Cardiac involvement in coronavirus disease 2019 assessed by cardiac magnetic resonance imaging: a meta-analysis

Heart and Vessels(2022)

引用 5|浏览6
暂无评分
摘要
In this systematic review and meta-analysis, we sought to evaluate the prevalence of cardiac involvement in patients with COVID-19 using cardiac magnetic resonance imaging. A literature review was performed to investigate the left ventricular (LV) and right ventricular (RV) ejection fraction (EF), the prevalence of LV late gadolinium enhancement (LGE), pericardial enhancement, abnormality on T1 mapping, and T2 mapping/T2-weighted imaging (T2WI), and myocarditis (defined by modified Lake Louis criteria). Pooled mean differences (MD) between COVID-19 patients and controls for LVEF and RVEF were estimated using random-effects models. We included data from 10.462 patients with COVID-19, comprising 1.010 non-athletes and 9.452 athletes from 29 eligible studies. The meta-analysis showed a significant difference between COVID-19 patients and controls in terms of LVEF [MD = − 2.84, 95% confidence interval (CI) − 5.11 to − 0.56, p < 0.001] and RVEF (MD = − 2.69%, 95% CI − 4.41 to − 1.27, p < 0.001). However, in athletes, no significant difference was identified in LVEF (MD = − 0.74%, 95% CI − 2.41 to − 0.93, p = 0.39) or RVEF (MD = − 1.88%, 95% CI − 5.21 to 1.46, p = 0.27). In non-athletes, the prevalence of LV LGE abnormalities, pericardial enhancement, T1 mapping, T2 mapping/T2WI, myocarditis were 27.5% (95%CI 17.4–37.6%), 11.9% (95%CI 4.1–19.6%), 39.5% (95%CI 16.2–62.8%), 38.1% (95%CI 19.0–57.1%) and 17.6% (95%CI 6.3–28.9%), respectively. In athletes, these values were 10.8% (95%CI 2.3–19.4%), 35.4% (95%CI − 3.2 to 73.9%), 5.7% (95%CI − 2.9 to 14.2%), 1.9% (95%CI 1.1–2.7%), 0.9% (0.3–1.6%), respectively. Both LVEF and RVEF were significantly impaired in COVID-19 patients compared to controls, but not in athletes. In addition, the prevalence of myocardial involvement is not negligible in patients with COVID-19.
更多
查看译文
关键词
COVID-19, Cardiac involvement, Meta-analysis
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要