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Original Article
Infection
In-hospital mortality prediction using frailty scale and severity score in elderly patients with severe COVID-19
Yong Sub Na, Jin Hyoung Kim, Moon Seong Baek, Won-Young Kim, Ae-Rin Baek, Bo young Lee, Gil Myeong Seong, Song-I Lee
Acute Crit Care. 2022;37(3):303-311.   Published online July 5, 2022
DOI: https://doi.org/10.4266/acc.2022.00017
  • 3,685 View
  • 213 Download
  • 5 Web of Science
  • 6 Crossref
AbstractAbstract PDF
Background
Elderly patients with coronavirus disease 2019 (COVID-19) have a high disease severity and mortality. However, the use of the frailty scale and severity score to predict in-hospital mortality in the elderly is not well established. Therefore, in this study, we investigated the use of these scores in COVID-19 cases in the elderly.
Methods
This multicenter retrospective study included severe COVID-19 patients admitted to seven hospitals in Republic of Korea from February 2020 to February 2021. We evaluated patients’ Acute Physiology and Chronic Health Evaluation (APACHE) II score; confusion, urea nitrogen, respiratory rate, blood pressure, 65 years of age and older (CURB-65) score; modified early warning score (MEWS); Sequential Organ Failure Assessment (SOFA) score; clinical frailty scale (CFS) score; and Charlson comorbidity index (CCI). We evaluated the predictive value using receiver operating characteristic (ROC) curve analysis.
Results
The study included 318 elderly patients with severe COVID-19 of whom 237 (74.5%) were survivors and 81 (25.5%) were non-survivors. The non-survivor group was older and had more comorbidities than the survivor group. The CFS, CCI, APACHE II, SOFA, CURB-65, and MEWS scores were higher in the non-survivor group than in the survivor group. When analyzed using the ROC curve, SOFA score showed the best performance in predicting the prognosis of elderly patients (area under the curve=0.766, P<0.001). CFS and SOFA scores were associated with in-hospital mortality in the multivariate analysis.
Conclusions
The SOFA score is an efficient tool for assessing in-hospital mortality in elderly patients with severe COVID-19.

Citations

Citations to this article as recorded by  
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Review Article
Rapid response system
Rapid response systems in Korea
Bo Young Lee, Sang-Bum Hong
Acute Crit Care. 2019;34(2):108-116.   Published online May 31, 2019
DOI: https://doi.org/10.4266/acc.2019.00535
  • 11,766 View
  • 394 Download
  • 21 Web of Science
  • 22 Crossref
AbstractAbstract PDF
The inpatient treatment process is becoming more and more complicated with advanced treatments, aging of the patient population, and multiple comorbidities. During the process, patients often experience unexpected deterioration, about half of which might be preventable. Early identification of patient deterioration and the proper response are priorities in most healthcare facilities. A rapid response system (RRS) is a safety net to identify antecedents of these adverse events and to respond in a timely manner. The RRS has become an essential part of the medical system worldwide, supported by all major quality improvement organizations. An RRS consists of a trigger system and response team and needs constant assessment and process improvement. Although the effectiveness and cost-benefit of RRS remain controversial, according to previous studies, it may be beneficial by decreasing in-hospital cardiac arrest and mortality. Since the first implementation of RRS in Korea in 2008, it has been developed in over 15 medical centers and continues to expand. Recent accreditation standards and an RRS pilot program by the Korean government will promote the proliferation of RRSs in Korea.

Citations

Citations to this article as recorded by  
  • Association between the timing of ICU admission and mortality in patients with hospital-onset sepsis: a nationwide prospective cohort study
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    Journal of Intensive Care.2023;[Epub]     CrossRef
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    BMC Emergency Medicine.2022;[Epub]     CrossRef
  • Mortality of patients with hospital-onset sepsis in hospitals with all-day and non-all-day rapid response teams: a prospective nationwide multicenter cohort study
    Dong-gon Hyun, Su Yeon Lee, Jee Hwan Ahn, Jin Won Huh, Sang-Bum Hong, Younsuck Koh, Chae-Man Lim, Dong Kyu Oh, Gee Young Suh, Kyeongman Jeon, Ryoung-Eun Ko, Young-Jae Cho, Yeon Joo Lee, Sung Yoon Lim, Sunghoon Park, Jeongwon Heo, Jae-myeong Lee, Kyung Cha
    Critical Care.2022;[Epub]     CrossRef
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    Byung Ju Kang, Sang-Bum Hong, Kyeongman Jeon, Sang-Min Lee, Dong Hyun Lee, Jae Young Moon, Yeon Joo Lee, Jung Soo Kim, Jisoo Park, Jong-Joon Ahn
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  • Impact of hospitalization duration before medical emergency team activation: A retrospective cohort study
    Jinmi Lee, Yujung Shin, Eunjoo Choi, Sunhui Choi, Jeongsuk Son, Youn Kyung Jung, Sang-Bum Hong, Tai-Heng Chen
    PLOS ONE.2021; 16(2): e0247066.     CrossRef
  • A multicentre validation study of the deep learning-based early warning score for predicting in-hospital cardiac arrest in patients admitted to general wards
    Yeon Joo Lee, Kyung-Jae Cho, Oyeon Kwon, Hyunho Park, Yeha Lee, Joon-Myoung Kwon, Jinsik Park, Jung Soo Kim, Man-Jong Lee, Ah Jin Kim, Ryoung-Eun Ko, Kyeongman Jeon, You Hwan Jo
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    Sang Hyuk Kim, Ji Young Hong, Youlim Kim
    Journal of Korean Medical Science.2021;[Epub]     CrossRef
  • Predicting severe outcomes using national early warning score (NEWS) in patients identified by a rapid response system: a retrospective cohort study
    Sang Hyuk Kim, Hye Suk Choi, Eun Suk Jin, Hayoung Choi, Hyun Lee, Sang-Hwa Lee, Chang Youl Lee, Myung Goo Lee, Youlim Kim
    Scientific Reports.2021;[Epub]     CrossRef
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    Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine.2021;[Epub]     CrossRef
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ACC : Acute and Critical Care