Abstract
BACKGROUND: Computed tomography (CT) analysis of lung morphology has significantly advanced our understanding of acute respiratory distress syndrome (ARDS). During the Coronavirus Disease 2019 (COVID-19) pandemic, CT imaging was widely utilized to evaluate lung injury and was suggested as a tool for predicting patient outcomes. However, data specifically focused on patients with ARDS admitted to intensive care units (ICUs) remain limited. METHODS: This retrospective study analyzed patients admitted to ICUs between March 2020 and November 2022 with moderate to severe COVID-19 ARDS. All CT scans performed within 48 h of ICU admission were independently reviewed by three experts. Lung injury severity was quantified using the CT Severity Score (CT-SS; range 0-25). Patients were categorized as having severe disease (CT-SS ≥ 18) or non-severe disease (CT-SS < 18). The primary outcome was all-cause mortality at 90 days. Secondary outcomes included ICU mortality and medical complications during the ICU stay. Additionally, we evaluated a computer-assisted CT-score assessment using artificial intelligence software (CT Pneumonia Analysis(®), SIEMENS Healthcare) to explore the feasibility of automated measurement and routine implementation. RESULTS: A total of 215 patients with moderate to severe COVID-19 ARDS were included. The median CT-SS at admission was 18/25 [interquartile range, 15-21]. Among them, 120 patients (56%) had a severe CT-SS (≥ 18), while 95 patients (44%) had a non-severe CT-SS (< 18). The 90-day mortality rates were 20.8% for the severe group and 15.8% for the non-severe group (p = 0.35). No significant association was observed between CT-SS severity and patient outcomes. CONCLUSION: In patients with moderate to severe COVID-19 ARDS, systematic CT assessment of lung parenchymal injury was not a reliable predictor of 90-day mortality or ICU-related complications.