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Distinctive facial features in idiopathic Moyamoya disease in Caucasians: a first systematic analysis

Overview of attention for article published in PeerJ, June 2018
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Title
Distinctive facial features in idiopathic Moyamoya disease in Caucasians: a first systematic analysis
Published in
PeerJ, June 2018
DOI 10.7717/peerj.4740
Pubmed ID
Authors

Markus Kraemer, Quoc Bao Huynh, Dagmar Wieczorek, Brunilda Balliu, Barbara Mikat, Stefan Boehringer

Abstract

Craniofacial dysmorphic features are morphological changes of the face and skull which are associated with syndromic conditions. Moyamoya angiopathy is a rare cerebral vasculopathy that can be divided into Moyamoya syndrome, which is associated or secondary to other diseases, and into idiopathic Moyamoya disease. Facial dysmorphism has been described in rare genetic syndromes with associated Moyamoya syndrome. However, a direct relationship between idiopathic Moyamoya disease with dysmorphic facial changes is not known yet. Landmarks were manually placed on frontal photographs of the face of 45 patients with bilateral Moyamoya disease and 50 matched controls. After procrustes alignment of landmarks a multivariate, penalized logistic regression (elastic-net) was performed on geometric features derived from landmark data to classify patients against controls. Classifiers were visualized in importance plots that colorcode importance of geometric locations for the classification decision. The classification accuracy for discriminating the total patient group from controls was 82.3% (P-value = 6.3×10-11, binomial test, a-priori chance 50.2%) for an elastic-net classifier. Importance plots show that differences around the eyes and forehead were responsible for the discrimination. Subgroup analysis corrected for body mass index confirmed a similar result. Results suggest that there is a resemblance in faces of Caucasian patients with idiopathic Moyamoya disease and that there is a difference to matched controls. Replication of findings is necessary as it is difficult to control all residual confounding in study designs such as ours. If our results would be replicated in a larger cohort, this would be helpful for pathophysiological interpretation and early detection of the disease.

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The data shown below were collected from the profiles of 3 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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 27%
Student > Ph. D. Student 3 20%
Student > Doctoral Student 1 7%
Professor 1 7%
Professor > Associate Professor 1 7%
Other 0 0%
Unknown 5 33%
Readers by discipline Count As %
Medicine and Dentistry 4 27%
Engineering 2 13%
Computer Science 1 7%
Biochemistry, Genetics and Molecular Biology 1 7%
Neuroscience 1 7%
Other 1 7%
Unknown 5 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 29 June 2018.
All research outputs
#14,134,028
of 23,092,602 outputs
Outputs from PeerJ
#7,794
of 13,486 outputs
Outputs of similar age
#180,163
of 329,163 outputs
Outputs of similar age from PeerJ
#378
of 644 outputs
Altmetric has tracked 23,092,602 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,486 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.3. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
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 329,163 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 644 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.