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Chinese Journal of Emergency Medicine ; (12): 365-370, 2023.
Article in Chinese | WPRIM | ID: wpr-989816

ABSTRACT

Objective:To explore the predictive value of systemic immune inflammation index (SII) for the risk of hospital death in critically ill patients.Methods:The basic information and clinical data of critically ill patients were extracted from the Medical Information Mart for Intensive Care database-Ⅳ (MIMIC-IV) database, including demographic data, vital signs, blood routine, Logistic organ dysfunction score (Lods), Oxford acute severity of illness score (Oasis), simplified acute physiology score (Saps-Ⅱ), acute physiology score Ⅲ (APS-Ⅲ), sequential organ failure score (SOFA) and outcome. The main outcome was hospital death, and the secondary outcomes were length of hospital stay, continuous renal replacement therapy (CRRT), invasive ventilation and 1-year mortality. Patients were divided into two groups according to in-hospital death, and the differences between the groups were compared. According to the SII tripartite for inter-group comparison, the patients were further divided into three groups for comparison, and Logistic regression model was used to analyze the odd ratio ( OR) of the three groups. Results:A total of 32 450 critically ill patients were included in the study, of which 3765 died in hospital, with a mortality rate of 11.6%. ① Compared with the survival group, the SII in the death group were significantly higher ( P < 0.05). ② The mortality for the SII tripartite grouping (<817; 817~2 151; >2 151) were 8.4%, 10.2% and 16.3%, respectively, and the differences between groups were statistically significant. ③ Further, Logistic regression model analysis showed that the risk of death increased gradually with the increase of groups (the first group was the reference group, OR of the second group was 1.38, 95% CI 1.24-1.54, and OR of the third group was 2.03, 95% CI 1.83-2.24 ( P < 0.05). Conclusions:SII has a certain value in predicting hospital death in critically ill patients. It is easy to obtain and can be used for risk stratification of critically ill patients.

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