SARS-CoV-2 serology increases diagnostic accuracy in CT-suspected, PCR-negative COVID-19 patients during pandemic.


Journal

Respiratory research
ISSN: 1465-993X
Titre abrégé: Respir Res
Pays: England
ID NLM: 101090633

Informations de publication

Date de publication:
23 Apr 2021
Historique:
received: 29 07 2020
accepted: 14 04 2021
entrez: 24 4 2021
pubmed: 25 4 2021
medline: 30 4 2021
Statut: epublish

Résumé

In the absence of PCR detection of SARS-CoV-2 RNA, accurate diagnosis of COVID-19 is challenging. Low-dose computed tomography (CT) detects pulmonary infiltrates with high sensitivity, but findings may be non-specific. This study assesses the diagnostic value of SARS-CoV-2 serology for patients with distinct CT features but negative PCR. IgM/IgG chemiluminescent immunoassay was performed for 107 patients with confirmed (group A: PCR + ; CT ±) and 46 patients with suspected (group B: repetitive PCR-; CT +) COVID-19, admitted to a German university hospital during the pandemic's first wave. A standardized, in-house CT classification of radiological signs of a viral pneumonia was used to assess the probability of COVID-19. Seroconversion rates (SR) determined on day 5, 10, 15, 20 and 25 after symptom onset (SO) were 8%, 25%, 65%, 76% and 91% for group A, and 0%, 10%, 19%, 37% and 46% for group B, respectively; (p < 0.01). Compared to hospitalized patients with a non-complicated course (non-ICU patients), seroconversion tended to occur at lower frequency and delayed in patients on intensive care units. SR of patients with CT findings classified as high certainty for COVID-19 were 8%, 22%, 68%, 79% and 93% in group A, compared with 0%, 15%, 28%, 50% and 50% in group B (p < 0.01). SARS-CoV-2 serology established a definite diagnosis in 12/46 group B patients. In 88% (8/9) of patients with negative serology > 14 days after symptom onset (group B), clinico-radiological consensus reassessment revealed probable diagnoses other than COVID-19. Sensitivity of SARS-CoV-2 serology was superior to PCR > 17d after symptom onset. Approximately one-third of patients with distinct COVID-19 CT findings are tested negative for SARS-CoV-2 RNA by PCR rendering correct diagnosis difficult. Implementation of SARS-CoV-2 serology testing alongside current CT/PCR-based diagnostic algorithms improves discrimination between COVID-19-related and non-related pulmonary infiltrates in PCR negative patients. However, sensitivity of SARS-CoV-2 serology strongly depends on the time of testing and becomes superior to PCR after the 2

Sections du résumé

BACKGROUND BACKGROUND
In the absence of PCR detection of SARS-CoV-2 RNA, accurate diagnosis of COVID-19 is challenging. Low-dose computed tomography (CT) detects pulmonary infiltrates with high sensitivity, but findings may be non-specific. This study assesses the diagnostic value of SARS-CoV-2 serology for patients with distinct CT features but negative PCR.
METHODS METHODS
IgM/IgG chemiluminescent immunoassay was performed for 107 patients with confirmed (group A: PCR + ; CT ±) and 46 patients with suspected (group B: repetitive PCR-; CT +) COVID-19, admitted to a German university hospital during the pandemic's first wave. A standardized, in-house CT classification of radiological signs of a viral pneumonia was used to assess the probability of COVID-19.
RESULTS RESULTS
Seroconversion rates (SR) determined on day 5, 10, 15, 20 and 25 after symptom onset (SO) were 8%, 25%, 65%, 76% and 91% for group A, and 0%, 10%, 19%, 37% and 46% for group B, respectively; (p < 0.01). Compared to hospitalized patients with a non-complicated course (non-ICU patients), seroconversion tended to occur at lower frequency and delayed in patients on intensive care units. SR of patients with CT findings classified as high certainty for COVID-19 were 8%, 22%, 68%, 79% and 93% in group A, compared with 0%, 15%, 28%, 50% and 50% in group B (p < 0.01). SARS-CoV-2 serology established a definite diagnosis in 12/46 group B patients. In 88% (8/9) of patients with negative serology > 14 days after symptom onset (group B), clinico-radiological consensus reassessment revealed probable diagnoses other than COVID-19. Sensitivity of SARS-CoV-2 serology was superior to PCR > 17d after symptom onset.
CONCLUSIONS CONCLUSIONS
Approximately one-third of patients with distinct COVID-19 CT findings are tested negative for SARS-CoV-2 RNA by PCR rendering correct diagnosis difficult. Implementation of SARS-CoV-2 serology testing alongside current CT/PCR-based diagnostic algorithms improves discrimination between COVID-19-related and non-related pulmonary infiltrates in PCR negative patients. However, sensitivity of SARS-CoV-2 serology strongly depends on the time of testing and becomes superior to PCR after the 2

