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Novel grading system for quantification of cystic macular lesions in Usher syndrome

Overview of attention for article published in Orphanet Journal of Rare Diseases, December 2015
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Title
Novel grading system for quantification of cystic macular lesions in Usher syndrome
Published in
Orphanet Journal of Rare Diseases, December 2015
DOI 10.1186/s13023-015-0372-0
Pubmed ID
Authors

Ieva Sliesoraityte, Tunde Peto, Saddek Mohand-Said, Jose Alain Sahel

Abstract

To evaluate novel grading system used to quantify optical coherence tomography (OCT) scans for cystic macular lesions (CML) in Usher syndrome (USH) patients, focusing on CML associated alterations in MOY7A and USH2A mutations. Two readers evaluated 76 patients' (mean age 42 ± 14 years) data prospectively uploaded on Eurush database. OCT was used to obtain high quality cross-sectional images through the fovea. The CML was graded as none, mild, moderate or severe, depending on the following features set: subretinal fluid without clearly detectable CML boundaries; central macular thickness; largest diameter of CML; calculated mean of all detectable CML; total number of detectable CML; retinal layers affected by CML. Intra-and inter-grader reproducibility was evaluated. CML were observed in 37 % of USH eyes, while 45 % were observed in MYO7A and 29 % in USH2A cases. Of those with CML: 52 % had mild, 22 % had moderate and 26 % had severe changes, respectively. CML were found in following retinal layers: 50 % inner nuclear layer, 44 % outer nuclear layer, 6 % retinal ganglion cell layer. For the inter-grader repeatability analysis, agreements rates for CML were 97 % and kappa statistics was 0.91 (95 % CI 0.83-0.99). For the intra-grader analysis, agreement rates for CML were 98 %, while kappa statistics was 0.96 (95 % CI 0.92-0.99). The novel grading system is a reproducible tool for grading OCT images in USH complicated by CML, and potentially could be used for objective tracking of macular pathology in clinical therapy trials.

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Mendeley readers

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Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 4 14%
Other 2 7%
Student > Bachelor 2 7%
Professor 2 7%
Researcher 2 7%
Other 5 18%
Unknown 11 39%
Readers by discipline Count As %
Medicine and Dentistry 6 21%
Biochemistry, Genetics and Molecular Biology 3 11%
Nursing and Health Professions 2 7%
Psychology 2 7%
Physics and Astronomy 1 4%
Other 1 4%
Unknown 13 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 11 December 2015.
All research outputs
#20,653,708
of 25,368,786 outputs
Outputs from Orphanet Journal of Rare Diseases
#2,441
of 3,105 outputs
Outputs of similar age
#291,390
of 394,829 outputs
Outputs of similar age from Orphanet Journal of Rare Diseases
#38
of 40 outputs
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