AUTHOR=Li Xiang , Li Nannan , Chen Zhen , Ye Ling , Zhang Ling , Jin Dakai , Gao Liangxin , Liu Xinhui , Lai Bolin , Yao Jiawen , Guo Dazhou , Zhang Hua , Lu Le , Xiao Jing , Huang Lingyun , Ai Fen , Wang Xiang TITLE=RETRACTED: CT-Based Risk Factors for Mortality of Patients With COVID-19 Pneumonia in Wuhan, China: A Retrospective Study JOURNAL=Frontiers in Radiology VOLUME=1 YEAR=2021 URL=https://www.frontiersin.org/journals/radiology/articles/10.3389/fradi.2021.661237 DOI=10.3389/fradi.2021.661237 ISSN=2673-8740 ABSTRACT=

Purpose: 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 have not been directly reported. We aim to determine the CT-based quantitative 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 (V) of total pneumonia infection and the average Hounsfield unit (HU) of consolidation areas was automatically quantified from CT by an artificial intelligence (AI) system. Cox proportional hazards models were used to investigate risk factors for mortality.

Results: The study included 238 patients (women 136/238, 57%; median age, 65 years, IQR 51–74 years), 126 of whom were survivors. The V-HU score was an independent predictor (hazard ratio [HR] 2.78, 95% confidence interval [CI] 1.50–5.17; p = 0.001) 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 score (c-index: 0.695 vs. 0.728; p < 0.001). Older patients (age ≥ 65 years; HR 3.56, 95% CI 1.64–7.71; p < 0.001) and younger patients (age < 65 years; HR 4.60, 95% CI 1.92–10.99; p < 0.001) could be further risk-stratified by the V-HU score.

Conclusions: 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.