In PloS one ; h5-index 176.0
BACKGROUND : Although scoring and machine learning methods have been developed to predict patient deterioration, bedside assessment by nurses should not be overlooked. This study aimed to evaluate the performance of subjective bedside assessment of the patient by the rapid response team (RRT) nurses in predicting short-term patient deterioration.
METHODS : Patients noticed by RRT nurses based on the vital sign instability, abnormal laboratory results, and direct contact via phone between November 1, 2016, and December 12, 2017, were included. Five RRT nurses visited the patients according to their shifts and assessed the possibility of patient deterioration. Patient acuity rating (PAR), a scale of 1-7, was used as the tool of bedside assessment. Other scores, including the modified early warning score, VitalPAC early warning score, standardised early warning score, and cardiac arrest risk triage, were calculated afterwards. The performance of these scores in predicting mortality and/or intensive care unit admission within 1 day was compared by calculating the area under the receiver operating curve.
RESULTS : A total of 1,426 patients were included in the study, of which 258 (18.1%) died or were admitted to the intensive care unit within 1 day. The area under the receiver operating curve of PAR was 0.87 (95% confidence interval [CI] 0.84-0.89), which was higher than those of modified early warning score (0.66, 95% CI 0.62-0.70), VitalPAC early warning score (0.69, 95% CI 0.66-0.73), standardised early warning score (0.67, 95% CI 0.63-0.70) and cardiac arrest risk triage (0.63, 95% CI 0.59-0.66) (P<0.001).
CONCLUSIONS : PAR assessed by RRT nurses can be a useful tool for assessing short-term patient prognosis in the RRT setting.
Kim Hyung-Jun, Min Hyun-Ju, Lee Dong-Seon, Choi Yun-Young, Yoon Miae, Lee Da-Yun, Song In-Ae, Cho Jun Yeun, Park Jong Sun, Cho Young-Jae, Jo You-Hwan, Yoon Ho Il, Lee Jae Ho, Lee Choon-Taek, Lee Yeon Joo