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The role of novel biomarkers in predicting diabetic nephropathy: a review

Overview of attention for article published in International Journal of Nephrology and Renovascular Disease, August 2017
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About this Attention Score

  • Among the highest-scoring outputs from this source (#48 of 144)
  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
2 tweeters
video
1 video uploader

Citations

dimensions_citation
20 Dimensions

Readers on

mendeley
84 Mendeley
Title
The role of novel biomarkers in predicting diabetic nephropathy: a review
Published in
International Journal of Nephrology and Renovascular Disease, August 2017
DOI 10.2147/ijnrd.s143186
Pubmed ID
Authors

Uwaezuoke, Samuel, Samuel N Uwaezuoke

Abstract

Diabetic nephropathy (DN) is one of the microvascular complications of the kidney arising commonly from type 1 diabetes mellitus (T1DM), and occasionally from type 2 diabetes mellitus (T2DM). Microalbuminuria serves as an early indicator of DN risk and a predictor of its progression as well as cardiovascular disease risk in both T1DM and T2DM. Although microalbuminuria remains the gold standard for early detection of DN, it is not a sufficiently accurate predictor of DN risk due to some limitations. Thus, there is a paradigm shift to novel biomarkers which would help to predict DN risk early enough and possibly prevent the occurrence of end-stage kidney disease. These new biomarkers have been broadly classified into glomerular biomarkers, tubular biomarkers, biomarkers of inflammation, biomarkers of oxidative stress, and miscellaneous biomarkers which also include podocyte biomarkers, some of which are also considered as tubular and glomerular biomarkers. Although they are potentially useful for the evaluation of DN, current data still preclude the routine clinical use of majority of them. However, their validation using high-quality and large longitudinal studies is of paramount importance, as well as the subsequent development of a biomarker panel which can reliably predict and evaluate this renal microvascular disease. This paper aims to review the predictive role of these biomarkers in the evaluation of DN.

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 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 84 100%

Demographic breakdown

Readers by professional status Count As %
Student > Postgraduate 14 17%
Student > Master 14 17%
Student > Bachelor 8 10%
Student > Ph. D. Student 8 10%
Researcher 8 10%
Other 17 20%
Unknown 15 18%
Readers by discipline Count As %
Medicine and Dentistry 33 39%
Biochemistry, Genetics and Molecular Biology 8 10%
Agricultural and Biological Sciences 7 8%
Pharmacology, Toxicology and Pharmaceutical Science 6 7%
Nursing and Health Professions 3 4%
Other 9 11%
Unknown 18 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 18 May 2018.
All research outputs
#7,474,207
of 12,961,138 outputs
Outputs from International Journal of Nephrology and Renovascular Disease
#48
of 144 outputs
Outputs of similar age
#130,066
of 265,330 outputs
Outputs of similar age from International Journal of Nephrology and Renovascular Disease
#3
of 4 outputs
Altmetric has tracked 12,961,138 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 144 research outputs from this source. They receive a mean Attention Score of 2.1. This one has gotten more attention than average, scoring higher than 57% of its peers.
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 265,330 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one.