A multicentre validation study of the deep earning-based early warning score for predicting in-hospital cardiac arrest in patients admitted to general wards

RESUSCITATION

卷:163

Article

Lee, Yeon Joo¹  Cho, Kyung-Jae²  Kwon, Oyeon²  Park, Hyunho²  Lee, Yeha²  Kwon, Joon-Myoung³  Park, Jinsik⁴  Kim, Jung Soo⁵  Lee, Man-Jong⁵  Kim, Ah Jin⁵  Ko, Ryoung-Eun⁶  Jeon, Kyeongman^6,7  Jo, You Hwan^8,9 

[1] Seoul Natl Univ, Div Pulm & Crit Care Med, Bundang Hosp, Gyeonggi Do, South Korea

[2] VUNO, Seoul, South Korea

[3] Mediplex Sejong Hosp, Dept Crit Care & Emergency Med, Incheon, South Korea

[4] Mediplex Sejong Hosp, Cardiovasc Ctr, Div Cardiol, Incheon, South Korea

[5] Inha Coll Med, Dept Hosp Med, Div Crit Care Med, Incheon, South Korea

[6] Sungkyunkwan Univ, Samsung Med Ctr, Dept Crit Care Med, Sch Med, Seoul, South Korea

[7] Sungkyunkwan Univ, Samsung Med Ctr, Dept Med, Div Pulm & Crit Care Med,Sch Med, Seoul, South Korea

[8] Seoul Natl Univ, Dept Emergency Med, Bundang Hosp, 82,Gumi Ro 173 Beon Gil, Seongnam Si 13620, Gyeonggi Do, South Korea

[9] Seoul Natl Univ, Dept Emergency Med, Coll Med, Seoul, South Korea

关键词: Cardiac arrest;    Prediction;    Deep learning;    Early warning score;    Artificial intelligence;    Rapid response system;   

DOI  :  10.1016/j.resuscitation.2021.04.013

来源: Elsevier

【 摘 要 】

Background: The recently developed deep learning (DL)-based early warning score (DEWS) has shown potential in predicting deteriorating patients. We aimed to validate DEWS in multiple centres and compare the prediction, alarming and timeliness performance with the modified early warning score (MEWS) to identify patients at risk for in-hospital cardiac arrest (IHCA). Method/research design: This retrospective cohort study included adult patients admitted to the general wards of five hospitals during a 12-month period. The occurrence of IHCA within 24 h of vital sign observation was the outcome of interest. We assessed the discrimination using the area under the receiver operating characteristic curve (AUROC). Results: The study population consists of 173,368 patients (224 IHCAs). The predictive performance of DEWS was superior to that of MEWS in both the internal (AUROC: 0.860 vs. 0.754, respectively) and external (AUROC: 0.905 vs. 0.785, respectively) validation cohorts. At the same specificity, DEWS had a higher sensitivity than MEWS, and at the same sensitivity, DEWS reduced the mean alarm count by nearly half of MEWS. Additionally, DEWS was able to predict more IHCA patients in the 24 - 0.5 h before the outcome, and DEWS was reasonably calibrated. Conclusion: Our study showed that DEWS was superior to MEWS in three key aspects (IHCA predictive, alarming, and timeliness performance). This study demonstrates the potential of DEWS as an effective, efficient screening tool in rapid response systems (RRSs) to identify high-risk patients.

【 授权许可】

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