Practical Clinical and Radiological Models to Diagnose COVID-19 on Chest CT in a French Multicentric Emergency Population

P Schuster, A Crombé, H Nivet, A Berger, L Pourriol, N Favard, A Chazot, F Alonzo-Lacroix, E Youssof, A Cheikh, J Balique, B Porta, F Petitpierre, G Bouquet, C Mastier, F Bratan, J Bergerot, V Thomson, N Banaste, G Gorincour

Like Comment

Received date: 2nd October 2020

Our aim was to develop practical models built with simple clinical-radiological features to facilitate COVID-19 diagnosis. To do so, 513 consecutive adult patients suspected of having COVID-19 from 15 emergency departments from 03/13/2020 to 04/14/2020 were included (244 [47.6%] with a positive RT-PCR). Chest CTs were immediately and prospectively analysed by on-call teleradiologists (OCTR) and systematically reviewed within one week by another senior teleradiologist. Each OCTR reading was concluded using a 5-point scale: normal, non-infectious, infectious non-COVID-19, indeterminate and highly suspicious of COVID-19. The senior reading reported the lesions’ semiology, distribution, extent and differential diagnoses. Multivariate stepwise logistic regression (Step-LR) and classification tree (CART) models to predict a positive RT-PCR were trained on 412 patients, validated on an independent cohort of 101 patients and compared with the OCTR performances (295 and 71 with available clinical data, respectively). Regarding models elaborated on radiological variables alone, best performances were reached with the CART model (i.e., AUC=0.92 versus 0.88 for OCTR) while step-LR provided the highest AUC with clinical-radiological variables (0.93 versus 0.86 for OCTR). Hence, these two simple models, depending on the availability of clinical data, could be used by any radiologist to support their conclusion in case of COVID-19 suspicion.

Read in full at RSQ.

This is an abstract of a preprint hosted on a preprint server, which is currently undergoing peer review at Scientific Reports. The findings have yet to be thoroughly evaluated, nor has a decision on ultimate publication been made. Therefore, the results reported should not be considered conclusive, and these findings should not be used to inform clinical practice, or public health policy, or be promoted as verified information.

Scientific Reports

-, Nature Portfolio, Springer Nature