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Autosomal dominant cerebellar ataxias: Imaging biomarkers with high effect sizes

Overview of attention for article published in NeuroImage: Clinical, January 2018
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (58th percentile)

Mentioned by

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5 tweeters

Citations

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28 Dimensions

Readers on

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37 Mendeley
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Title
Autosomal dominant cerebellar ataxias: Imaging biomarkers with high effect sizes
Published in
NeuroImage: Clinical, January 2018
DOI 10.1016/j.nicl.2018.06.011
Pubmed ID
Authors

Isaac M. Adanyeguh, Vincent Perlbarg, Pierre-Gilles Henry, Daisy Rinaldi, Elodie Petit, Romain Valabregue, Alexis Brice, Alexandra Durr, Fanny Mochel

Abstract

As gene-based therapies may soon arise for patients with spinocerebellar ataxia (SCA), there is a critical need to identify biomarkers of disease progression with effect sizes greater than clinical scores, enabling trials with smaller sample sizes. We enrolled a unique cohort of patients with SCA1 (n = 15), SCA2 (n = 12), SCA3 (n = 20) and SCA7 (n = 10) and 24 healthy controls of similar age, sex and body mass index. We collected longitudinal clinical and imaging data at baseline and follow-up (mean interval of 24 months). We performed both manual and automated volumetric analyses. Diffusion tensor imaging (DTI) and a novel tractography method, called fixel-based analysis (FBA), were assessed at follow-up. Effect sizes were calculated for clinical scores and imaging parameters. Clinical scores worsened as atrophy increased over time (p < 0.05). However, atrophy of cerebellum and pons showed very large effect sizes (>1.2) compared to clinical scores (<0.8). FBA, applied for the first time to SCA, was sensitive to microstructural cross-sectional differences that were not captured by conventional DTI metrics, especially in the less studied SCA7 group. FBA also showed larger effect sizes than DTI metrics. This study showed that volumetry outperformed clinical scores to measure disease progression in SCA1, SCA2, SCA3 and SCA7. Therefore, we advocate the use of volumetric biomarkers in therapeutic trials of autosomal dominant ataxias. In addition, FBA showed larger effect size than DTI to detect cross-sectional microstructural alterations in patients relative to controls.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 19%
Researcher 4 11%
Student > Master 4 11%
Lecturer 2 5%
Student > Bachelor 2 5%
Other 7 19%
Unknown 11 30%
Readers by discipline Count As %
Neuroscience 6 16%
Medicine and Dentistry 6 16%
Psychology 4 11%
Computer Science 1 3%
Agricultural and Biological Sciences 1 3%
Other 4 11%
Unknown 15 41%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 03 July 2018.
All research outputs
#7,997,086
of 15,553,472 outputs
Outputs from NeuroImage: Clinical
#892
of 1,839 outputs
Outputs of similar age
#112,710
of 277,013 outputs
Outputs of similar age from NeuroImage: Clinical
#1
of 1 outputs
Altmetric has tracked 15,553,472 research outputs across all sources so far. This one is in the 48th percentile – i.e., 48% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,839 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.2. This one has gotten more attention than average, scoring higher than 50% 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 277,013 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them