l44i7r6e

Property	Value
?:abstract	BACKGROUND: Respiratory viruses (RVs) is a common cause of illness in people of all ages, at present, different types of sampling methods are available for respiratory viral diagnosis. However, the diversity of available sampling methods and the limited direct comparisons in randomised controlled trials (RCTs) make decision-making difficult. We did a network meta-analysis, which accounted for both direct and indirect comparisons, to determine the detection rate of different sampling methods for RVs. METHODS: Relevant articles were retrieved comprehensively by searching the online databases of PubMed, Embase and Cochrane published before 25 March 2020. With the help of R V.3.6.3 software and ‘GeMTC V.0.8.2’ package, network meta-analysis was performed within a Bayesian framework. Node-splitting method and I(2) test combined leverage graphs and Gelman-Rubin-Brooks plots were conducted to evaluate the model’s accuracy. The rank probabilities in direct and cumulative rank plots were also incorporated to rank the corresponding sampling methods for overall and specific virus. RESULTS: 16 sampling methods with 54 438 samples from 57 literatures were ultimately involved in this study. The model indicated good consistency and convergence but high heterogeneity, hence, random-effect analysis was applied. The top three sampling methods for RVs were nasopharyngeal wash (NPW), mid-turbinate swab (MTS) and nasopharyngeal swab (NPS). Despite certain differences, the results of virus-specific subanalysis were basically consistent with RVs: MTS, NPW and NPS for influenza; MTS, NPS and NPW for influenza-a and b; saliva, NPW and NPS for rhinovirus and parainfluenza; NPW, MTS and nasopharyngeal aspirate for respiratory syncytial virus; saliva, NPW and MTS for adenovirus and sputum; MTS and NPS for coronavirus. CONCLUSION: This network meta-analysis provides supporting evidences that NPW, MTS and NPS have higher diagnostic value regarding RVs infection, moreover, particular preferred methods should be considered in terms of specific virus pandemic. Of course, subsequent RCTs with larger samples are required to validate our findings.
is ?:annotates of	<https://research.tib.eu/covid-19/entity/l44i7r6e_hasAnnotation_C0001483> <https://research.tib.eu/covid-19/entity/l44i7r6e_hasAnnotation_C0035236> <https://research.tib.eu/covid-19/entity/l44i7r6e_hasAnnotation_C0035473> <https://research.tib.eu/covid-19/entity/l44i7r6e_hasAnnotation_C0042776> <https://research.tib.eu/covid-19/entity/l44i7r6e_hasAnnotation_C0597404>
?:creator	<https://research.tib.eu/covid-19/entity/Hou%2C_Nianzong%3B_Wang%2C_Kai%3B_Zhang%2C_Haiyang%3B_Bai%2C_Mingjian%3B_Chen%2C_Hao%3B_Song%2C_Weidong%3B_Jia%2C_Fusen%3B_Zhang%2C_Yi%3B_Han%2C_Shiliang%3B_Xie%2C_Bing>
?:doi	10.1136/bmjgh-2020-003053
?:doi	<https://research.tib.eu/covid-19/entity/10.1136/bmjgh-2020-003053>
?:journal	BMJ_Glob_Health
?:license	cc-by-nc
?:pdf_json_files	document_parses/pdf_json/4ee45b597dda98c1939581b8151efe472aaf69aa.json
?:pmc_json_files	document_parses/pmc_json/PMC7654123.xml.json
?:pmcid	<https://research.tib.eu/covid-19/entity/PMC7654123>
?:pmid	<https://research.tib.eu/covid-19/entity/33168521.0>
?:pmid	33168521.0
?:publication_isRelatedTo_Disease	<https://research.tib.eu/covid-19/entity/COVID-19>
?:sha_id	<https://research.tib.eu/covid-19/entity/4ee45b597dda98c1939581b8151efe472aaf69aa>
?:source	Medline; PMC
?:title	Comparison of detection rate of 16 sampling methods for respiratory viruses: a Bayesian network meta-analysis of clinical data and systematic review
?:type	<https://research.tib.eu/covid-19/vocab/Publication>
?:year	2020-11-09

Property

Value

?:abstract

BACKGROUND: Respiratory viruses (RVs) is a common cause of illness in people of all ages, at present, different types of sampling methods are available for respiratory viral diagnosis. However, the diversity of available sampling methods and the limited direct comparisons in randomised controlled trials (RCTs) make decision-making difficult. We did a network meta-analysis, which accounted for both direct and indirect comparisons, to determine the detection rate of different sampling methods for RVs. METHODS: Relevant articles were retrieved comprehensively by searching the online databases of PubMed, Embase and Cochrane published before 25 March 2020. With the help of R V.3.6.3 software and ‘GeMTC V.0.8.2’ package, network meta-analysis was performed within a Bayesian framework. Node-splitting method and I(2) test combined leverage graphs and Gelman-Rubin-Brooks plots were conducted to evaluate the model’s accuracy. The rank probabilities in direct and cumulative rank plots were also incorporated to rank the corresponding sampling methods for overall and specific virus. RESULTS: 16 sampling methods with 54 438 samples from 57 literatures were ultimately involved in this study. The model indicated good consistency and convergence but high heterogeneity, hence, random-effect analysis was applied. The top three sampling methods for RVs were nasopharyngeal wash (NPW), mid-turbinate swab (MTS) and nasopharyngeal swab (NPS). Despite certain differences, the results of virus-specific subanalysis were basically consistent with RVs: MTS, NPW and NPS for influenza; MTS, NPS and NPW for influenza-a and b; saliva, NPW and NPS for rhinovirus and parainfluenza; NPW, MTS and nasopharyngeal aspirate for respiratory syncytial virus; saliva, NPW and MTS for adenovirus and sputum; MTS and NPS for coronavirus. CONCLUSION: This network meta-analysis provides supporting evidences that NPW, MTS and NPS have higher diagnostic value regarding RVs infection, moreover, particular preferred methods should be considered in terms of specific virus pandemic. Of course, subsequent RCTs with larger samples are required to validate our findings.

is ?:annotates of