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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?
Rueckel, Johannes; Fink, Nicola; Kaestle, Sophia; Stüber, Theresa; Schwarze, Vincent; Gresser, Eva; Hoppe, Boj F; Rudolph, Jan; Kunz, Wolfgang G; Ricke, Jens; Sabel, Bastian O.
  • Rueckel J; Department of Radiology, University Hospital, LMU Munich, 81377 Munich, Germany.
  • Fink N; Department of Radiology, University Hospital, LMU Munich, 81377 Munich, Germany.
  • Kaestle S; Comprehensive Pneumology Center (CPC-M), German Center for Lung Research (DZL), 81377 Munich, Germany.
  • Stüber T; Department of Radiology, University Hospital, LMU Munich, 81377 Munich, Germany.
  • Schwarze V; Department of Radiology, University Hospital, LMU Munich, 81377 Munich, Germany.
  • Gresser E; Chair of Statistical Learning & Data Science, Department of Statistics, LMU Munich, 80539 Munich, Germany.
  • Hoppe BF; Department of Radiology, University Hospital, LMU Munich, 81377 Munich, Germany.
  • Rudolph J; Department of Radiology, University Hospital, LMU Munich, 81377 Munich, Germany.
  • Kunz WG; Department of Radiology, University Hospital, LMU Munich, 81377 Munich, Germany.
  • Ricke J; Department of Radiology, University Hospital, LMU Munich, 81377 Munich, Germany.
  • Sabel BO; Department of Radiology, University Hospital, LMU Munich, 81377 Munich, Germany.
J Clin Med ; 10(1)2020 Dec 28.
Article in English | MEDLINE | ID: covidwho-1004736
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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Full text: Available Collection: International databases Database: MEDLINE Type of study: Diagnostic study / Prognostic study Language: English Year: 2020 Document Type: Article Affiliation country: Jcm10010084

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Diagnostic study / Prognostic study Language: English Year: 2020 Document Type: Article Affiliation country: Jcm10010084