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ApreciseKUre: an approach of Precision Medicine in a Rare Disease

Overview of attention for article published in BMC Medical Informatics and Decision Making, April 2017
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2 tweeters

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13 Dimensions

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27 Mendeley
Title
ApreciseKUre: an approach of Precision Medicine in a Rare Disease
Published in
BMC Medical Informatics and Decision Making, April 2017
DOI 10.1186/s12911-017-0438-0
Pubmed ID
Authors

Ottavia Spiga, Vittoria Cicaloni, Andrea Bernini, Andrea Zatkova, Annalisa Santucci

Abstract

Alkaptonuria (AKU; OMIM:203500) is a classic Mendelian genetic disorder described by Garrod already in 1902. It causes urine to turn black upon exposure to air and also leads to ochronosis as well as early osteoarthritis. Our objective is the implementation of a Precision Medicine (PM) approach to AKU. We present here a novel ApreciseKUre database facilitating the collection, integration and analysis of patient data in order to create an AKU-dedicated "PM Ecosystem" in which genetic, biochemical and clinical resources can be shared among registered researchers. In order to exploit the ApreciseKUre database, we developed an analytic method based on Pearson's correlation coefficient and P value that generates as refreshable correlation matrix. A complete statistical analysis is obtained by associating every pair of parameters to examine the dependence between multiple variables at the same time. Employing this analytic approach, we showed that some clinically used biomarkers are not suitable as prognostic biomarkers in AKU for a more reliable patients' clinical monitoring. We believe this database could be a good starting point for the creation of a new clinical management tool in AKU, which will lead to the development of a deeper knowledge network on the disease and will advance its treatment. Moreover, our approach can serve as a personalization model paradigm for other inborn errors of metabolism or rare diseases in general.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 22%
Researcher 5 19%
Student > Bachelor 3 11%
Student > Doctoral Student 3 11%
Student > Ph. D. Student 3 11%
Other 3 11%
Unknown 4 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 15%
Pharmacology, Toxicology and Pharmaceutical Science 3 11%
Medicine and Dentistry 3 11%
Computer Science 3 11%
Engineering 2 7%
Other 7 26%
Unknown 5 19%

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 26 April 2017.
All research outputs
#5,489,659
of 9,730,393 outputs
Outputs from BMC Medical Informatics and Decision Making
#734
of 1,041 outputs
Outputs of similar age
#133,874
of 236,814 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#19
of 26 outputs
Altmetric has tracked 9,730,393 research outputs across all sources so far. This one is in the 26th percentile – i.e., 26% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,041 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 19th percentile – i.e., 19% 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 236,814 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.