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Evaluation and integration of disparate classification systems for clefts of the lip

Overview of attention for article published in Frontiers in Physiology, May 2014
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Title
Evaluation and integration of disparate classification systems for clefts of the lip
Published in
Frontiers in Physiology, May 2014
DOI 10.3389/fphys.2014.00163
Pubmed ID
Authors

Kathie H. Wang, Carrie L. Heike, Melissa D. Clarkson, Jose L. V. Mejino, James F. Brinkley, Raymond W. Tse, Craig B. Birgfeld, David A. Fitzsimons, Timothy C. Cox

Abstract

Orofacial clefting is a common birth defect with wide phenotypic variability. Many systems have been developed to classify cleft patterns to facilitate diagnosis, management, surgical treatment, and research. In this review, we examine the rationale for different existing classification schemes and determine their inter-relationships, as well as strengths and deficiencies for subclassification of clefts of the lip. The various systems differ in how they describe and define attributes of cleft lip (CL) phenotypes. Application and analysis of the CL classifications reveal discrepancies that may result in errors when comparing studies that use different systems. These inconsistencies in terminology, variable levels of subclassification, and ambiguity in some descriptions may confound analyses and impede further research aimed at understanding the genetics and etiology of clefts, development of effective treatment options for patients, as well as cross-institutional comparisons of outcome measures. Identification and reconciliation of discrepancies among existing systems is the first step toward creating a common standard to allow for a more explicit interpretation that will ultimately lead to a better understanding of the causes and manifestations of phenotypic variations in clefting.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
Unknown 102 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 14 13%
Student > Bachelor 14 13%
Student > Ph. D. Student 12 11%
Other 10 10%
Student > Postgraduate 9 9%
Other 23 22%
Unknown 23 22%
Readers by discipline Count As %
Medicine and Dentistry 55 52%
Agricultural and Biological Sciences 5 5%
Biochemistry, Genetics and Molecular Biology 4 4%
Economics, Econometrics and Finance 2 2%
Arts and Humanities 2 2%
Other 9 9%
Unknown 28 27%
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 14 May 2014.
All research outputs
#20,229,658
of 22,755,127 outputs
Outputs from Frontiers in Physiology
#9,328
of 13,559 outputs
Outputs of similar age
#192,931
of 227,204 outputs
Outputs of similar age from Frontiers in Physiology
#74
of 110 outputs
Altmetric has tracked 22,755,127 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,559 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.5. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 110 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.