Chest radiography predictor of COVID-19 adverse outcomes. A lesson learnt from the first wave

Flor, N.; Casazza, G.; Saggiante, L.; Savoldi, A. P.; Vitale, R.; Villa, P.; Martucci, F.; Ballone, E.; Castelli, A.; Brambilla, A. M.

Aim To assess the role of a severity score based on chest radiography (CXR) in predicting the risk of adverse outcomes in coronavirus disease 2019 (COVID-19). Materials and methods Of the patients who presented to Hospital between 21 February and 31 March 2020, patients with a laboratory confirmation of COVID-19 who also underwent a CXR were included in the study. To quantify the extent of lung involvement, each CXR image was given a score ([Blinded] score), ranging from 0 to 24, depending on the presence of reticular pattern and/or ground-glass opacities and/or extensive consolidations in each of the 12 areas in which the lungs were divided. The score was calculated by an expert radiologist, blinded to laboratory tests. The ability of the [Blinded] score to predict hospital admission and mortality, after adjusting for some variables (age; gender; comorbidities; time between symptoms onset and admission), using univariate and multivariate statistical analysis was investigated retrospectively. Results Among the 554 patients, 115 of which (21%) had a negative CXR, the in-hospital mortality was 16% (90/554). At univariate analysis, age, gender, and comorbidities were significant predictors of mortality and hospital admission. At multivariate analysis, adjusting for age and gender, the [Blinded] score was an independent predictor of mortality and hospitalisation. In particular, patients with a [Blinded] score ≥ 9 had a mortality risk five-times higher than those with a lower score. Other independent predictors of mortality were gender and age. Conclusions The CXR [Blinded] score was an independent predictive factor of both in-hospital mortality and hospital admission.