Typical chest CT features can determine the severity of COVID-19: A systematic review and meta-analysis of the observational studies

Background: It remains unclear whether a specific chest CT characteristic is associated with the clinical severity of COVID-19. This meta-analysis was performed to assess the relationship between different chest CT features and severity of clinical presentation in COVID-19. Methods: PubMed, Embase, Scopus, web of science databases (WOS), Cochrane library, and Google scholar were searched up to May 19, 2020 for observational studies that assessed the relationship of different chest CT manifestations and the severity of clinical presentation in COVID-19 infection. Risk of bias assessment was evaluated applying the Newcastle-Ottawa Scale. A random-effects model or fixed-effects model, as appropriately, were used to pool results. Heterogeneity was assessed using Forest plot, Cochran?s Q test, and I2. Publication bias was assessed applying Egger?s test. Results: A total of 18 studies involving 3323 patients were included. Bronchial wall thickening (OR 11.64, 95% CI 1.81?74.66) was more likely to be associated with severe cases of COVID-19 infection, followed by crazy paving (OR 7.60, 95% CI 3.82?15.14), linear opacity (OR 3.27, 95% CI 1.10?9.70), and GGO (OR 1.37, 95% CI 1.08?1.73). However, there was no significant association between the presence of consolidation and severity of clinical presentation (OR 2.33, 95% CI 0.85?6.36). Considering the lesion distribution bilateral lung involvement was more frequently associated with severe clinical presentation (OR 3.44, 95% CI 1.74?6.79). Conclusions: Our meta-analysis of observational studies indicates some specific chest CT features are associated with clinical severity of COVID-19.