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04849nam a2201081Ia 4500 |
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10.1002-jcla.23685 |
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220427s2021 CNT 000 0 und d |
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|a 08878013 (ISSN)
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|a Differential diagnosis of coronavirus disease 2019 pneumonia or influenza A pneumonia by clinical characteristics and laboratory findings
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|b John Wiley and Sons Inc
|c 2021
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|z View Fulltext in Publisher
|u https://doi.org/10.1002/jcla.23685
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|a Background: Pneumonia caused by the 2019 novel Coronavirus (COVID-2019) shares overlapping signs and symptoms, laboratory findings, imaging features with influenza A pneumonia. We aimed to identify their clinical characteristics to help early diagnosis. Methods: We retrospectively retrieved data for laboratory-confirmed patients admitted with COVID-19–induced or influenza A–induced pneumonia from electronic medical records in Ningbo First Hospital, China. We recorded patients' epidemiological and clinical features, as well as radiologic and laboratory findings. Results: The median age of influenza A cohort was higher and it exhibited higher temperature and higher proportion of pleural effusion. COVID-19 cohort exhibited higher proportions of fatigue, diarrhea and ground-glass opacity and higher levels of lymphocyte percentage, absolute lymphocyte count, red-cell count, hemoglobin and albumin and presented lower levels of monocytes, c-reactive protein, aspartate aminotransferase, alkaline phosphatase, serum creatinine. Multivariate logistic regression analyses showed that fatigue, ground-glass opacity, and higher level of albumin were independent risk factors for COVID-19 pneumonia, while older age, higher temperature, and higher level of monocyte count were independent risk factors for influenza A pneumonia. Conclusions: In terms of COVID-19 pneumonia and influenza A pneumonia, fatigue, ground-glass opacity, and higher level of albumin tend to be helpful for diagnosis of COVID-19 pneumonia, while older age, higher temperature, and higher level of monocyte count tend to be helpful for the diagnosis of influenza A pneumonia. © 2021 The Authors. Journal of Clinical Laboratory Analysis published by Wiley Periodicals LLC
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|a adult
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|a age
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|a albumin
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|a albumin blood level
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|a Article
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|a aspartate aminotransferase
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|a aspartate aminotransferase blood level
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|a body temperature
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|a C reactive protein
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|a China
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|a clinical characteristics
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|a clinical feature
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|a Clinical Laboratory Techniques
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|a cohort analysis
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|a coronavirus disease 2019
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|a COVID-19
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|a COVID-19
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|a creatinine
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|a creatinine blood level
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|a Diagnosis, Differential
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|a diagnostic imaging
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|a diarrhea
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|a differential diagnosis
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|a differential diagnosis
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|a differential diagnosis
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|a early diagnosis
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|a electronic medical record
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|a erythrocyte count
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|a fatigue
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|a female
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|a Female
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|a ground glass opacity
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|a hemoglobin
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|a hemoglobin blood level
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|a hospital admission
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|a human
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|a Humans
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|a influenza A
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|a influenza A
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|a Influenza A virus
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|a Influenza A virus
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|a laboratory diagnosis
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|a laboratory technique
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|a Logistic Models
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|a lymphocyte count
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|a lymphocyte percentage
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|a major clinical study
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|a male
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|a Male
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|a middle aged
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|a Middle Aged
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|a monocyte percentage
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|a multivariate analysis
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|a Multivariate Analysis
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|a physiology
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|a pleura effusion
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|a pneumonia
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|a pneumonia
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|a Pneumonia
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|a protein blood level
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|a retrospective study
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|a risk factor
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|a Risk Factors
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|a SARS-CoV-2
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|a statistical model
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|a Tomography, X-Ray Computed
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|a virology
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|a virus pneumonia
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|a x-ray computed tomography
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|a Chen, X.-Q.
|e author
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|a Chu, J.-G.
|e author
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|a He, Y.-W.
|e author
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|a Liang, J.
|e author
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|a Lu, B.-B.
|e author
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|a Lv, D.-F.
|e author
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|a Mu, Q.-T.
|e author
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|a Qian, G.-Q.
|e author
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|a Weng, X.-B.
|e author
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|a Ying, Q.-M.
|e author
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|a Zhang, J.-H.
|e author
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|t Journal of Clinical Laboratory Analysis
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