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A risk scoring model based on vital signs and laboratory data predicting transfer to the intensive care unit of patients admitted to gastroenterology wards

Authors
Kim, Won-YoungLee, JinmiJung, Youn KyungLee, Ju-RyKim, Hwa JungHuh, Jin WonLim, Chae-ManKoh, YounsuckHong, Sang-Bum
Issue Date
Aug-2017
Publisher
W B SAUNDERS CO-ELSEVIER INC
Keywords
Predictive scores; Vital signs; Laboratory scores; Intensive care units; Gastroenterology
Citation
JOURNAL OF CRITICAL CARE, v.40, pp 213 - 217
Pages
5
Journal Title
JOURNAL OF CRITICAL CARE
Volume
40
Start Page
213
End Page
217
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/69440
DOI
10.1016/j.jcrc.2017.04.024
ISSN
0883-9441
1557-8615
Abstract
Purpose: To compare the ability of a score based on vital signs and laboratory data with that of the modified early warning score (MEWS) to predict ICU transfer of patients with gastrointestinal disorders. Materials and methods: Consecutive events triggering medical emergency team activation in adult patients admitted to the gastroenterology wards of the Asan Medical Center were reviewed. Binary logistic regression was used to identify factors predicting transfer to the ICU. Gastrointestinal early warning score (EWS-GI) was calculated as the sum of simplified regression weights (SRW). Results: Of the 1219 included patients, 468 (38%) were transferred to the ICU. Multivariate analysis identified heart rate >= 105 bpm (SRW 1), respiratory rate >= 26 bpm (SRW2), ACDU (Alert, Confused, Drowsy, Unresponsive) score >= 1 (SRW 2), SpO(2)/FiO(2) ratio < 240 (SRW 2), creatinine >= 2.0 mg/dL (SRW 2), total bilirubin >= 9.0 mg/dL (SRW 2), prothrombin time/international normalized ratio (INR) >= 1.5 (SRW 2), and lactate >= 3.0 mmol/L (SRW 2) for inclusion in EWS-GI. The area under the receiver operating characteristic curve of the EWS-GI was larger than that of MEWS (0.76 vs. 0.64; P < 0.001). Conclusions: EWS-GI may predict ICU transfer among patients admitted to gastroenterology wards. The EWS-GI should be prospectively validated. (C) 2017 Elsevier Inc. All rights reserved.
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