LUO Changbin 1,2 , CHENG Lingxia 1 , HUANG Wenbin 1 , LI Liang 1 , CAO Linghong 1 , XU Ping 1,2
  • 1. Emergency Department, Zigong Fourth People’s Hospital, Zigong, Sichuan 643000, P. R. China;
  • 2. Institute of Medical Big Data, Zigong Academy of Artificial Intelligence and Big Data for Medical Science, Zigong, Sichuan 643000, P. R. China;
XU Ping, Email: 58124453@qq.com
Acute heart failure; Composite Congestion Score; Acute Physiology and Chronic Health Assessment System Ⅱ; adverse events; predictive value
10.7507/1002-0179.202210165
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Objective  To explore the predictive value of Composite Congestion Score (CCS) in predicting adverse events within 180 days in patients with acute heart failure (AHF) in emergency intensive care unit (EICU). Methods  The patients with AHF who were admitted to EICU of Zigong Fourth People’s Hospital between January 1, 2018 and December 31, 2020 were included consecutively. The patients were followed up for 180 days, and were divided into poor prognosis group and good prognosis group according to whether there were adverse events. Logistic regression equation was used to screen independent risk factors for predicting adverse events in patients with AHF within 180 days after leaving EICU. To compare the discrimination, calibration and clinical usefulness of independent risk factors at EICU discharge and the Acute Physiology and Chronic Health Assessment SystemⅡ (APACHEⅡ) score at EICU admission to predict the occurrence of adverse events of AHF. Results  A total of 71 patients were included, including 32 patients with good prognosis and 39 patients with poor prognosis. Except for age, APACHEⅡscore at EICU admission and CCS score at EICU discharge (P<0.05), there was no significant difference in other indicators between the two groups (P>0.05). Logistic regression analysis showed that CCS score at EICU discharge [odds ratio (OR)=2.806, 95% confidence interval (CI) (1.428, 5.512), P=0.003], age [OR=1.086, 95%CI (1.017, 1.159), P=0.013] were independent risk factors for predicting death or returning to hospital within 180 days. Among them, the CCS score at EICU discharge combining with age had a positive improvement ability compared with the CCS score at EICU discharge, the age, and the APACHE Ⅱ score at EICU admission. The calibration curves of the four scoring methods for predicting adverse events within 180 days showed that the CCS score at EICU discharge had the highest calibration and the calibration of age was the lowest. The decision curve showed that the clinical usefulness of age, the CCS score at EICU discharge and the CCS score at EICU discharge combining with age was better than the APACHE Ⅱ score at EICU admission. Conclusions  The CCS score of patients with AHF at EICU discharge is closely related to adverse events within 180 days. The CCS score is designed based on clinical variables, simple and practical. The combination of age and the CCS score at EICU discharge will further enhance its clinical application value.

Citation： LUO Changbin, CHENG Lingxia, HUANG Wenbin, LI Liang, CAO Linghong, XU Ping. Clinical value of Composite Congestion Score in predicting adverse events in patients with acute heart failure in emergency intensive care unit within 180 days. West China Medical Journal, 2022, 37(12): 1824-1830. doi: 10.7507/1002-0179.202210165 Copy

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