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Usefulness of plasminogen activator inhibitor-1 as a predictive marker of mortality in sepsis

Overview of attention for article published in Journal of Intensive Care, July 2017
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2 tweeters

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26 Mendeley
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Title
Usefulness of plasminogen activator inhibitor-1 as a predictive marker of mortality in sepsis
Published in
Journal of Intensive Care, July 2017
DOI 10.1186/s40560-017-0238-8
Pubmed ID
Authors

Kota Hoshino, Taisuke Kitamura, Yoshihiko Nakamura, Yuhei Irie, Norihiko Matsumoto, Yasumasa Kawano, Hiroyasu Ishikura

Abstract

Sepsis is one of the most significant causes of mortality in intensive care units. It indicates crosstalk between inflammation and coagulation. In this study, we aimed to identify prognostic markers among sepsis biomarkers and coagulation/fibrinolysis markers. Patients with sepsis according to the Sepsis-3 criteria were enrolled from January 2013 to September 2015. Univariate and multivariate logistic regression analyses were performed to identify an independent predictive marker of 28-day mortality among sepsis biomarkers and coagulation/fibrinolysis markers on ICU admission. Receiver operating characteristic analysis was performed; the optimal cutoff value of 28-day mortality was calculated using the predictive marker. Patients were classified into two groups according to the cutoff level of the predictive marker. Patient characteristics were compared between the groups. A total of 186 patients were enrolled in this study; the 28-day mortality was 19.4% (36/186). PAI-1 was identified as the only independent predictive marker of 28-day mortality by univariate and multivariate logistic regression. The area under the curve was 0.72; the optimal cutoff level was 83 ng/ml (sensitivity, 75%; specificity, 61%). Patients were classified into a higher group (PAI-1 level ≥83 ng/ml; n = 85) and a lower group (PAI-1 level <83 ng/ml; n = 101). All disseminated intravascular coagulation (DIC) scores and Sequential Organ Failure Assessment score were significantly higher in the higher group than in the lower group. PAI-1 can predict prognosis in sepsis patients. PAI-1 reflects DIC with suppressed fibrinolysis and organ failure, with microthrombi leading to microcirculatory dysfunction.

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

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 19%
Student > Master 3 12%
Student > Ph. D. Student 3 12%
Student > Doctoral Student 2 8%
Student > Bachelor 2 8%
Other 7 27%
Unknown 4 15%
Readers by discipline Count As %
Medicine and Dentistry 16 62%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Agricultural and Biological Sciences 1 4%
Biochemistry, Genetics and Molecular Biology 1 4%
Computer Science 1 4%
Other 1 4%
Unknown 5 19%

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 12 July 2017.
All research outputs
#7,108,264
of 11,459,905 outputs
Outputs from Journal of Intensive Care
#173
of 235 outputs
Outputs of similar age
#147,287
of 259,185 outputs
Outputs of similar age from Journal of Intensive Care
#16
of 27 outputs
Altmetric has tracked 11,459,905 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 235 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one is in the 25th percentile – i.e., 25% 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 259,185 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.