Early Systemic Inflammatory Response Syndrome Duration Predicts Infected Pancreatic Necrosis View Full Text


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Article Info

DATE

2019-03-19

AUTHORS

Chaochao Tan, Li Yang, Fengxia Shi, Jiliang Hu, Xingwen Zhang, Yupeng Wang, Zhonghua Deng, Jiang Li, Hao Yuan, Ting Shi, Cunyan Li, Yan Xiao, Ya Peng, Wen Xu, Ying Huang

ABSTRACT

BACKGROUND AND PURPOSE: Systemic inflammatory response syndrome (SIRS) was considered to play an important role in the progress of acute pancreatitis, but its specific relation with infected pancreatic necrosis remains largely unclear. We aimed to investigate the correlation between SIRS duration and infected pancreatic necrosis, and its application in prediction of infected pancreatic necrosis. METHODS: A prospective observational cohort study of 2130 patients with acute pancreatitis from 2012 to 2017. The SIRS duration at the first week was registered daily, and demographic, radiology, and all clinical laboratory data were prospectively collected and retrospectively reviewed. RESULTS: A significant upward tendency of infected pancreatic necrosis incidence was observed with increased SIRS duration. In multivariate logistic regression, SIRS duration (odds ratio, 1.305; 95% CI, 1.161-1.468) was independently associated with infected pancreatic necrosis. ROC analysis demonstrated that the areas under curves of SIRS duration for predicting persistent multi-organ failure, pancreatic infection, and mortality were 0.97 (95% CI, 0.96-0.98), 0.92 (95% CI, 0.91-0.94), and 0.86 (95% CI, 0.83-0.90), respectively, which were comparable to, or even greater than, the area under curves of APACHE II and CT severity index scores. CONCLUSIONS: Early SIRS duration was strongly associated with infected pancreatic necrosis and could serve as an easy bedside indicator to predict pancreatic infection. More... »

PAGES

1-8

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s11605-019-04149-5

    DOI

    http://dx.doi.org/10.1007/s11605-019-04149-5

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1112871170

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30891659


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    RDF/XML is a standard XML format for linked data.

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