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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
Semantic information from SemMedBD (by NLM)
1. Evaluation procedure USES tomography
Subject
Evaluation procedure
Predicate
USES
Object
tomography
2. Evaluation procedure USES tomography
Subject
Evaluation procedure
Predicate
USES
Object
tomography
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.
Keywords

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

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