Unknown

Dataset Information

0

Evaluation of the SpO2/FiO2 ratio as a predictor of intensive care unit transfers in respiratory ward patients for whom the rapid response system has been activated.


ABSTRACT: Efforts to detect patient deterioration early have led to the development of early warning score (EWS) models. However, these models are disease-nonspecific and have shown variable accuracy in predicting unexpected critical events. Here, we propose a simpler and more accurate method for predicting risk in respiratory ward patients. This retrospective study analyzed adult patients who were admitted to the respiratory ward and detected using the rapid response system (RRS). Study outcomes included transfer to the intensive care unit (ICU) within 24 hours after RRS activation and in-hospital mortality. Prediction power of existing EWS models including Modified EWS (MEWS), National EWS (NEWS), and VitalPAC EWS (ViEWS) and SpO2/FiO2 (SF) ratio were compared to each other using the area under the receiver operating characteristic curve (AUROC). Overall, 456 patients were included; median age was 75 years (interquartile range: 65-80) and 344 (75.4%) were male. Seventy-three (16.0%) and 79 (17.3%) patients were transferred to the ICU and died. The SF ratio displayed better or comparable predictive accuracy for unexpected ICU transfer (AUROC: 0.744) compared to MEWS (0.744 vs. 0.653, P = 0.03), NEWS (0.744 vs. 0.667, P = 0.04), and ViEWS (0.744 vs. 0.675, P = 0.06). For in-hospital mortality, although there was no statistical difference, the AUROC of the SF ratio (0.660) was higher than that of each of the preexisting EWS models. In comparison with the preexisting EWS models, the SF ratio showed better or comparable predictive accuracy for unexpected ICU transfers in the respiratory wards.

SUBMITTER: Kwack WG 

PROVIDER: S-EPMC6067747 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

altmetric image

Publications

Evaluation of the SpO2/FiO2 ratio as a predictor of intensive care unit transfers in respiratory ward patients for whom the rapid response system has been activated.

Kwack Won Gun WG   Lee Dong Seon DS   Min Hyunju H   Choi Yun Young YY   Yun Miae M   Kim Youlim Y   Lee Sang Hoon SH   Song Inae I   Park Jong Sun JS   Cho Young-Jae YJ   Jo You Hwan YH   Yoon Ho Il HI   Lee Jae Ho JH   Lee Choon-Taek CT   Lee Yeon Joo YJ  

PloS one 20180731 7


Efforts to detect patient deterioration early have led to the development of early warning score (EWS) models. However, these models are disease-nonspecific and have shown variable accuracy in predicting unexpected critical events. Here, we propose a simpler and more accurate method for predicting risk in respiratory ward patients. This retrospective study analyzed adult patients who were admitted to the respiratory ward and detected using the rapid response system (RRS). Study outcomes included  ...[more]

Similar Datasets

| S-EPMC7833145 | biostudies-literature
| S-EPMC4980543 | biostudies-literature
| S-EPMC8654817 | biostudies-literature