Author: Hare, S. S.; Tavare, A. N.; Dattani, V.; Musaddaq, B.; Beal, I.; Cleverley, J.; Cash, C.; Lemoniati, E.; Barnett, J.
Title: Validation of the British Society of Thoracic Imaging guidelines for COVID-19 chest radiograph reporting Cord-id: 448tamvr Document date: 2020_6_17
ID: 448tamvr
Snippet: Abstract Aim To validate the British Society of Thoracic Imaging issued guidelines for the categorisation of chest radiographs for coronavirus disease 2019 (COVID-19) reporting regarding reproducibility amongst radiologists and diagnostic performance. Materials and methods Chest radiographs from 50 patients with COVID-19, and 50 control patients with symptoms consistent with COVID-19 from prior to the emergence of the novel coronavirus were assessed by seven consultant radiologists with regards
Document: Abstract Aim To validate the British Society of Thoracic Imaging issued guidelines for the categorisation of chest radiographs for coronavirus disease 2019 (COVID-19) reporting regarding reproducibility amongst radiologists and diagnostic performance. Materials and methods Chest radiographs from 50 patients with COVID-19, and 50 control patients with symptoms consistent with COVID-19 from prior to the emergence of the novel coronavirus were assessed by seven consultant radiologists with regards to the British Society of Thoracic Imaging guidelines. Results The findings show excellent specificity (100%) and moderate sensitivity (44%) for guideline-defined Classic/Probable COVID-19, and substantial interobserver agreement (Fleiss’ k=0.61). Fair agreement was observed for the “Indeterminate for COVID-19†(k=0.23), and “Non-COVID-19†(k=0.37) categories; furthermore, the sensitivity (0.26 and 0.14 respectively) and specificity (0.76, 0.80) of these categories for COVID-19 were not significantly different (McNemar’s test p=0.18 and p=0.67). Conclusion An amalgamation of the categories of “Indeterminate for COVID-19†and “Non-COVID-19†into a single “not classic of COVID-19†classification would improve interobserver agreement, encompass patients with a similar probability of COVID-19, and remove the possibility of labelling patients with COVID-19 as “Non-COVID-19â€, which is the presenting radiographic appearance in a significant minority (14%) of patients.
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