↓ Skip to main content

A New Coding System for Metabolic Disorders Demonstrates Gaps in the International Disease Classifications ICD‐10 and SNOMED‐CT, Which Can Be Barriers to Genotype–Phenotype Data Sharing

Overview of attention for article published in Human Mutation, June 2013
Altmetric Badge

Mentioned by

twitter
2 X users

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
38 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A New Coding System for Metabolic Disorders Demonstrates Gaps in the International Disease Classifications ICD‐10 and SNOMED‐CT, Which Can Be Barriers to Genotype–Phenotype Data Sharing
Published in
Human Mutation, June 2013
DOI 10.1002/humu.22316
Pubmed ID
Authors

Annet Sollie, Rolf H. Sijmons, Dick Lindhout, Ans T. van der Ploeg, M. Estela Rubio Gozalbo, G. Peter A. Smit, Frans Verheijen, Hans R. Waterham, Sonja van Weely, Frits A. Wijburg, Rudolph Wijburg, Gepke Visser

Abstract

Data sharing is essential for a better understanding of genetic disorders. Good phenotype coding plays a key role in this process. Unfortunately, the two most widely used coding systems in medicine, ICD-10 and SNOMED-CT, lack information necessary for the detailed classification and annotation of rare and genetic disorders. This prevents the optimal registration of such patients in databases and thus data-sharing efforts. To improve care and to facilitate research for patients with metabolic disorders, we developed a new coding system for metabolic diseases with a dedicated group of clinical specialists. Next, we compared the resulting codes with those in ICD and SNOMED-CT. No matches were found in 76% of cases in ICD-10 and in 54% in SNOMED-CT. We conclude that there are sizable gaps in the SNOMED-CT and ICD coding systems for metabolic disorders. There may be similar gaps for other classes of rare and genetic disorders. We have demonstrated that expert groups can help in addressing such coding issues. Our coding system has been made available to the ICD and SNOMED-CT organizations as well as to the Orphanet and HPO organizations for further public application and updates will be published online (www.ddrmd.nl and www.cineas.org).

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 3%
United States 1 3%
Unknown 36 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 32%
Student > Master 4 11%
Student > Ph. D. Student 4 11%
Other 3 8%
Student > Postgraduate 3 8%
Other 6 16%
Unknown 6 16%
Readers by discipline Count As %
Medicine and Dentistry 10 26%
Agricultural and Biological Sciences 8 21%
Biochemistry, Genetics and Molecular Biology 3 8%
Pharmacology, Toxicology and Pharmaceutical Science 2 5%
Computer Science 2 5%
Other 4 11%
Unknown 9 24%
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 28 January 2014.
All research outputs
#17,286,379
of 25,374,647 outputs
Outputs from Human Mutation
#2,348
of 2,982 outputs
Outputs of similar age
#131,482
of 207,878 outputs
Outputs of similar age from Human Mutation
#15
of 22 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,982 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 15th percentile – i.e., 15% 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 207,878 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.