• TheScientificWorldJournal · Jan 2014

    Comparative Study

    Comparison of risks factors for unplanned ICU transfer after ED admission in patients with infections and those without infections.

    • Jeffrey Che-Hung Tsai, Ching-Wan Cheng, Shao-Jen Weng, Chin-Yin Huang, David Hung-Tsang Yen, and Hsiu-Ling Chen.
    • Department of Emergency Medicine, China Medical University Hospital, No. 2 Yude Road, North District, Taichung City 404, Taiwan ; School of Medicine, College of Medicine, China Medical University, Taichung 404, Taiwan ; Department of Industrial Engineering & Enterprise Information, Tunghai University, Taichung 407, Taiwan.
    • ScientificWorldJournal. 2014 Jan 1;2014:102929.

    BackgroundThe objectives of this study were to compare the risk factors for unplanned intensive care unit (ICU) transfer after emergency department (ED) admission in patients with infections and those without infections and to explore the feasibility of using risk stratification tools for sepsis to derive a prediction system for such unplanned transfer.MethodsThe ICU transfer group included 313 patients, while the control group included 736 patients randomly selected from those who were not transferred to the ICU. Candidate variables were analyzed for association with unplanned ICU transfer in the 1049 study patients.ResultsTwenty-four variables were associated with unplanned ICU transfer. Sixteen (66.7%) of these variables displayed association in patients with infections and those without infections. These common risk factors included specific comorbidities, physiological responses, organ dysfunctions, and other serious symptoms and signs. Several common risk factors were statistically independent.ConclusionsThe risk factors for unplanned ICU transfer in patients with infections were comparable to those in patients without infections. The risk factors for unplanned ICU transfer included variables from multiple dimensions that could be organized according to the PIRO (predisposition, insult/infection, physiological response, and organ dysfunction) model, providing the basis for the development of a predictive system.

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