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Models predicting the growth response to growth hormone treatment in short children independent of GH status, birth size and gestational age

Overview of attention for article published in BMC Medical Informatics and Decision Making, December 2007
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Title
Models predicting the growth response to growth hormone treatment in short children independent of GH status, birth size and gestational age
Published in
BMC Medical Informatics and Decision Making, December 2007
DOI 10.1186/1472-6947-7-40
Pubmed ID
Authors

Jovanna Dahlgren, Berit Kriström, Aimon Niklasson, Andreas FM Nierop, Sten Rosberg, Kerstin Albertsson-Wikland

Abstract

Mathematical models can be used to predict individual growth responses to growth hormone (GH) therapy. The aim of this study was to construct and validate high-precision models to predict the growth response to GH treatment of short children, independent of their GH status, birth size and gestational age. As the GH doses are included, these models can be used to individualize treatment.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
New Zealand 1 4%
Unknown 23 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 25%
Student > Bachelor 4 17%
Researcher 4 17%
Student > Master 4 17%
Professor 2 8%
Other 4 17%
Readers by discipline Count As %
Medicine and Dentistry 17 71%
Engineering 2 8%
Agricultural and Biological Sciences 2 8%
Computer Science 1 4%
Business, Management and Accounting 1 4%
Other 1 4%

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 15 March 2014.
All research outputs
#3,102,334
of 4,506,837 outputs
Outputs from BMC Medical Informatics and Decision Making
#644
of 754 outputs
Outputs of similar age
#74,238
of 107,376 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#27
of 29 outputs
Altmetric has tracked 4,506,837 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 754 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 4th percentile – i.e., 4% 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 107,376 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 29 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.