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Biomarkers for diagnosis of sepsis in patients with systemic inflammatory response syndrome: a systematic review and meta-analysis

Overview of attention for article published in SpringerPlus, December 2016
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2 tweeters


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131 Mendeley
Biomarkers for diagnosis of sepsis in patients with systemic inflammatory response syndrome: a systematic review and meta-analysis
Published in
SpringerPlus, December 2016
DOI 10.1186/s40064-016-3591-5
Pubmed ID

Yong Liu, Jun-huan Hou, Qing Li, Kui-jun Chen, Shu-Nan Wang, Jian-min Wang


Sepsis is one of the most common diseases that seriously threaten human health. Although a large number of markers related to sepsis have been reported in the last two decades, the diagnostic accuracy of these biomarkers remains unclear due to the lack of similar baselines among studies. Therefore, we conducted a large systematic review and meta-analysis to evaluate the diagnostic value of biomarkers from studies that included non-infectious systemic inflammatory response syndrome patients as a control group. We searched Medline, Embase and the reference lists of identified studies beginning in April 2014. The last retrieval was updated in September 2016. Ultimately, 86 articles fulfilled the inclusion criteria. Sixty biomarkers and 10,438 subjects entered the final analysis. The areas under the receiver operating characteristic curves for the 7 most common biomarkers, including procalcitonin, C-reactive protein, interleukin 6, soluble triggering receptor expressed on myeloid cells-1, presepsin, lipopolysaccharide binding protein and CD64, were 0.85, 0.77, 0.79, 0.85, 0.88, 0.71 and 0.96, respectively. The remaining 53 biomarkers exhibited obvious variances in diagnostic value and methodological quality. Although some biomarkers displayed moderate or above moderate diagnostic value for sepsis, the limitations of the methodological quality and sample size may weaken these findings. Currently, we still lack an ideal biomarker to aid in the diagnosis of sepsis. In the future, biomarkers with better diagnostic value as well as a combined diagnosis using multiple biomarkers are expected to solve the challenge of the diagnosis of sepsis.

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

Geographical breakdown

Country Count As %
Mexico 1 <1%
Unknown 130 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 14%
Researcher 18 14%
Student > Bachelor 15 11%
Student > Master 12 9%
Student > Doctoral Student 9 7%
Other 28 21%
Unknown 31 24%
Readers by discipline Count As %
Medicine and Dentistry 52 40%
Biochemistry, Genetics and Molecular Biology 8 6%
Engineering 6 5%
Agricultural and Biological Sciences 4 3%
Nursing and Health Professions 3 2%
Other 19 15%
Unknown 39 30%

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 24 August 2019.
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Outputs of similar age
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Outputs of similar age from SpringerPlus
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Altmetric has tracked 21,094,310 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,842 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 55% of its peers.
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