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Quantifying fat replacement of muscle by quantitative MRI in muscular dystrophy

Overview of attention for article published in Journal of Neurology, July 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

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8 X users
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2 patents

Citations

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156 Dimensions

Readers on

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198 Mendeley
Title
Quantifying fat replacement of muscle by quantitative MRI in muscular dystrophy
Published in
Journal of Neurology, July 2017
DOI 10.1007/s00415-017-8547-3
Pubmed ID
Authors

Jedrzej Burakiewicz, Christopher D. J. Sinclair, Dirk Fischer, Glenn A. Walter, Hermien E. Kan, Kieren G. Hollingsworth

Abstract

The muscular dystrophies are rare orphan diseases, characterized by progressive muscle weakness: the most common and well known is Duchenne muscular dystrophy which affects young boys and progresses quickly during childhood. However, over 70 distinct variants have been identified to date, with different rates of progression, implications for morbidity, mortality, and quality of life. There are presently no curative therapies for these diseases, but a range of potential therapies are presently reaching the stage of multi-centre, multi-national first-in-man clinical trials. There is a need for sensitive, objective end-points to assess the efficacy of the proposed therapies. Present clinical measurements are often too dependent on patient effort or motivation, and lack sensitivity to small changes, or are invasive. Quantitative MRI to measure the fat replacement of skeletal muscle by either chemical shift imaging methods (Dixon or IDEAL) or spectroscopy has been demonstrated to provide such a sensitive, objective end-point in a number of studies. This review considers the importance of the outcome measures, discusses the considerations required to make robust measurements and appropriate quality assurance measures, and draws together the existing literature for cross-sectional and longitudinal cohort studies using these methods in muscular dystrophy.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 198 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 198 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 33 17%
Student > Ph. D. Student 32 16%
Student > Master 21 11%
Student > Bachelor 13 7%
Other 12 6%
Other 29 15%
Unknown 58 29%
Readers by discipline Count As %
Medicine and Dentistry 52 26%
Engineering 20 10%
Neuroscience 12 6%
Nursing and Health Professions 8 4%
Physics and Astronomy 6 3%
Other 29 15%
Unknown 71 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 21 March 2023.
All research outputs
#2,800,414
of 23,572,442 outputs
Outputs from Journal of Neurology
#569
of 4,604 outputs
Outputs of similar age
#52,508
of 315,242 outputs
Outputs of similar age from Journal of Neurology
#7
of 56 outputs
Altmetric has tracked 23,572,442 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,604 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.3. This one has done well, scoring higher than 87% 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 315,242 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 83% of its contemporaries.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.