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      Prevalence of abnormal cardiovascular magnetic resonance findings in recovered patients from COVID-19: a systematic review and meta-analysis

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          Abstract

          Background

          The prevalence of abnormal cardiovascular magnetic resonance (CMR) findings in recovered coronavirus disease 2019 (COVID-19) patients is unclear. This study aimed to investigate the prevalence of abnormal CMR findings in recovered COVID-19 patients.

          Methods

          A systematic literature search was performed to identify studies that report the prevalence of abnormal CMR findings in recovered COVID-19 patients. The number of patients with abnormal CMR findings and diagnosis of myocarditis on CMR (based on the Lake Louise criteria) and each abnormal CMR parameter were extracted. Subgroup analyses were performed according to patient characteristics (athletes vs. non-athletes and normal vs. undetermined cardiac enzyme levels). The pooled prevalence and 95% confidence interval (CI) of each CMR finding were calculated. Study heterogeneity was assessed, and meta-regression analysis was performed to investigate factors associated with heterogeneity.

          Results

          In total, 890 patients from 16 studies were included in the analysis. The pooled prevalence of one or more abnormal CMR findings in recovered COVID-19 patients was 46.4% (95% CI 43.2%–49.7%). The pooled prevalence of myocarditis and late gadolinium enhancement (LGE) was 14.0% (95% CI 11.6%–16.8%) and 20.5% (95% CI 17.7%–23.6%), respectively. Further, heterogeneity was observed (I 2 > 50%, p < 0.1). In the subgroup analysis, the pooled prevalence of abnormal CMR findings and myocarditis was higher in non-athletes than in athletes (62.5% vs. 17.1% and 23.9% vs. 2.5%, respectively). Similarly, the pooled prevalence of abnormal CMR findings and LGE was higher in the undetermined than in the normal cardiac enzyme level subgroup (59.4% vs. 35.9% and 45.5% vs. 8.3%, respectively). Being an athlete was a significant independent factor related to heterogeneity in multivariate meta-regression analysis (p < 0.05).

          Conclusions

          Nearly half of recovered COVID-19 patients exhibited one or more abnormal CMR findings. Athletes and patients with normal cardiac enzyme levels showed a lower prevalence of abnormal CMR findings than non-athletes and patients with undetermined cardiac enzyme levels.

          Trial registration The study protocol was registered in the PROSPERO database (registration number: CRD42020225234).

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12968-021-00792-7.

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          Most cited references47

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          Bias in meta-analysis detected by a simple, graphical test

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            Quantifying heterogeneity in a meta-analysis.

            The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.
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              Meta-analysis in clinical trials

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                Author and article information

                Contributors
                jinkim0411@naver.com
                khhan@yuhs.ac
                rongzusuh@gmail.com
                Journal
                J Cardiovasc Magn Reson
                J Cardiovasc Magn Reson
                Journal of Cardiovascular Magnetic Resonance
                BioMed Central (London )
                1097-6647
                1532-429X
                3 September 2021
                3 September 2021
                2021
                : 23
                : 100
                Affiliations
                [1 ]GRID grid.412091.f, ISNI 0000 0001 0669 3109, Department of Radiology, Dongsan Hospital, , Keimyung University College of Medicine, ; Daegu, Korea
                [2 ]GRID grid.415562.1, ISNI 0000 0004 0636 3064, Department of Radiology, , Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, ; 50–1 Yonsei-ro, Seodaemun-gu, Seoul, 03722 Korea
                Author information
                http://orcid.org/0000-0001-6714-8358
                http://orcid.org/0000-0002-5687-7237
                http://orcid.org/0000-0002-2078-5832
                Article
                792
                10.1186/s12968-021-00792-7
                8414035
                34479603
                ebd24c0e-4072-4430-9258-235d2194b81a
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 29 March 2021
                : 8 July 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100002509, Keimyung University;
                Award ID: 20200204
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Cardiovascular Medicine
                cardiac magnetic resonance imaging,magnetic resonance imaging,coronavirus disease 2019

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