Clinical data from 513 patients supporting: The accuracy of teleradiologists in diagnosing COVID-19 based on a French multicentric emergency cohort

<b>Summary</b>This metadata record provides details of the data supporting the claims of the related manuscript: “The accuracy of teleradiologists in diagnosing COVID-19 based on a French multicentric emergency cohort”.The data consist of a single Excel .xlsx format spreadsheet.The related study aimed to evaluate the accuracy of diagnoses of COVID-19 based on chest CT as well as interobserver agreement between teleradiologists during on-call duty and senior radiologists in suspected COVID-19 patients.<b>Patient selection and study design</b> At our emergency teleradiology center, all consecutive patients who were suspected, by a board-certified emergency physician, to have COVID-19, and who underwent both chest CT imaging and RT-PCR from 03/13/2020 to 04/14/2020 in 15 French emergency departments, were included. The examinations took place during on-call duty periods between 6pm and 8.30am on weekdays and 24 hours a day on weekends. A COVID-19 dedicated workflow was implemented, which consisted of a standardised COVID-19 CT request form for the requesting physician, structured and standardised radiological reports, and a systematic review by a senior radiologist. <b>CT techniques</b> Chest CT examinations were performed using a 16, 64 or 80-detector row CT scanner with a standardised non-contrast chest CT COVID-19 protocol for all hospitals. If pulmonary embolism was suspected, a CT pulmonary angiographic protocol with bolus-tracking intravenous iodine contrast agent administration at a rate of 3–4 mL/sec was used instead. The on-site requesting physician supervised contrast administration if needed. <b>Radiology interpretation protocol</b> The teleradiology interpretation protocol met the current French recommendations for teleradiology practice. Reports and requests with clinical data for the interpretation of COVID-19 chest CT images were received from partner hospitals at our teleradiology center, using teleradiology software (ITIS; Deeplink Medical). The images were securely transferred over a virtual private network (VPN) to a local picture archiving and communication system for interpretation (PACS; Carestream Health 12). Images were interpreted by a teleradiologist (TR) in two dedicated emergency reading rooms during the study period. The panel of TRs consisted of 106 senior radiologists with at least five years of emergency imaging experience (mean length of practice: seven years) and 45 junior radiologists (<i>i.e</i>., residents) with between three and five years of emergency imaging experience (mean length of practice: 4 years). TRs operated an on-call rota in groups of at least five TRs per night, and the report turn-around times were recorded. CT examinations were systematically reviewed within a week after each on-call period by a senior radiologist (15 senior radiologists; mean length of practice: 12.1 years) who was not involved in the on-call duty period, blinded to RT-PCR results and the first reader report, and unblinded to the patient’s medical history. <b>Clinical data</b> Clinical information was prospectively provided by emergency physicians upon presentation and was collected using the teleradiology software as a dedicated COVID-19 CT request form (ITIS; Deeplink Medical). This clinical information included: age; gender; active smoking; significant medical history; recent medication with anti-inflammatory drugs; time since onset of symptoms (categorised as: &lt;1 week, 1–2 weeks, ≥2 weeks); oxygen saturation (categorised as: ≥95%, 90–95% and &lt;90%); dyspnoea; fever (³38°C); cough; asthenia; headache; and ear, nose and throat symptoms. The RT-PCR results were retrospectively collected from the patients’ electronic medical records by each partner hospital. The initial RT-PCR was considered as the standard of reference.<b></b> Discrepancies between the RT-PCR results and the score from the second reading were reviewed by contacting hospitals and investigating patients’ outcome, in order to determine whether a second chest CT and/or a second RT-PCR test had been performed. <b>CT image analysis</b> Six common radiological features were extracted from the specific, structured COVID-19 chest-CT reports by the first and second independent readers. These features included the presence of GGO, consolidation, fibrosis (with traction bronchiectasis and architectural distortions), intralobular reticulations, and extent of abnormalities (categorised as low [&lt;25%], moderate [25-50%] or high [&gt;50%]). Additionally, the second reading included an assessment of image quality (categorised as good, moderate or poor) and the following radiological features: (a) underlying pulmonary disease (categorised as emphysema, lung cancer, interstitial lung disease, pleural lesions, bronchiectasis); (b) GGO pattern (categorised as rounded and non-rounded GGO); (c) consolidation pattern (categorized as rounded, non-rounded consolidations and subpleural bands); (d) predominant pattern (categorised as GGO or consolidation); (e) distribution pattern of lesions (categorised as peripheral predominant, central predominant, or mixed); (f) bilateral lesions; (g) diffuse lesions (<i>i.e</i>., five lobes involved); (h) basal predominant lesions; (i) pleural effusion (categorised as uni- or bilateral); (j) adenomegaly (defined as lymph node with short axis &gt; 10 mm); (k) bronchial wall thickening (further categorised as lobar/segmental or diffuse); (l) airways secretions; (m) tree-in-bud centrilobular micronodules; and (n) pulmonary embolism. Each reading was categorised using a five-point score, adapted from the recommendations of the Société Française de Radiologie (SFR): (1) normal; (2) non-infectious findings; (3) infectious findings but not consistent with COVID-19 infection; (4) consistent with COVID-19 infection; (5) typical appearance of COVID-19 infection. To support the conclusions of the TRs, all radiologists underwent a two-hour e-learning session based on reported chest-CT findings associated with COVID-19 from the literature, which was made publicly available on the 7^th April. A private medical discussion group (PandaLab) was used at the onset of the outbreak, such that on-call TRs could discuss and share images from their cases with all TRs who were not on call, prior to completing their reports.<b>Additional manuscript using this data</b>The authors of the manuscript described above also have a second manuscript which uses this data and is currently under review. The manuscript is titled: "Practical Clinical and Radiological Models to Diagnose COVID-19 on Chest CT in a French Multicentric Emergency Population", and aims to develop practical models built with simple clinical-radiological features to facilitate COVID-19 diagnosis. When this manuscript is published, it will be added as a Reference on this figshare record.