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Therapies to Preserve β-Cell Function in Type 1 Diabetes

Overview of attention for article published in Drugs, December 2015
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Title
Therapies to Preserve β-Cell Function in Type 1 Diabetes
Published in
Drugs, December 2015
DOI 10.1007/s40265-015-0511-x
Pubmed ID
Authors

Johnny Ludvigsson

Abstract

In spite of modern techniques, the burden for patients with type 1 diabetes mellitus will not disappear, and type 1 diabetes will remain a life-threatening disease causing severe complications and increased mortality. We have to learn of ways to stop the destructive process, preserve residual insulin secretion or even improve the disease via β-cell regeneration. This will give a milder disease, a more stable metabolism, simpler treatment and perhaps even cure. Therapies based on single drugs have not shown sufficient efficacy; however, there are several treatments with encouraging efficacy and no apparent, or rather mild, adverse events. As the disease process is heterogeneous, treatments have to be chosen to fit relevant subgroups of patients, and step by step efficacy can possibly be improved by the use of combination therapies. Thus immunosuppressive therapies like anti-CD3 and anti-CD20 monoclonal antibodies might be combined with fusion proteins such as etanercept [tumor necrosis factor (TNF)-α inhibitor] and/or abatacept (CTLA4-Ig) early after onset to stop the destructive process, supported by β-cell protective agents. The effect may be prolonged by using autoantigen therapy [glutamate decarboxylase (GAD) proinsulin], and by adding agents facilitating β-cell regeneration [e.g. glucagon-like peptide-1 (GLP-1)] there should be a good chance to make the disease milder, perhaps leading to cure in some patients.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 68 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 16%
Student > Bachelor 9 13%
Student > Master 8 12%
Student > Doctoral Student 4 6%
Student > Ph. D. Student 4 6%
Other 10 15%
Unknown 22 32%
Readers by discipline Count As %
Medicine and Dentistry 18 26%
Nursing and Health Professions 7 10%
Biochemistry, Genetics and Molecular Biology 5 7%
Agricultural and Biological Sciences 5 7%
Immunology and Microbiology 5 7%
Other 4 6%
Unknown 24 35%
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 21 February 2016.
All research outputs
#18,443,697
of 22,851,489 outputs
Outputs from Drugs
#2,982
of 3,255 outputs
Outputs of similar age
#280,632
of 388,718 outputs
Outputs of similar age from Drugs
#37
of 41 outputs
Altmetric has tracked 22,851,489 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,255 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one is in the 3rd percentile – i.e., 3% of its peers scored the same or lower than it.
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We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.