↓ Skip to main content

Plasma endostatin may improve acute kidney injury risk prediction in critically ill patients

Overview of attention for article published in Annals of Intensive Care, January 2016
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

twitter
4 X users

Citations

dimensions_citation
28 Dimensions

Readers on

mendeley
40 Mendeley
Title
Plasma endostatin may improve acute kidney injury risk prediction in critically ill patients
Published in
Annals of Intensive Care, January 2016
DOI 10.1186/s13613-016-0108-x
Pubmed ID
Authors

Johan Mårtensson, Niklas Jonsson, Neil J. Glassford, Max Bell, Claes-Roland Martling, Rinaldo Bellomo, Anders Larsson

Abstract

Breakdown of renal endothelial, tubular and glomerular matrix collagen plays a major role in acute kidney injury (AKI) development. Such collagen breakdown releases endostatin into the circulation. The aim of this study was to compare the AKI predictive value of plasma endostatin with two previously suggested biomarkers of AKI, cystatin C and neutrophil gelatinase-associated lipocalin (NGAL). We studied 93 patients without kidney disease who had a first plasma sample obtained within 48 h of ICU admission. We identified risk factors for AKI within the population and designed a predictive model. The individual ability and net contribution of endostatin, cystatin C and NGAL to predict AKI were evaluated by the area under the receiver operating characteristics curve (AUC), likelihood-ratio test, net reclassification improvement (NRI) and integrated discrimination improvement (IDI). In total, 21 (23 %) patients experienced AKI within 72 h. A three-parameter model (age, illness severity score and early oliguria) predicted AKI with an AUC of 0.759 (95 % CI 0.646-0.872). Adding endostatin to the predictive model significantly (P = 0.04) improved the AUC to 0.839 (95 % CI 0.752-0.925). In addition, endostatin significantly improved risk prediction using the likelihood-ratio test (P = 0.005), NRI analysis (0.27; P = 0.04) and IDI analysis (0.07; P = 0.04). In contrast, adding cystatin C or NGAL to the three-parameter model did not improve risk prediction in any of the four analyses. In this cohort of critically ill patients, plasma endostatin improved AKI prediction based on clinical risk factors, while cystatin C and NGAL did not.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users 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 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Denmark 1 3%
Italy 1 3%
Unknown 37 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 20%
Student > Master 6 15%
Researcher 6 15%
Student > Postgraduate 5 13%
Student > Bachelor 4 10%
Other 6 15%
Unknown 5 13%
Readers by discipline Count As %
Medicine and Dentistry 24 60%
Biochemistry, Genetics and Molecular Biology 3 8%
Agricultural and Biological Sciences 2 5%
Computer Science 1 3%
Nursing and Health Professions 1 3%
Other 2 5%
Unknown 7 18%
Attention Score in Context

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 18 January 2016.
All research outputs
#12,823,738
of 22,840,638 outputs
Outputs from Annals of Intensive Care
#668
of 1,043 outputs
Outputs of similar age
#177,811
of 395,522 outputs
Outputs of similar age from Annals of Intensive Care
#13
of 31 outputs
Altmetric has tracked 22,840,638 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,043 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.7. This one is in the 35th percentile – i.e., 35% 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 395,522 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 54% of its contemporaries.
We're also able to compare this research output to 31 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 58% of its contemporaries.