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      Multiparametric exercise stress cardiovascular magnetic resonance in the diagnosis of coronary artery disease: the EMPIRE trial

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          Abstract

          Background

          Stress cardiovascular magnetic resonance (CMR) offers assessment of ventricular function, myocardial perfusion and viability in a single examination to detect coronary artery disease (CAD).

          We developed an in-scanner exercise stress CMR (ExCMR) protocol using supine cycle ergometer and aimed to examine the diagnostic value of a multiparametric approach in patients with suspected CAD, compared with invasive fractional flow reserve (FFR) as the reference gold standard.

          Methods

          In this single-centre prospective study, patients who had symptoms of angina and at least one cardiovascular disease risk factor underwent both ExCMR and invasive angiography with FFR. Rest-based left ventricular function (ejection fraction, regional wall motion abnormalities), tissue characteristics and exercise stress-derived (perfusion defects, inducible regional wall motion abnormalities and peak exercise cardiac index percentile-rank) CMR parameters were evaluated in the study.

          Results

          In the 60 recruited patients with intermediate CAD risk, 50% had haemodynamically significant CAD based on FFR. Of all the CMR parameters assessed, the late gadolinium enhancement, stress-inducible regional wall motion abnormalities, perfusion defects and peak exercise cardiac index percentile-rank were independently associated with FFR-positive CAD. Indeed, this multiparametric approach offered the highest incremental diagnostic value compared to a clinical risk model ( χ 2 for the diagnosis of FFR-positive increased from 7.6 to 55.9; P < 0.001) and excellent performance [c-statistic area under the curve 0.97 (95% CI: 0.94–1.00)] in discriminating between FFR-normal and FFR-positive patients.

          Conclusion

          The study demonstrates the clinical potential of using in-scanner multiparametric ExCMR to accurately diagnose CAD.

          Trial registration: ClinicalTrials.gov, NCT03217227, Registered 11 July 2017–Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03217227?id=NCT03217227&draw=2&rank=1&load=cart

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          Most cited references45

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          Purposeful selection of variables in logistic regression

          Background The main problem in many model-building situations is to choose from a large set of covariates those that should be included in the "best" model. A decision to keep a variable in the model might be based on the clinical or statistical significance. There are several variable selection algorithms in existence. Those methods are mechanical and as such carry some limitations. Hosmer and Lemeshow describe a purposeful selection of covariates within which an analyst makes a variable selection decision at each step of the modeling process. Methods In this paper we introduce an algorithm which automates that process. We conduct a simulation study to compare the performance of this algorithm with three well documented variable selection procedures in SAS PROC LOGISTIC: FORWARD, BACKWARD, and STEPWISE. Results We show that the advantage of this approach is when the analyst is interested in risk factor modeling and not just prediction. In addition to significant covariates, this variable selection procedure has the capability of retaining important confounding variables, resulting potentially in a slightly richer model. Application of the macro is further illustrated with the Hosmer and Lemeshow Worchester Heart Attack Study (WHAS) data. Conclusion If an analyst is in need of an algorithm that will help guide the retention of significant covariates as well as confounding ones they should consider this macro as an alternative tool.
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            Initial Invasive or Conservative Strategy for Stable Coronary Disease

            Among patients with stable coronary disease and moderate or severe ischemia, whether clinical outcomes are better in those who receive an invasive intervention plus medical therapy than in those who receive medical therapy alone is uncertain.
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              Clinical recommendations for cardiovascular magnetic resonance mapping of T1, T2, T2* and extracellular volume: A consensus statement by the Society for Cardiovascular Magnetic Resonance (SCMR) endorsed by the European Association for Cardiovascular Imaging (EACVI)

              Parametric mapping techniques provide a non-invasive tool for quantifying tissue alterations in myocardial disease in those eligible for cardiovascular magnetic resonance (CMR). Parametric mapping with CMR now permits the routine spatial visualization and quantification of changes in myocardial composition based on changes in T1, T2, and T2*(star) relaxation times and extracellular volume (ECV). These changes include specific disease pathways related to mainly intracellular disturbances of the cardiomyocyte (e.g., iron overload, or glycosphingolipid accumulation in Anderson-Fabry disease); extracellular disturbances in the myocardial interstitium (e.g., myocardial fibrosis or cardiac amyloidosis from accumulation of collagen or amyloid proteins, respectively); or both (myocardial edema with increased intracellular and/or extracellular water). Parametric mapping promises improvements in patient care through advances in quantitative diagnostics, inter- and intra-patient comparability, and relatedly improvements in treatment. There is a multitude of technical approaches and potential applications. This document provides a summary of the existing evidence for the clinical value of parametric mapping in the heart as of mid 2017, and gives recommendations for practical use in different clinical scenarios for scientists, clinicians, and CMR manufacturers.
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                Author and article information

                Contributors
                le.thu.thao@nhcs.com.sg
                Journal
                J Cardiovasc Magn Reson
                J Cardiovasc Magn Reson
                Journal of Cardiovascular Magnetic Resonance
                BioMed Central (London )
                1097-6647
                1532-429X
                4 March 2021
                4 March 2021
                2021
                : 23
                : 17
                Affiliations
                [1 ]GRID grid.419385.2, ISNI 0000 0004 0620 9905, National Heart Research Institute Singapore, National Heart Centre Singapore, ; 5 Hospital Drive, Singapore, 169609 Singapore
                [2 ]GRID grid.428397.3, ISNI 0000 0004 0385 0924, Cardiovascular Sciences ACP, Duke-NUS Graduate Medical School, ; Singapore, Singapore
                [3 ]GRID grid.419385.2, ISNI 0000 0004 0620 9905, Department of Cardiology, , National Heart Centre Singapore, ; Singapore, Singapore
                [4 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, National Heart and Lung Institute, Imperial College, ; London, UK
                Article
                705
                10.1186/s12968-021-00705-8
                7931509
                33658056
                1f9d8cc1-1e58-446a-8a38-30f6beafd1b2
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 21 July 2020
                : 6 January 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001381, National Research Foundation Singapore;
                Award ID: NMRC/OFYIRG/030/2017
                Award ID: NMRC/CGAug16/M006
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Cardiovascular Medicine
                exercise stress,supine cycle ergometer,coronary artery disease,cardiovascular magnetic resonance,fractional flow reserve

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