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COVID-19 Pandemic and Upcoming Influenza Season—Does an Expert’s Computed Tomography Assessment Differentially Identify COVID-19, Influenza and Pneumonias of Other Origin?
Journal of Clinical Medicine ; 10(1):84, 2021.
Article in English | ScienceDirect | ID: covidwho-984764
ABSTRACT
(1)

Background:

Time-consuming SARS-CoV-2 RT-PCR suffers from limited sensitivity in early infection stages whereas fast available chest CT can already raise COVID-19 suspicion. Nevertheless, radiologists’performance to differentiate COVID-19, especially from influenza pneumonia, is not sufficiently characterized. (2)

Methods:

A total of 201 pneumonia CTs were identified and divided into subgroups based on RT-PCR 78 COVID-19 CTs, 65 influenza CTs and 62 Non-COVID-19-Non-influenza (NCNI) CTs. Three radiology experts (blinded from RT-PCR results) raised pathogen-specific suspicion (separately for COVID-19, influenza, bacterial pneumonia and fungal pneumonia) according to the following reading scores 0—not typical/1—possible/2—highly suspected. Diagnostic performances were calculated with RT-PCR as a reference standard. Dependencies of radiologists’pathogen suspicion scores were characterized by Pearson’s Chi2 Test for Independence. (3)

Results:

Depending on whether the intermediate reading score 1 was considered as positive or negative, radiologists correctly classified 83–85% (vs. NCNI)/79–82% (vs. influenza) of COVID-19 cases (sensitivity up to 94%). Contrarily, radiologists correctly classified only 52–56% (vs. NCNI)/50–60% (vs. COVID-19) of influenza cases. The COVID-19 scoring was more specific than the influenza scoring compared with suspected bacterial or fungal infection. (4)

Conclusions:

High-accuracy COVID-19 detection by CT might expedite patient management even during the upcoming influenza season.
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Collection: Databases of international organizations Database: ScienceDirect Type of study: Prognostic study Language: English Journal: Journal of Clinical Medicine Year: 2021 Document Type: Article
Search on Google
Collection: Databases of international organizations Database: ScienceDirect Type of study: Prognostic study Language: English Journal: Journal of Clinical Medicine Year: 2021 Document Type: Article