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A clinical approach to the diagnosis of patients with leukodystrophies and genetic leukoencephelopathies

Overview of attention for article published in Molecular Genetics & Metabolism, December 2014
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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)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

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7 X users
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3 patents
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2 Facebook pages
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1 YouTube creator

Citations

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168 Dimensions

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234 Mendeley
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Title
A clinical approach to the diagnosis of patients with leukodystrophies and genetic leukoencephelopathies
Published in
Molecular Genetics & Metabolism, December 2014
DOI 10.1016/j.ymgme.2014.12.434
Pubmed ID
Authors

Sumit Parikh, Geneviève Bernard, Richard J. Leventer, Marjo S. van der Knaap, Johan van Hove, Amy Pizzino, Nathan H. McNeill, Guy Helman, Cas Simons, Johanna L. Schmidt, William B. Rizzo, Marc C. Patterson, Ryan J. Taft, Adeline Vanderver, on behalf of the GLIA Consortium

Abstract

Leukodystrophies (LD) and genetic leukoencephalopathies (gLE) are disorders that result in white matter abnormalities in the central nervous system (CNS). Magnetic resonance (MR) imaging (MRI) has dramatically improved and systematized the diagnosis of LDs and gLEs, and in combination with specific clinical features, such as Addison's disease in Adrenoleukodystrophy or hypodontia in Pol-III related or 4H leukodystrophy, can often resolve a case with a minimum of testing. The diagnostic odyssey for the majority LD and gLE patients, however, remains extensive - many patients will wait nearly a decade for a definitive diagnosis and at least half will remain unresolved. The combination of MRI, careful clinical evaluation and next generation genetic sequencing holds promise for both expediting the diagnostic process and dramatically reducing the number of unresolved cases. Here we present a workflow detailing the Global Leukodystrophy Initiative (GLIA) consensus recommendations for an approach to clinical diagnosis, including salient clinical features suggesting a specific diagnosis, neuroimaging features and molecular genetic testing. We also discuss recommendations on the use of broad-spectrum next-generation sequencing in instances of ambiguous MRI or clinical findings. We conclude with a proposal for systematic trials of genome-wide agnostic testing as a first line diagnostic in LDs and gLEs given the increasing number of genes associated with these disorders.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 234 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 <1%
Italy 1 <1%
South Africa 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 229 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 30 13%
Student > Ph. D. Student 25 11%
Student > Bachelor 24 10%
Other 23 10%
Student > Postgraduate 22 9%
Other 67 29%
Unknown 43 18%
Readers by discipline Count As %
Medicine and Dentistry 98 42%
Neuroscience 37 16%
Biochemistry, Genetics and Molecular Biology 17 7%
Agricultural and Biological Sciences 10 4%
Nursing and Health Professions 4 2%
Other 12 5%
Unknown 56 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 01 October 2023.
All research outputs
#3,338,982
of 26,017,215 outputs
Outputs from Molecular Genetics & Metabolism
#152
of 2,413 outputs
Outputs of similar age
#43,918
of 365,183 outputs
Outputs of similar age from Molecular Genetics & Metabolism
#3
of 33 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,413 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 93% 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 365,183 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 particularly well, scoring higher than 90% of its contemporaries.