Current best evidence for clinical care (more info)
OBJECTIVES: To assess inter-reader agreements and diagnostic accuracy of chest CT to identify COVID-19 pneumonia in patients with intermediate clinical probability during an acute disease outbreak.
METHODS: From March 20 to April 8, 319 patients (mean age 62.3 years old) consecutive patients with an intermediate clinical probability of COVID-19 pneumonia underwent a chest CT scan. Two independent chest radiologists blinded to clinical information and RT-PCR results retrospectively reviewed and classified images on a 1-5 confidence level scale for COVID-19 pneumonia. Agreements between radiologists were assessed with kappa statistics. Diagnostic accuracy of chest CT compared with RT-PCR assay and patient outcomes was measured using receiver operating characteristics (ROC). Positive predictive value (PPV) and negative predictive value (NPV) for COVID-19 pneumonia were calculated.
RESULTS: Inter-observer agreement for highly probable (kappa: 0.83 [p < .001]) and highly probable or probable (kappa: 0.82 [p < .001]) diagnosis of COVID-19 pneumonia was very good. RT-PCR tests performed in 307 patients were positive in 174 and negative in 133. The areas under the curve (AUC) were 0.94 and 0.92 respectively. With a disease prevalence of 61.2%, PPV were 95.9% and 94.3%, and NPV 84.4% and 77.1%.
CONCLUSION: During acute COVID-19 outbreak, chest CT scan may be used for triage of patients with intermediate clinical probability with very good inter-observer agreements and diagnostic accuracy.
KEY POINTS: • Concordances between two chest radiologists to diagnose or exclude a COVID-19 pneumonia in 319 consecutive patients with intermediate clinical probability were very good (kappa: 0.82; p < .001). • When compared with RT-PCR results and patient outcomes, the diagnostic accuracy of CT to identify COVID-19 pneumonia was high for both radiologists (AUC: 0.94 and 0.92). • With a disease prevalence of 61.2% in the studied population, the positive predictive values of CT for diagnosing COVID-19 pneumonia were 95.9% and 94.3% with negative predictive values of 84.4% and 77.1%.
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Although this study evaluated a single centre population of a country, the data found have clinical relevance to other populations. The study´s objective was to access the concordance rates between two radiologists about results of CT Scan as screening test for Covid19 pneumonia. CT scan was compared with RT-PCR test and high positive predictive value and negative predictive value were found for the interpratation by both radiologists. A total of 319 patients were included in the study. The blinding methods, excluding/including criteria and confounding factors were adequatelly aproached. I consider the article as a high quality paper.
This is a very good study and help us in determining positive cases of COVID 19 based on the imaging results. This study highlights the importance of chest imaging in patients of COVID 19. However they have used RT-PCR to confirm all the patients with CT scans. Now that we are 6 months to 1 year into the pandemic, the testing availability along with sensitivity and specificity of RT-PCR has increased significantly. The best use of this paper is for patients who may have negative COVID 19 testing in an area with high prevalence and positive CT scan findings should be treated as positive for COVID 19 and these patients should receive appropriate therapy for COVID 19. Overall, this is a very well done study and very informative.
This is an analysis of the sensitivity and specificity of CT Chest for diagnosis of SARS-CoV2 infection in a population with 61% prevalence of infection during a surge in the pandemic in France. In this setting, CT Chest performs well.
This is a well performed study, with clinical relevant and valuable information. Interestingly the two raters have different professional experience, that facilitates the generalizability of the results. The discussion takes into account the flaws of the study.
This is an observational study on the effectiveness of CT for the diagnosis of uncertain COVID-19; It seems to me that it is too tied to observer-dependent criteria,