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Predictors of severe sepsis-related in-hospital mortality based on a multicenter cohort study

机译:基于多中心队列研究的严重败血症相关内死亡率预测因素

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ABSTRACT:This study aimed to identify prognostic factors for severe sepsis-related in-hospital mortality using the structural equation model (SEM) analysis with statistical causality. Sepsis data from the Focused Outcomes Research in Emergency Care in Acute Respiratory Distress Syndrome, Sepsis, and Trauma study (FORECAST), a multicenter cohort study, was used. Forty seven observed variables from the database were used to construct 4 latent variables. SEM analysis was performed on these latent variables to analyze the statistical causality among these data. This study evaluated whether the variables had an effect on in-hospital mortality. Overall, 1148 patients were enrolled. The SEM analysis showed that the 72-hour physical condition was the strongest latent variable affecting mortality, followed by physical condition before treatment. Furthermore, the 72-hour physical condition and the physical condition before treatment strongly influenced the Sequential Organ Failure Assessment (SOFA) score with path coefficients of 0.954 and 0.845, respectively. The SOFA score was the strongest variable that affected mortality after the onset of severe sepsis. The score remains the most robust prognostic factor and can facilitate appropriate policy development on care.Copyright ? 2021 the Author(s). Published by Wolters Kluwer Health, Inc.
机译:摘要:本研究旨在鉴定使用结构方程模型(SEM)分析与统计因果关系的严重脓毒症相关内部死亡率的预后因素。使用了来自急性呼吸窘迫综合征,脓毒症和创伤研究(预测)的急性呼吸窘迫综合症研究中的脓毒症数据,是一种多中心队列研究。来自数据库的四十七种观察到的变量用于构建4个潜在变量。对这些潜在变量进行SEM分析,分析这些数据之间的统计因果关系。本研究评估了变量是否对住院内死亡率产生影响。总体而言,1148名患者注册。 SEM分析表明,72小时的身体状况是影响死亡率最强的潜在变量,然后在治疗前进行身体状况。此外,治疗前72小时的身体状况和身体状况强烈影响顺序器官衰竭评估(沙发)分别与0.954和0.845的路径系数。沙发评分是严重败血症发作后影响死亡率的最强变量。得分仍然是最强大的预后因素,可以促进护理的适当政策制定吗? 2021提交人。由Wolters Kluwer Health,Inc。出版

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