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Chinese medicines in the treatment of experimental diabetic nephropathy

Overview of attention for article published in Chinese Medicine, February 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

twitter
3 tweeters
facebook
3 Facebook pages

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
14 Mendeley
citeulike
1 CiteULike
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Title
Chinese medicines in the treatment of experimental diabetic nephropathy
Published in
Chinese Medicine, February 2016
DOI 10.1186/s13020-016-0075-z
Pubmed ID
Authors

Jing-Yi Liu, Xiao-Xin Chen, Sydney Chi-Wai Tang, Stephen Cho-Wing Sze, Yi-Bin Feng, Kai-Fai Lee, Kalin Yan-Bo Zhang

Abstract

Diabetic nephropathy (DN) is a severe micro vascular complication accompanying diabetes mellitus that affects millions of people worldwide. End-stage renal disease occurs in nearly half of all DN patients, resulting in large medical costs and lost productivity. The course of DN progression is complicated, and effective and safe therapeutic strategies are desired. While the complex nature of DN renders medicines with a single therapeutic target less efficacious, Chinese medicine, with its holistic view targeting the whole system of the patient, has exhibited efficacy for DN management. This review aims to describe the experimental evidence for Chinese medicines in DN management, with an emphasis on the underlying mechanisms, and to discuss the combined use of herbs and drugs in DN treatment.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 21%
Professor 2 14%
Professor > Associate Professor 2 14%
Student > Bachelor 2 14%
Student > Postgraduate 2 14%
Other 1 7%
Unknown 2 14%
Readers by discipline Count As %
Medicine and Dentistry 5 36%
Nursing and Health Professions 1 7%
Biochemistry, Genetics and Molecular Biology 1 7%
Agricultural and Biological Sciences 1 7%
Immunology and Microbiology 1 7%
Other 1 7%
Unknown 4 29%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 07 October 2017.
All research outputs
#6,020,653
of 11,880,222 outputs
Outputs from Chinese Medicine
#61
of 266 outputs
Outputs of similar age
#105,363
of 291,896 outputs
Outputs of similar age from Chinese Medicine
#3
of 11 outputs
Altmetric has tracked 11,880,222 research outputs across all sources so far. This one is in the 49th percentile – i.e., 49% of other outputs scored the same or lower than it.
So far Altmetric has tracked 266 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 75% 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 291,896 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.