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作 者:吴传飞 余佩 宣传富 Wu Chuanfei;Yu Pei;Xuan Chuanfu(Department of Pediatrics,Yiwu Maternity and Children Hospital,Yiwu 322000,China)
出 处:《新医学》2023年第8期574-579,共6页Journal of New Medicine
基 金:义乌市科技计划项目(20-3-140)。
摘 要:目的探讨婴幼儿呼吸道合胞病毒(RSV)中-重度感染的危险因素,建立预测模型并验证。方法回顾性分析399例RSV感染患儿的临床资料,其中299例为建模组、100例为验证组。采用单因素和多因素Logistic回归分析筛选出中-重度感染的危险因素,并建立临床评分模型。结果建模组299例RSV感染患儿中,判定为中-重度48例、轻度251例。根据单因素及多因素Logistic回归分析筛选出体重、喂养史、是否喘息、红细胞分布宽度、红细胞压积等影响因素(P均<0.05),用于拟合联合诊断,制作临床评分模型。该临床评分模型的曲线下面积为0.777(95%CI 0.703~0.853),诊断阈值为1.365,此时灵敏度为0.829、特异度为0.604,内部验证结果表明该模型有较好的一致性。结论建立了预测RSV中-重度感染的临床评分模型,该评分模型具有一定准确度。Objective To explore the risk factors for moderate and severe respiratory syncytial virus(RSV)infection in infants,and to establish and validate the predictive model.Methods Clinical data of 399 children with RSV infection were retrospectively analyzed,including 299 cases in the model group and 100 cases in the validation group.Univariate and multivariate Logistic regression analyses were used to screen the risk factors of moderate and severe RSV infection,and a clinical scoring model was established.Results In the model group(n=299),48 children were classified with moderate to severe RSV infection and 251 cases of mild RSV infection.According to univariate and multivariate Logistic regression analyses,body weight,feeding history,wheezing,erythrocyte distribution width and hematocrit were the risk factors(all P<0.05),which were used to fit the joint diagnosis and establish the clinical scoring model.The area under the ROC curve(AUC)of clinical scoring model was 0.777(95%CI 0.703-0.853),the diagnostic cutoff value was 1.365,the sensitivity was 0.829 and the specificity was 0.604,respectively.The internal validation results showed that the model had high consistency.Conclusion A clinical scoring model for predicting moderate and severe RSV infection is established,which has certain accuracy.
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