About: Differentiating between 2019 novel coronavirus pneumonia and influenza using a non-specific laboratory marker-based dynamic nomogram

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About: Differentiating between 2019 novel coronavirus pneumonia and influenza using a non-specific laboratory marker-based dynamic nomogram Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Differentiating between 2019 novel coronavirus pneumonia and influenza using a non-specific laboratory marker-based dynamic nomogram
Creator	Wang, Lin Zhang, Wei Wang, Jingjing Yang, Li Zhang, Ting Fan, Ying Zhang, Ming Liu, Yao Chen, Zhihai Liu, Jingyuan Xiong, Haofeng Xu, Yanli Han, Bing Li, Chuansheng Pu, Lin Song, Meihua Song, Rui Tan, Jianbo Wang, Xianbo Ditan, Beijing Wang, Linghang Yang, Siyuan Cheng, Cheng Jiang, Yuyong
Source	Medline; PMC
abstract	BACKGROUND: There is currently a lack of non-specific laboratory indicators as a quantitative standard to distinguish between the 2019 coronavirus disease (COVID-19) and an influenza A or B virus infection. Thus, the aim of this study was to establish a nomogram to detect COVID-19. METHODS: A nomogram was established using data collected from 457 patients (181 with COVID-19 and 276 with influenza A or B infection) at China. The nomogram used age, lymphocyte percentage, and monocyte count to differentiate COVID-19 from influenza. RESULTS: Our nomogram predicted probabilities of COVID-19 with an AUROC of 0.913 (95% confidence interval [CI], 0.883–0.937), greater than that of the lymphocyte-to-monocyte ratio (0.849, 95%CI, 0.812–0.880; p = 0.0007), lymphocyte percentage (0.808, 95%CI, 0.768–0.843; p < 0.0001), monocyte count (0.780, 95%CI, 0.739–0.817; p < 0.0001), or age (0.656, 95%CI, 0.610–0.699; p < 0.0001). The predicted probability conformed to the real observation outcomes of COVID-19, according to the calibration curves. CONCLUSIONS: We found that age, lymphocyte percentage, and monocyte count are risk factors for the early-stage prediction of patients infected with the 2019 novel coronavirus. As such, our research provides a useful test for doctors to differentiate COVID-19 from influenza.
has issue date	2020-05-16(xsd:dateTime)
bibo:doi	10.1093/ofid/ofaa169
bibo:pmid	32490031
has license	cc-by-nc-nd
sha1sum (hex)	49899785994a27e28ff79253936fad39a7d6b986
schema:url	https://doi.org/10.1093/ofid/ofaa169
resource representing a document's title	Differentiating between 2019 novel coronavirus pneumonia and influenza using a non-specific laboratory marker-based dynamic nomogram
has PubMed Central identifier	PMC7239104
has PubMed identifier	32490031
schema:publication	Open Forum Infect Dis
resource representing a document's body	covid:49899785994a27e28ff79253936fad39a7d6b986#body_text
is schema:about of	named entity 'cough' named entity 'PCR diagnosis' named entity 'COVID' named entity 'non-specific' named entity 'nomogram' named entity 'pneumonia' named entity 'real-time polymerase chain reaction' named entity 'chi-square test' named entity 'incubation period' named entity 'p-value' named entity 'influenza' named entity 'COVID' named entity 'R Foundation' named entity 'influenza' named entity 'COVID' named entity 'influenza' named entity '8 December 2019' named entity 'Chicago' named entity 'pneumonia' named entity 'Huanan seafood market' named entity 'coronavirus' named entity 'COVID' named entity 'coronavirus' named entity 'nucleic acid testing' named entity 'demographic' named entity 'laboratory tests' named entity 'nomogram' named entity 'COVID' named entity 'lower respiratory tract' named entity 'nomogram' named entity 'RT-PCR' named entity 'false negative' named entity 'pneumonia' named entity 'coronavirus' named entity 'COVID' named entity 'coronavirus' named entity 'nucleic acids' named entity 'upper respiratory tract' named entity 'virus' named entity 'virus' named entity 'COVID-19' named entity 'pneumonia' named entity 'homologous' named entity 'infection' named entity 'Pandemics' named entity 'WBC' named entity 'dyspnea' named entity 'coronavirus' named entity 'lymphocyte' named entity 'coronavirus' named entity 'nucleic acids' named entity 'COVID-19' named entity 'receiver operating characteristic' named entity 'influenza' named entity 'non-specific' named entity 'Vienna, Austria' named entity 'RT-PCR' named entity 'statistically significant'

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