ABSTRACT
Background: Computed tomography (CT) characteristics associated with critical outcomes of patients with coronavirus disease 2019 (COVID-19) have been reported. However, CT risk factors for mortality are poorly understood. We aimed to investigate the automatically quantified CT imaging predictors for COVID-19 mortality.Methods: In this retrospective study, laboratory-confirmed COVID-19 patients at Wuhan Central Hospital between December 9, 2019, and March 19, 2020, were included. A novel prognostic biomarker, V-HU score, depicting the volume of total pneumonia infection and the average Hounsfield unit (HU) value of consolidation areas was quantified from CT by an artificial intelligence (AI) system. Cox proportional hazards models were used to investigate risk factors for mortality.Findings: This study included 238 patients (126 survivors and 112 non-survivors). The V-HU marker was an independent predictor (hazard ratio [HR] 2·78, 95% CI 1·50-5·17; p=0·0012) after adjusting for several COVID-19 prognostic indicators significant in univariable analysis. The prognostic performance of the model containing clinical and outpatient laboratory factors was improved by integrating the V-HU marker (c-index: 0·695 versus 0·728; p<0·0001). Older patients (age>=65 years; HR 3·56, 95% CI 1·64-7·71; p=0·0006) and younger patients (age<65 years; HR 4·60, 95% CI 1·92-10·99; p<0·0001) could be risk-stratified by the V-HU marker.Interpretation: A combination of an increased volume of total pneumonia infection and high HU value of consolidation areas showed a strong correlation to COVID-19 mortality, as determined by AI quantified CT. The novel radiologic marker may be used for early risk assessment to prioritize critical care resources for patients at a high risk of mortality.Funding: None.Declaration of Interests: The authors declare no competing interests.Ethics Approval Statement: The study was approved by the Research Ethics Commission of Wuhan Central Hospital, and the requirement for writing informed consent was waived by the Ethics Commission for the emergence of infectious diseases.