↓ Skip to main content

Revisiting the links between glycaemia, diabetes and cardiovascular disease

Overview of attention for article published in Diabetologia, January 2013
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
137 Dimensions

Readers on

mendeley
163 Mendeley
citeulike
1 CiteULike
Title
Revisiting the links between glycaemia, diabetes and cardiovascular disease
Published in
Diabetologia, January 2013
DOI 10.1007/s00125-012-2817-5
Pubmed ID
Authors

N. Sattar

Abstract

Whilst the interplay between type 2 diabetes and cardiovascular disease (CVD) has been recognised for many years, recent analyses of existing studies have helped refine several aspects of this relationship with relevance to clinical practice. First, recent data demonstrate that fasting glucose is not linearly related to CVD risk in those without diabetes; rather, risk levels escalate (modestly at first) only beyond specific glucose thresholds. Consequently, glucose-based measures may not necessarily enhance CVD risk prediction in those without diabetes. Second, other data confirm that new-onset diabetes is not a post-myocardial infarction 'risk equivalent' state and that, on average, several years of diabetes duration is needed to attain this level of risk. Third, meta-analyses and systemic reviews have confirmed that diabetes increases CVD risk by around twofold on average and this risk is subject to wide variation, being lowest in those newly diagnosed and highest in those with existing vascular disease, proteinuria or renal disease. Fourth, meta-analyses of major glucose-lowering trials suggest that, whilst glucose-lowering lessens vascular risk, risk reduction arising from statins and blood pressure-lowering is greater. Fifth, statins increase diabetes risk, albeit modestly, adding to the emerging concept that some agents that primarily target CVD risk may be diabetogenic, and vice versa. Finally, arising in part from the latter observation, as well as an understanding that CVD and diabetes risk overlap in some individuals but not others, the case for combined CVD/diabetes risk screening (generally using non-fasting lipids and HbA1c), has gained strength.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 163 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 <1%
South Africa 1 <1%
United Kingdom 1 <1%
Mexico 1 <1%
Thailand 1 <1%
Unknown 158 97%

Demographic breakdown

Readers by professional status Count As %
Other 20 12%
Student > Master 18 11%
Researcher 17 10%
Student > Ph. D. Student 17 10%
Student > Bachelor 14 9%
Other 46 28%
Unknown 31 19%
Readers by discipline Count As %
Medicine and Dentistry 86 53%
Nursing and Health Professions 7 4%
Biochemistry, Genetics and Molecular Biology 6 4%
Agricultural and Biological Sciences 6 4%
Pharmacology, Toxicology and Pharmaceutical Science 5 3%
Other 18 11%
Unknown 35 21%
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 26 April 2013.
All research outputs
#18,337,420
of 22,708,120 outputs
Outputs from Diabetologia
#4,669
of 5,029 outputs
Outputs of similar age
#218,632
of 281,802 outputs
Outputs of similar age from Diabetologia
#36
of 50 outputs
Altmetric has tracked 22,708,120 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 5,029 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.6. This one is in the 3rd percentile – i.e., 3% 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 281,802 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 50 others from the same source and published within six weeks on either side of this one. This one is in the 2nd percentile – i.e., 2% of its contemporaries scored the same or lower than it.