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. 2020 Dec 3;15(12):e0243261.
doi: 10.1371/journal.pone.0243261. eCollection 2020.

Characteristics associated with COVID-19 or other respiratory viruses' infections at a single-center emergency department

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Characteristics associated with COVID-19 or other respiratory viruses' infections at a single-center emergency department

Donia Bouzid et al. PLoS One. .

Erratum in

Abstract

Background: Rapid identification of patients with high suspicion of COVID-19 will become a challenge with the co-circulation of multiple respiratory viruses (RVs). We have identified clinical or biological characteristics to help distinguish SARS-CoV-2 from other RVs.

Methods: We used a prospective cohort including all consecutive patients admitted through the emergency department's (ED) and presenting respiratory symptoms from November 2019 to April 2020. Patients were tested for RV using multiplex polymerase chain reaction (mPCR) and SARS-CoV-2 RT-PCR.

Results: 203/508 patients were positive for an RV during the non-SARS-CoV-2 epidemic period (November to February), and 268/596 patients were SARS-CoV-2 positive during the SARS-CoV-2 epidemic (March to April). Younger age, male gender, fever, absence of expectoration and absence of chronic lung disease were statistically associated with SARS-CoV-2 detection. Combining these variables allowed for the distinguishing of SARS-CoV-2 infections with 83, 65, 75 and 76% sensitivity, specificity, PPV and NPV, respectively.

Conclusion: Patients' characteristics associated with a positive PCR are common between SARS-CoV-2 and other RVs, but a simple discrimination of strong SARS-CoV-2 suspicion with a limited set of clinical features seems possible. Such scoring could be useful but has to be prospectively evaluated and will not eliminate the need for rapid PCR assays.

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Conflict of interest statement

DB and BV declare having received past personal fees and grant from Qiagen. All the others declare having no conflict of interest. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

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