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首页> 外文期刊>BMC Infectious Diseases >Score risk model for predicting severe fever with thrombocytopenia syndrome mortality
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Score risk model for predicting severe fever with thrombocytopenia syndrome mortality

机译:评估严重发热伴血小板减少综合征死亡率的评分风险模型

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Background Severe fever with thrombocytopenia syndrome (SFTS) is an emerging epidemic infectious disease with high mortality in East Aisa, especially in China. To predict the prognosis of SFTS precisely is important in clinical practice. Methods From May 2013 to November 2015, 233 suspected SFTS patients were tested for SFTS virus using RT-PCR. Cox regression model was utilized to comfirm independent risk factors for mortality. A risk score model for mortality was constructed based on regression coefficient of risk factors. Log-rank test was used to evaluate the significance of this model. Results One hundred seventy-four patients were confirmed with SFTS, of which 40 patients died (23%). Baseline age, serum aspartate aminotransferase (AST) and serum creatinine (sCr) level were independent risk factors of mortality. The area under ROC curve (AUCs) of these parameters for predicting death were 0.771, 0.797 and 0.764, respectively. And hazard ratio (HR) were 1.128, 1.002 and 1.013, respectively. The cutoff value of the risk model was 10. AUC of the model for predicting mortality was 0.892, with sensitivity and specificity of 82.5 and 86.6%, respectively. Log-rank test indicated strong statistical significance (×2?=?88.35, p Conclusions This risk score model may be helpful to predicting the prognosis of SFTS patients.
机译:背景技术严重血小板减少症候群(SFTS)的高烧是一种在东艾萨(East Aisa)尤其是中国的新兴流行病,其死亡率很高。准确预测SFTS的预后在临床实践中很重要。方法2013年5月至2015年11月,采用RT-PCR方法对233名疑似SFTS患者进行了SFTS病毒检测。使用Cox回归模型来确认死亡的独立危险因素。基于风险因素的回归系数,建立了死亡率风险评分模型。对数秩检验用于评估该模型的重要性。结果174例确诊为SFTS的患者,其中40例死亡(23%)。基线年龄,血清天冬氨酸转氨酶(AST)和血清肌酐(sCr)水平是死亡率的独立危险因素。这些用于预测死亡的参数的ROC曲线下面积(AUC)分别为0.771、0.797和0.764。危险比(HR)分别为1.128、1.002和1.013。风险模型的临界值为10。该模型用于预测死亡率的AUC为0.892,敏感性和特异性分别为82.5和86.6%。 Log-rank检验表明有很强的统计学意义(× 2 ?=?88.35,p结论)该风险评分模型可能有助于预测SFTS患者的预后。

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