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首页> 外文期刊>BMC Infectious Diseases >Novel risk scoring system for predicting acute respiratory distress syndrome among hospitalized patients with coronavirus disease 2019 in Wuhan, China
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Novel risk scoring system for predicting acute respiratory distress syndrome among hospitalized patients with coronavirus disease 2019 in Wuhan, China

机译:中国武汉冠状病毒疾病急性呼吸窘迫综合征预测急性呼吸窘迫综合征的新型风险评分系统

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摘要

The mortality rate from acute respiratory distress syndrome (ARDS) is high among hospitalized patients with coronavirus disease 2019 (COVID-19). Hence, risk evaluation tools are required to immediately identify high-risk patients upon admission for early intervention. A cohort of 220 consecutive patients with COVID-19 were included in this study. To analyze the risk factors of ARDS, data obtained from approximately 70% of the participants were randomly selected and used as training dataset to establish a logistic regression model. Meanwhile, data obtained from the remaining 30% of the participants were used as test dataset to validate the effect of the model. Lactate dehydrogenase, blood urea nitrogen, D-dimer, procalcitonin, and ferritin levels were included in the risk score system and were assigned a score of 25, 15, 34, 20, and 24, respectively. The cutoff value for the total score was ?35, with a sensitivity of 100.00% and specificity of 81.20%. The area under the receiver operating characteristic curve and the Hosmer–Lemeshow test were 0.967 (95% confidence interval [CI]: 0.925–0.989) and 0.437(P Value?=?0.437). The model had excellent discrimination and calibration during internal validation. The novel risk score may be a valuable risk evaluation tool for screening patients with COVID-19 who are at high risk of ARDS.
机译:来自急性呼吸窘迫综合征(ARDS)的死亡率在住院治疗患者2019年(Covid-19)中是高的。因此,风险评估工具必须立即识别高风险患者,以便在提前干预方面。本研究包括220名连续220名Covid-19患者。要分析ARDS的危险因素,从大约70%的参与者获取的数据被随机选择并用作训练数据集,以建立一个逻辑回归模型。同时,从剩余的30%获得的数据用作测试数据集以验证模型的效果。乳酸脱氢酶,血尿尿素氮,D-二聚体,proCalcitonin和铁素水平分别分别分配25,15,34,20和24分。总分的截止值为>?35,灵敏度为100.00%,特异性为81.20%。接收器操作特性曲线和Hosmer-Lemeshow测试的区域为0.967(95%置信区间[CI]:0.925-0.989)和0.437(P值?= 0.437)。该模型在内部验证过程中具有出色的歧视和校准。新颖的风险评分可能是筛查患者的有价值的风险评估工具,用于筛查患有高风险的Covid-19患者。

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