Ruling out COVID-19 by chest CT at emergency admission when prevalence is low: the prospective, observational SCOUT study.


Journal

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

Informations de publication

Date de publication:
12 Jan 2021
Historique:
received: 09 10 2020
accepted: 29 12 2020
entrez: 13 1 2021
pubmed: 14 1 2021
medline: 20 1 2021
Statut: epublish

Résumé

It is essential to avoid admission of patients with undetected corona virus disease 2019 (COVID-19) to hospitals' general wards. Even repeated negative reverse transcription polymerase chain reaction (RT-PCR) results do not rule-out COVID-19 with certainty. The study aimed to evaluate a rule-out strategy for COVID-19 using chest computed tomography (CT) in adults being admitted to the emergency department and suspected of COVID-19. In this prospective, single centre, diagnostic accuracy cohort study, consecutive adults (≥ 18 years) presenting with symptoms consistent with COVID-19 or previous contact to infected individuals, admitted to the emergency department and supposed to be referred to general ward were included in March and April 2020. All participants underwent low-dose chest CT. RT-PCR- and specific antibody tests were used as reference standard. Main outcome measures were sensitivity and specificity of chest CT. Predictive values were calculated based on the theorem of Bayes using Fagan's nomogram. Of 165 participants (56.4% male, 71 ± 16 years) included in the study, the diagnosis of COVID-19 was confirmed with RT-PCR and AB tests in 13 participants (prevalence 7.9%). Sensitivity and specificity of chest CT were 84.6% (95% confidence interval [CI], 54.6-98.1) and 94.7% (95% CI, 89.9-97.7), respectively. Positive and negative likelihood ratio of chest CT were 16.1 (95% CI, 7.9-32.8) and 0.16 (95% CI, 0.05-0.58) and positive and negative predictive value were 57.9% (95% CI, 40.3-73.7) and 98.6% (95% CI, 95.3-99.6), respectively. At a low prevalence of COVID-19, chest CT could be used as a complement to repeated RT-PCR testing for early COVID-19 exclusion in adults with suspected infection before referral to hospital's general wards. Trial registration ClinicalTrials.gov: NCT04357938 April 22, 2020.

Sections du résumé

BACKGROUND BACKGROUND
It is essential to avoid admission of patients with undetected corona virus disease 2019 (COVID-19) to hospitals' general wards. Even repeated negative reverse transcription polymerase chain reaction (RT-PCR) results do not rule-out COVID-19 with certainty. The study aimed to evaluate a rule-out strategy for COVID-19 using chest computed tomography (CT) in adults being admitted to the emergency department and suspected of COVID-19.
METHODS METHODS
In this prospective, single centre, diagnostic accuracy cohort study, consecutive adults (≥ 18 years) presenting with symptoms consistent with COVID-19 or previous contact to infected individuals, admitted to the emergency department and supposed to be referred to general ward were included in March and April 2020. All participants underwent low-dose chest CT. RT-PCR- and specific antibody tests were used as reference standard. Main outcome measures were sensitivity and specificity of chest CT. Predictive values were calculated based on the theorem of Bayes using Fagan's nomogram.
RESULTS RESULTS
Of 165 participants (56.4% male, 71 ± 16 years) included in the study, the diagnosis of COVID-19 was confirmed with RT-PCR and AB tests in 13 participants (prevalence 7.9%). Sensitivity and specificity of chest CT were 84.6% (95% confidence interval [CI], 54.6-98.1) and 94.7% (95% CI, 89.9-97.7), respectively. Positive and negative likelihood ratio of chest CT were 16.1 (95% CI, 7.9-32.8) and 0.16 (95% CI, 0.05-0.58) and positive and negative predictive value were 57.9% (95% CI, 40.3-73.7) and 98.6% (95% CI, 95.3-99.6), respectively.
CONCLUSION CONCLUSIONS
At a low prevalence of COVID-19, chest CT could be used as a complement to repeated RT-PCR testing for early COVID-19 exclusion in adults with suspected infection before referral to hospital's general wards. Trial registration ClinicalTrials.gov: NCT04357938 April 22, 2020.

Identifiants

pubmed: 33435973
doi: 10.1186/s12931-020-01611-w
pii: 10.1186/s12931-020-01611-w
pmc: PMC7802980
doi:

Banques de données

ClinicalTrials.gov
['NCT04357938']

Types de publication

Journal Article Observational Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

13

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Auteurs

Ulf Teichgräber (U)

Department of Radiology, Friedrich-Schiller-University, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany. ulf.teichgraeber@med.uni-jena.de.

Amer Malouhi (A)

Department of Radiology, Friedrich-Schiller-University, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany.

Maja Ingwersen (M)

Department of Radiology, Friedrich-Schiller-University, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany.

Rotraud Neumann (R)

Department of Radiology, Friedrich-Schiller-University, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany.

Marina Reljic (M)

Department of Internal Medicine, Friedrich-Schiller-University, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany.

Stefanie Deinhardt-Emmer (S)

Institute of Medical Microbiology, Friedrich-Schiller-University, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany.

Bettina Löffler (B)

Institute of Medical Microbiology, Friedrich-Schiller-University, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany.

Wilhelm Behringer (W)

Department of Emergency Medicine, Friedrich-Schiller-University, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany.

Jan-Christoph Lewejohann (JC)

Department of Emergency Medicine, Friedrich-Schiller-University, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany.

Andreas Stallmach (A)

Department of Internal Medicine, Friedrich-Schiller-University, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany.

Philipp Reuken (P)

Department of Internal Medicine, Friedrich-Schiller-University, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany.

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Classifications MeSH