Differential diagnosis of coronavirus disease 2019 pneumonia or influenza A pneumonia by clinical characteristics and laboratory findings

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Abstract

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.

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APA

Lv, D. feng, Ying, Q. ming, He, Y. wen, Liang, J., Zhang, J. hong, Lu, B. bei, … Mu, Q. tian. (2021). Differential diagnosis of coronavirus disease 2019 pneumonia or influenza A pneumonia by clinical characteristics and laboratory findings. Journal of Clinical Laboratory Analysis, 35(2). https://doi.org/10.1002/jcla.23685

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