin T, N-terminal pro brain natiuretic peptide, Severe aortic stenosis, Valve replacement, Survival, Risk stratification

Details

Language :
English
ISSN :
23523409
Volume :
29
Issue :
-
Database :
Directory of Open Access Journals
Journal :
Data in Brief
Publication Type :
Academic Journal
Accession number :
edsdoj.9694e10427cf42c9a9af432ecd4bb6b6
Document Type :
article
Full Text :
https://doi.org/10.1016/j.dib.2020.105111