刘宁静，贾艳霞，耿晓丽

引用本文： 刘宁静，贾艳霞，耿晓丽.甲型流感病毒合并多重感染的临床特征[J].护理研究,2024,38(1):17-23

摘要： 目的： 调查新型冠状病毒大面积感染后（2023年）病人的呼吸道病原学监测结果，并与疫情前（2018—2019年）及疫情防控期间（2020—2022年）结果比较，分析呼吸道病毒感染趋势变化及甲型流感病毒（IFVA）与混合感染的临床特点。 方法： 收集2023年2月—3月就诊于山西医科大学第一医院的2 902例呼吸道疾病病人和疫情前（=1 216）、疫情防控期间（=3 113）同期就诊的呼吸道疾病病人外周血病原体IgM检测结果进行分析，根据感染情况将阳性病人分为IFVA组、IFVA+肺原支原体（MP）组、IFVA+呼吸道合胞病毒（RSV）组和IFVA+乙型流感病毒（IFVB）组，对混合感染组与单纯感染组的临床特征及血常规进行比较。 结果： 2023年的2 902例呼吸道感染病人血清中，病原体IgM阳性的病例数为1 207例，其中IFVA⁃IgM阳性率最高，2种及以上抗体组合检出共计393例；疫情防控期间的3 113例呼吸道感染病人血清中病原体IgM阳性病例数为794例，其中IFVA⁃IgM阳性率最高，2种及以上抗体组合检出总计194例；疫情前的1 216例呼吸道感染病人血清中病原体IgM阳性病例数为393例，其中IFVA⁃IgM阳性率最高，2种及以上抗体组合检出总计63例。Logistic回归分析结果显示，年龄是IFVA+MP感染的独立影响因素，年龄、血小板计数（PLT）是IFVA+RSV感染的独立影响因素；PLT升高、有喘息气短胸闷症状、存在基础疾病是IFVA+IFVB感染的独立影响因素。在受试者工作特征（ROC）曲线中，年龄预测IFVA+MP感染的ROC曲线下面积为0.715［95%CI（0.657，0.773）］，年龄预测IFVA+RSV感染的ROC曲线下面积为0.742［95%CI（0.690，0.794）］。 结论： 新型冠状病毒感染期间严格的防控措施可以遏制呼吸道病原体的传播。经历新型冠状病毒大面积感染后，人们免疫力水平普遍下降，更易发生病毒感染和混合感染，临床医生可根据病人的临床症状、体征及实验室检查指标，及时预判是否发生混合感染并进行对症治疗。

关键词： 呼吸道病毒;流感病毒;混合感染;病原学检测;流行特征

课题： 中华国际科学交流基金会项目(Z2020LSXD07) ;山西省回国留学人员科研项目(2020⁃166)

LIU Ningjing，JIA Yanxia，GENG Xiaoli

Abstract Objective： To investigate the results of respiratory pathogenetic surveillance of patients after novel coronavirus pandemic infection （2023） and to compare them with the pre⁃epidemic （2018—2019） and intra⁃epidemic （2020—2022） results， and to analyze the changes in the trend of respiratory viral infections and the clinical characteristics of influenza A virus （IFVA） and mixed infections. Methods： The peripheral blood pathogen IgM test results of 2 902 patients with respiratory diseases who attended the First Hospital of Shanxi Medical University from February to March 2023 and those who attended the same period of time before （=1 216） and during the epidemic（=3 113） were collected and analyzed，and the positive patients were classified into the IFVA group according to the infection status，IFVA+Mycoplasma pneumoniae （MP），IFVA+Respiratory Syncytial Virus （RSV），and IFVA+Influenza B Virus （IFVB） groups，and the clinical characteristics and blood routine of the mixed infection groups were compared with those of the simple infection groups. Results： In the serum of 2 902 respiratory infection patients in 2023，the number of positive cases for pathogen IgM detection was 1 207，among which IFVA⁃ IgM had the highest positive rate，with a total of 393 cases detected with a combination of two or more antibodies；During the epidemic，the serum IgM test results of 3 113 respiratory infection patients showed a positive number of 794 cases，among which IFVA ⁃ IgM had the highest positive rate，with a total of 194 cases detected by a combination of two or more antibodies；before the epidemic，the serum IgM test results of 1 216 respiratory infection patients showed a positive number of 393 cases，of which IFVA⁃IgM had the highest positive rate，and a total of 63 cases were detected with two or more antibody combinations.The results of Logistic regression analysis showed that age is an independent influencing factor of IFVA+MP，while age and platelet count （PLT） are independent influencing factors of IFVA+RSV； Elevated PLT，shortness of breath and chest tightness，and the presence of underlying diseases are independent influencing factors of IFVA+IFBV.In the receiver operating characteristic （ROC） curve，the area under the ROC curve for age predicted IFVA+MP is 0.715（95%CI 0.657⁃0.773）.The area under the ROC curve for age prediction of IFVA+RSV is 0.742 （95%CI 0.690⁃0.794）. Conclusion： Strict precautionary measures during novel coronavirus infection can curb the spread of respiratory pathogens. Control measures can contain the spread of respiratory pathogens. After the widespread infection of novel coronavirus，people's immunity level generally decreases，which makes them more susceptible to viral infections and mixed infections. Clinicians can predict the occurrence of mixed infections based on patients' clinical symptoms，signs and laboratory tests，and provide symptomatic treatment in a timely manner.

Keywords respiratory virus;influenza virus;mixed infection;pathogenic testing;epidemic characteristics

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