Identifiants

pubmed: 33892720
doi: 10.1186/s12931-021-01717-9
pii: 10.1186/s12931-021-01717-9
pmc: PMC8062836
doi:

Substances chimiques

Immunoglobulin G 0
Immunoglobulin M 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

119

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Auteurs

Jochen Schneider (J)

Department of Internal Medicine II, School of Medicine, Technical University of Munich, Munich, Germany. Jochen.Schneider@tum.de.
German Center for Infection Research (DZIF), partner site Munich, Munich, Germany. Jochen.Schneider@tum.de.

Hrvoje Mijočević (H)

German Center for Infection Research (DZIF), partner site Munich, Munich, Germany.
Institute for Virology, School of Medicine, Technical University of Munich, Munich, Germany.

Kurt Ulm (K)

Institute for Medical Statistics and Epidemiology, School of Medicine, Technical University of Munich, Munich, Germany.

Bernhard Ulm (B)

Department of Anaesthesiology and Intensive Care Medicine, School of Medicine, Technical University of Munich, Munich, Germany.

Simon Weidlich (S)

Department of Internal Medicine II, School of Medicine, Technical University of Munich, Munich, Germany.
German Center for Infection Research (DZIF), partner site Munich, Munich, Germany.

Silvia Würstle (S)

Department of Internal Medicine II, School of Medicine, Technical University of Munich, Munich, Germany.

Kathrin Rothe (K)

German Center for Infection Research (DZIF), partner site Munich, Munich, Germany.
Institute for Medical Microbiology, Immunology and Hygiene, School of Medicine, Technical University of Munich, Munich, Germany.

Matthias Treiber (M)

Department of Internal Medicine II, School of Medicine, Technical University of Munich, Munich, Germany.

Roman Iakoubov (R)

Department of Internal Medicine II, School of Medicine, Technical University of Munich, Munich, Germany.

Ulrich Mayr (U)

Department of Internal Medicine II, School of Medicine, Technical University of Munich, Munich, Germany.

Tobias Lahmer (T)

Department of Internal Medicine II, School of Medicine, Technical University of Munich, Munich, Germany.

Sebastian Rasch (S)

Department of Internal Medicine II, School of Medicine, Technical University of Munich, Munich, Germany.

Alexander Herner (A)

Department of Internal Medicine II, School of Medicine, Technical University of Munich, Munich, Germany.

Egon Burian (E)

Institute for Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Munich, Germany.

Fabian Lohöfer (F)

Institute for Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Munich, Germany.

Rickmer Braren (R)

Institute for Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Munich, Germany.

Marcus R Makowski (MR)

Institute for Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Munich, Germany.

Roland M Schmid (RM)

Department of Internal Medicine II, School of Medicine, Technical University of Munich, Munich, Germany.

Ulrike Protzer (U)

German Center for Infection Research (DZIF), partner site Munich, Munich, Germany.
Institute for Virology, School of Medicine, Technical University of Munich, Munich, Germany.

Christoph Spinner (C)

Department of Internal Medicine II, School of Medicine, Technical University of Munich, Munich, Germany.
German Center for Infection Research (DZIF), partner site Munich, Munich, Germany.

Fabian Geisler (F)

Department of Internal Medicine II, School of Medicine, Technical University of Munich, Munich, Germany. Fabian.geisler@mri.tum.de.

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Classifications MeSH