Cargando…
Radiological Findings as Predictors of COVID-19 Lung Sequelae: A Systematic Review and Meta-Analysis
BACKGROUND: 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. METHOD: We systematically searched PubMed, EMBASE, and Web of Science for studies report...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Published by Elsevier Inc. on behalf of The Association of University Radiologists
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10242153/ https://www.ncbi.nlm.nih.gov/pubmed/37491177 http://dx.doi.org/10.1016/j.acra.2023.06.002 |
_version_ | 1785054152325332992 |
---|---|
author | Alilou, Sanam Zangiabadian, Moein Pouramini, Alireza Jaberinezhad, Mehran Shobeiri, Parnian Ghozy, Sherief Haseli, Sara Beizavi, Zahra |
author_facet | Alilou, Sanam Zangiabadian, Moein Pouramini, Alireza Jaberinezhad, Mehran Shobeiri, Parnian Ghozy, Sherief Haseli, Sara Beizavi, Zahra |
author_sort | Alilou, Sanam |
collection | PubMed |
description | BACKGROUND: 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. METHOD: 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, 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. CT severity score (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 (OR: 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. |
format | Online Article Text |
id | pubmed-10242153 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Published by Elsevier Inc. on behalf of The Association of University Radiologists |
record_format | MEDLINE/PubMed |
spelling | pubmed-102421532023-06-06 Radiological Findings as Predictors of COVID-19 Lung Sequelae: A Systematic Review and Meta-Analysis Alilou, Sanam Zangiabadian, Moein Pouramini, Alireza Jaberinezhad, Mehran Shobeiri, Parnian Ghozy, Sherief Haseli, Sara Beizavi, Zahra Acad Radiol Article BACKGROUND: 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. METHOD: 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, 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. CT severity score (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 (OR: 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. Published by Elsevier Inc. on behalf of The Association of University Radiologists 2023-06-06 /pmc/articles/PMC10242153/ /pubmed/37491177 http://dx.doi.org/10.1016/j.acra.2023.06.002 Text en © 2023 Published by Elsevier Inc. on behalf of The Association of University Radiologists. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Alilou, Sanam Zangiabadian, Moein Pouramini, Alireza Jaberinezhad, Mehran Shobeiri, Parnian Ghozy, Sherief Haseli, Sara Beizavi, Zahra Radiological Findings as Predictors of COVID-19 Lung Sequelae: A Systematic Review and Meta-Analysis |
title | Radiological Findings as Predictors of COVID-19 Lung Sequelae: A Systematic Review and Meta-Analysis |
title_full | Radiological Findings as Predictors of COVID-19 Lung Sequelae: A Systematic Review and Meta-Analysis |
title_fullStr | Radiological Findings as Predictors of COVID-19 Lung Sequelae: A Systematic Review and Meta-Analysis |
title_full_unstemmed | Radiological Findings as Predictors of COVID-19 Lung Sequelae: A Systematic Review and Meta-Analysis |
title_short | Radiological Findings as Predictors of COVID-19 Lung Sequelae: A Systematic Review and Meta-Analysis |
title_sort | radiological findings as predictors of covid-19 lung sequelae: a systematic review and meta-analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10242153/ https://www.ncbi.nlm.nih.gov/pubmed/37491177 http://dx.doi.org/10.1016/j.acra.2023.06.002 |
work_keys_str_mv | AT alilousanam radiologicalfindingsaspredictorsofcovid19lungsequelaeasystematicreviewandmetaanalysis AT zangiabadianmoein radiologicalfindingsaspredictorsofcovid19lungsequelaeasystematicreviewandmetaanalysis AT pouraminialireza radiologicalfindingsaspredictorsofcovid19lungsequelaeasystematicreviewandmetaanalysis AT jaberinezhadmehran radiologicalfindingsaspredictorsofcovid19lungsequelaeasystematicreviewandmetaanalysis AT shobeiriparnian radiologicalfindingsaspredictorsofcovid19lungsequelaeasystematicreviewandmetaanalysis AT ghozysherief radiologicalfindingsaspredictorsofcovid19lungsequelaeasystematicreviewandmetaanalysis AT haselisara radiologicalfindingsaspredictorsofcovid19lungsequelaeasystematicreviewandmetaanalysis AT beizavizahra radiologicalfindingsaspredictorsofcovid19lungsequelaeasystematicreviewandmetaanalysis |