Usefulness of High-Resolution Computed Tomography in Early Diagnosis of Patients with Suspected COVID-19.
Curr Med Imaging
; 18(14): 1510-1516, 2022.
Article
in English
| MEDLINE | ID: covidwho-1879363
ABSTRACT
BACKGROUND:
Diagnosis of coronavirus disease 2019 (COVID-19) is mainly based on molecular testing. General population studies have shown that chest Computed Tomography (CT) can also be useful.OBJECTIVE:
The study aims to examine the usefulness of high-resolution chest CT for early diagnosis of patients with suspected COVID-19. DESIGN ANDSETTING:
This is a cross-sectional study from May 1, 2020, to August 31, 2021, at the COVID Hospital, Mexico City.METHODS:
This study examined the clinical, high-resolution chest CT imaging, and laboratory data of 160 patients who were suspected to have COVID-19. Patients with positive Reverse Transcription- Polymerase Chain Reaction (RT-PCR) testing and those with negative RT-PCR testing but clinical data compatible with COVID-19 and positive antibody testing were considered to have COVID-19 (positive). Sensitivity and specificity of CT for diagnosis of COVID-19 were calculated. p < 0.05 was considered significant.RESULTS:
Median age of 160 study patients was 58 years. The proportion of patients with groundglass pattern was significantly higher in patients with COVID-19 than in those without COVID (65.1% versus 0%; P = 0.005). COVID-19 was ruled out in sixteen (11.1%). Only four of the 132 patients diagnosed with COVID-19 (3.0%) did not show CT alterations (p < 0.001). Sensitivity and specificity of CT for COVID-19 diagnosis were 96.7% and 42.8%, respectively.CONCLUSIONS:
Chest CT can identify patients with COVID-19, as characteristic disease patterns are observed on CT in the early disease stage.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
COVID-19
Type of study:
Diagnostic study
/
Observational study
/
Prognostic study
/
Randomized controlled trials
Limits:
Humans
/
Middle aged
Language:
English
Journal:
Curr Med Imaging
Year:
2022
Document Type:
Article
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