Radiological Findings As Predictors of Covid-19 Lung Sequelae: A Systematic Review and Meta-Analysis Publisher Pubmed



Alilou S^{1, 2} ; Zangiabadian M^{3, 4} ; Pouramini A⁵ ; Jaberinezhad M⁶ ; Shobeiri P^{7, 8} ; Ghozy S⁹ ; Haseli S¹⁰ ; Beizavi Z¹¹ Show Affiliations
Source: Academic Radiology Published:2023

Abstract

Rationale and Objectives: This systematic review and meta-analysis aimed to investigate the radiological predictors of post-coronavirus disease 19 (COVID-19) pulmonary fibrosis and incomplete absorption of pulmonary lesions. Materials and Methods: We systematically searched PubMed, EMBASE, and Web of Science for studies reporting the predictive value of radiological findings in patients with post-COVID-19 lung residuals published through November 11, 2022. The pooled odds ratios with a 95% confidence interval (CI) were assessed. The random-effects model was used due to the heterogeneity of the true effect sizes. Results: We included 11 studies. There were 1777 COVID-19-positive patients, and 1014 (57%) were male. All studies used chest computed tomography (CT) as a radiologic tool. Moreover, chest X-ray (CXR) and lung ultrasound were used in two studies, along with a CT scan. CT severity score (CTSS), Radiographic Assessment of Lung Edema score (RALE), interstitial score, lung ultrasound score (LUS), patchy opacities, abnormal CXR, pleural traction, and subpleural abnormalities were found to be predictors of post-COVID-19 sequels. CTSS and consolidations were the most common predictors among included studies. Pooled analysis revealed that pulmonary residuals in patients with initial consolidation are about four times more likely than in patients without this finding (odds ratio: 3.830; 95% CI: 1.811-8.102, I2: 4.640). Conclusion: Radiological findings can predict the long-term pulmonary sequelae of COVID-19 patients. CTSS is an important predictor of lung fibrosis and COVID-19 mortality. Lung fibrosis can be diagnosed and tracked using the LUS. Changes in RALE score during hospitalization can be used as an independent predictor of mortality. © 2023 The Association of University Radiologists