Role of cardiovascular computed tomography parameters and lungs findings in predicting severe COVID-19 patients: a single-centre retrospective study

Abstract Background During the coronavirus disease 2019 (COVID-19) pandemic, most patients experienced various respiratory and cardiovascular problems, and their health suddenly deteriorated despite active treatment. Many parameters have been used to assess patient health status. However, few have c...

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Bibliographic Details
Main Authors: Mahmoud Mousa, Marwan Matar, Mohammad Matar, Sadi Jaber, Fouad S. Jaber, Yasser Al Ajerami, Amjad Falak, Mohammed Abujazar, Ammar A. Oglat, Hammoda Abu-Odah
Format: Article
Language:English
Published: SpringerOpen 2022-10-01
Series:The Egyptian Journal of Radiology and Nuclear Medicine
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Online Access:https://doi.org/10.1186/s43055-022-00910-0
Description
Summary:Abstract Background During the coronavirus disease 2019 (COVID-19) pandemic, most patients experienced various respiratory and cardiovascular problems, and their health suddenly deteriorated despite active treatment. Many parameters have been used to assess patient health status. However, few have considered chest computed tomography (CCT) and lung findings to predict patient outcomes. This single-centre retrospective observational study was conducted between December 2020 and March 2021 at the European Gaza Hospital to predict the mortality of COVID-19 patients based on their CCT parameters and lung involvement scores. Results A total of 152 patients with severe respiratory symptoms were admitted during the study period, of which 93 (61.2%) improved and 59 (38.8%) died. Deceased patients showed a significantly higher right pulmonary diameter, cardiothoracic ratio, and ground glass with crazy paving opacity (p < 0.05). A cardiothoracic ratio ≥ 0.49 was associated with significantly higher mortality risk (p < 0.05) and a fourfold higher hazard ratio (p < 0.05) compared to < 0.49. Conclusions Assessing cardiac indices on CCT could provide prognostic information and guide physicians in patient management and risk stratification.
ISSN:2090-4762