Radiological Findings as Predictors of COVID-19 Lung Sequelae : A Systematic Review and Meta-analysis
Copyright © 2023 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved..
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.
Medienart: |
E-Artikel |
---|
Erscheinungsjahr: |
2023 |
---|---|
Erschienen: |
2023 |
Enthalten in: |
Zur Gesamtaufnahme - volume:30 |
---|---|
Enthalten in: |
Academic radiology - 30(2023), 12 vom: 01. Dez., Seite 3076-3085 |
Sprache: |
Englisch |
---|
Beteiligte Personen: |
Alilou, Sanam [VerfasserIn] |
---|
Links: |
---|
Themen: |
Coronavirus disease 2019 |
---|
Anmerkungen: |
Date Completed 01.12.2023 Date Revised 04.12.2023 published: Print-Electronic Citation Status MEDLINE |
---|
doi: |
10.1016/j.acra.2023.06.002 |
---|
funding: |
|
---|---|
Förderinstitution / Projekttitel: |
|
PPN (Katalog-ID): |
NLM359913466 |
---|
LEADER | 01000naa a22002652 4500 | ||
---|---|---|---|
001 | NLM359913466 | ||
003 | DE-627 | ||
005 | 20231226081905.0 | ||
007 | cr uuu---uuuuu | ||
008 | 231226s2023 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1016/j.acra.2023.06.002 |2 doi | |
028 | 5 | 2 | |a pubmed24n1199.xml |
035 | |a (DE-627)NLM359913466 | ||
035 | |a (NLM)37491177 | ||
035 | |a (PII)S1076-6332(23)00297-0 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 1 | |a Alilou, Sanam |e verfasserin |4 aut | |
245 | 1 | 0 | |a Radiological Findings as Predictors of COVID-19 Lung Sequelae |b A Systematic Review and Meta-analysis |
264 | 1 | |c 2023 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a ƒaComputermedien |b c |2 rdamedia | ||
338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
500 | |a Date Completed 01.12.2023 | ||
500 | |a Date Revised 04.12.2023 | ||
500 | |a published: Print-Electronic | ||
500 | |a Citation Status MEDLINE | ||
520 | |a Copyright © 2023 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved. | ||
520 | |a 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 | ||
520 | |a 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 | ||
520 | |a 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) | ||
520 | |a 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 | ||
650 | 4 | |a Meta-Analysis | |
650 | 4 | |a Systematic Review | |
650 | 4 | |a Journal Article | |
650 | 4 | |a Review | |
650 | 4 | |a Coronavirus disease 2019 | |
650 | 4 | |a High-resolution computed tomography | |
650 | 4 | |a Pulmonary fibrosis | |
650 | 4 | |a Pulmonary sequelae | |
650 | 4 | |a SARS-CoV-2 | |
700 | 1 | |a Zangiabadian, Moein |e verfasserin |4 aut | |
700 | 1 | |a Pouramini, Alireza |e verfasserin |4 aut | |
700 | 1 | |a Jaberinezhad, Mehran |e verfasserin |4 aut | |
700 | 1 | |a Shobeiri, Parnian |e verfasserin |4 aut | |
700 | 1 | |a Ghozy, Sherief |e verfasserin |4 aut | |
700 | 1 | |a Haseli, Sara |e verfasserin |4 aut | |
700 | 1 | |a Beizavi, Zahra |e verfasserin |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Academic radiology |d 1995 |g 30(2023), 12 vom: 01. Dez., Seite 3076-3085 |w (DE-627)NLM087676818 |x 1878-4046 |7 nnns |
773 | 1 | 8 | |g volume:30 |g year:2023 |g number:12 |g day:01 |g month:12 |g pages:3076-3085 |
856 | 4 | 0 | |u http://dx.doi.org/10.1016/j.acra.2023.06.002 |3 Volltext |
912 | |a GBV_USEFLAG_A | ||
912 | |a GBV_NLM | ||
951 | |a AR | ||
952 | |d 30 |j 2023 |e 12 |b 01 |c 12 |h 3076-3085 |