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Quantification of mitral regurgitation in patients with hypertrophic cardiomyopathy using aortic and pulmonary flow data: impacts of left ventricular outflow tract obstruction and different left…

Overview of attention for article published in Critical Reviews in Diagnostic Imaging, December 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

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Title
Quantification of mitral regurgitation in patients with hypertrophic cardiomyopathy using aortic and pulmonary flow data: impacts of left ventricular outflow tract obstruction and different left ventricular segmentation methods
Published in
Critical Reviews in Diagnostic Imaging, December 2017
DOI 10.1186/s12968-017-0417-8
Pubmed ID
Authors

Mateusz Śpiewak, Mariusz Kłopotowski, Monika Gawor, Agata Kubik, Ewa Kowalik, Barbara Miłosz-Wieczorek, Maciej Dąbrowski, Konrad Werys, Łukasz Mazurkiewicz, Katarzyna Kożuch, Magdalena Polańska-Skrzypczyk, Joanna Petryka-Mazurkiewicz, Anna Klisiewicz, Zofia T. Bilińska, Jacek Grzybowski, Adam Witkowski, Magdalena Marczak

Abstract

Cardiovascular magnetic resonance (CMR) imaging in patients with hypertrophic cardiomyopathy (HCM) enables the assessment of not only left ventricular (LV) hypertrophy and scarring but also the severity of mitral regurgitation. CMR assessment of mitral regurgitation is primarily based on the difference between LV stroke volume (LVSV) and aortic forward flow (Ao) measured using the phase-contrast (PC) technique. However, LV outflow tract (LVOT) obstruction causing turbulent, non-laminar flow in the ascending aorta may impact the accuracy of aortic flow quantification, leading to false conclusions regarding mitral regurgitation severity. Thus, we decided to quantify mitral regurgitation in patients with HCM using Ao or, alternatively, main pulmonary artery forward flow (MPA) for mitral regurgitation volume (MRvol) calculations. The analysis included 143 prospectively recruited subjects with HCM and 15 controls. MRvol was calculated as the difference between LVSV computed with either the inclusion (LVSVincl) or exclusion (LVSVexcl) of papillary muscles and trabeculations from the blood pool and either Ao (MRvolAoi or MRvolAoe) or MPA (MRvolMPAi or MRvolMPAe). The presence or absence of LVOT obstruction was determined based on Doppler echocardiography findings. MRvolAoi was higher than MRvolMPAi in HCM patients with LVOT obstruction [47.0 ml, interquartile range (IQR) = 31.5-60.0 vs. 35.5 ml, IQR = 26.0-51.0; p < 0.0001] but not in non-obstructive HCM patients (23.0 ml, IQR = 16.0-32.0 vs. 24.0 ml, IQR = 15.3-32.0; p = 0.26) or controls (18.0 ml, IQR = 14.3-21.8 vs. 20.0 ml, IQR = 14.3-22.0; p = 0.89). In contrast to controls and HCM patients without LVOT obstruction, in HCM patients with LVOT obstruction, aortic flow-based MRvol (MRvolAoi) was higher than pulmonary-based findings (MRvolMPAi) (bias = 9.5 ml; limits of agreement: -11.7-30.7 with a difference of 47 ml in the extreme case). The differences between aortic-based and pulmonary-based MRvol values calculated using LVSVexcl mirrored those derived using LVSVincl. However, MRvol values calculated using LVSVexcl were lower in all the groups analyzed (HCM with LVOT obstruction, HCM without LVOT obstruction, and controls) and with all methods of MRvol quantification used (p ≤ 0.0001 for all comparisons). In HCM patients, LVOT obstruction significantly affects the estimation of aortic flow, leading to its underestimation and, consequently, to higher MRvol values than those obtained with MPA-based MRvol calculations.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 18%
Researcher 6 15%
Other 4 10%
Student > Bachelor 4 10%
Student > Master 3 8%
Other 6 15%
Unknown 9 23%
Readers by discipline Count As %
Medicine and Dentistry 18 46%
Biochemistry, Genetics and Molecular Biology 2 5%
Computer Science 1 3%
Economics, Econometrics and Finance 1 3%
Agricultural and Biological Sciences 1 3%
Other 4 10%
Unknown 12 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 January 2018.
All research outputs
#2,566,590
of 25,728,855 outputs
Outputs from Critical Reviews in Diagnostic Imaging
#114
of 1,386 outputs
Outputs of similar age
#55,122
of 449,985 outputs
Outputs of similar age from Critical Reviews in Diagnostic Imaging
#7
of 33 outputs
Altmetric has tracked 25,728,855 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,386 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has done particularly well, scoring higher than 91% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 449,985 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.