Iranian Journal of Medical Sciences

Document Type : Review Article

Authors

1 Community Based Psychiatric Care Research Center, Shiraz University of Medical Sciences, Shiraz, Iran

2 Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran

3 HIV/AIDs Research Center, Shiraz University of Medical Sciences, Shiraz, Iran

Abstract

Background: It has been found that the new coronavirus can affect various parts of the cardiovascular system. Cardiovascular complications caused by coronavirus disease 2019 (COVID-19) are often serious and can increase the mortality rate among infected patients. This study aimed to investigate the prevalence of cardiovascular complications in COVID-19 adult patients. 
Methods: A systematic review and meta-analysis of observational studies published in English were conducted between December 2019 and February 2021. A complete search was performed in PubMed (PubMed Central and MEDLINE), Google Scholar, Cochrane Library, Science Direct, Ovid, Embase, Scopus, CINAHL, Web of Science, and WILEY, as well as BioRXiv, MedRXiv, and gray literature. A random effect model was used to examine the prevalence of cardiovascular complications among COVID-19 patients. The I2 test was used to measure heterogeneity across the included studies.
Results: A total of 74 studies involving 34,379 COVID-19 patients were included for meta-analysis. The mean age of the participants was 61.30±14.75 years. The overall pooled prevalence of cardiovascular complications was 23.45%. The most prevalent complications were acute myocardial injury (AMI) (19.38%, 95% CI=13.62-26.81, test for heterogeneity I2=97.5%, P<0.001), arrhythmia (11.16%, 95% CI=8.23-14.96, test for heterogeneity I2=91.5%, P<0.001), heart failure (HF) (7.56%, 95% CI=4.50-12.45, test for heterogeneity I2=96.3%, P<0.001), and cardiomyopathy (2.78%, 95% CI=0.34-9.68). The highest pooled prevalence of cardiac enzymes was lactate dehydrogenase (61.45%), troponin (23.10%), and creatine kinase-myocardial band or creatine kinase (14.52%).
Conclusion: The high prevalence of serious cardiovascular complications in COVID-19 patients (AMI, arrhythmia, and HF) necessitates increased awareness by healthcare administrators.

Keywords

What’s Known

There are no large-scale review studies investigating the pooled prevalence of cardiovascular complications associated with coronavirus disease 2019 (COVID-19), including underlying medical conditions and common cardiovascular signs and symptoms. The reported common cardiovascular consequences of infection with the new coronavirus vary depending on the number and types of reviewed articles.

What’s New

The overall pooled prevalence of cardiovascular complications was about 23.45%. The most prevalent cardiovascular complications in COVID-19 patients were, in descending order, acute cardiac/myocardial injury, cardiac arrhythmia, and heart failure. Cardiomyopathy and myocarditis have rarely been reported.

Introduction

At the beginning of the coronavirus disease 2019 (COVID-19) pandemic, the predominance of clinical symptoms of the respiratory system led to the belief that the coronavirus was targeting its victims’ lungs. 1 Later, it was established that the virus can spread throughout the body and directly attack other organs, including the heart. Cardiac and pulmonary cells are covered by a protein molecule called angiotensin II enzyme convertor (ACE2), through which the virus can enter the cells. In addition, as the heart and the lungs are closely related, the occurrence of pneumonia puts extra pressure on the heart, which may lead to cardiac injury with the signs and symptoms of cardiac disorders. 2 - 4 Previous viral epidemics, e.g., severe acute respiratory syndrome (SARS), were accompanied by cardiac complications, including arrhythmia, myocardial injury, and cardiomegaly. 5 , 6 Likewise, the consequences of Middle East respiratory syndrome (MERS) were reported to include cardiac disorders, myocarditis, cardiomegaly, heart tissue damage, and heart failure (HF). 7 - 9 Compared to COVID-19, both SARS and MERS have been less infectious but had higher mortality rates. 10 , 11 SARS-coronaviruses (SARS-CoV-2) and MERS-coronaviruses (MERS-CoV-2) have similar pathogenicity and can lead to myocardial damage which complicates the treatment of patients. 12

Several studies showed that, as a result of their systemic inflammatory response and immune system disorders, COVID-19 patients are more prone to cardiovascular complications. 4 , 13 , 14 Arrhythmia and cardiomyopathy (CMP) are among the cardiac complications associated with COVID-19. 15 - 17 It appears that older individuals with underlying medical conditions, including hypertension (HTN), diabetes mellitus (DM), liver diseases, kidney diseases, malignancies, and cardiovascular diseases (CVD) are at greater risk of mortality. 18 - 20 In a study of 274 patients with COVID-19, 89 had suffered acute heart injury, 43 suffered acute heart failure, 83 had increased levels of cardiac troponin (cTn), and 116 had increased levels of lactate dehydrogenase. 21 Heart injury is a dominant complication that affects 20% to 30% of hospitalized patients and accounts for 40% of the mortality rate. 22 The prevalence of acute myocardial injury in COVID-19 patients were reported to range from 17% to 37.54%. 23 , 24 The findings of several studies showed that there is an association between mortality and patients suffering from both cardiac injury and COVID-19. 13 , 16

According to official reports, acute myocardial injury, HF, cardiomegaly, various types of arrhythmias, blood pressure disorders, thromboembolism, inflammation of small and large vessels, circulatory collapse, and elevated rate of biomarkers indicative of cardiovascular injury are prevalent disorders in patients with COVID-19. 17 , 22 , 25 In a study by Xie and colleagues, of the 733 patients infected with the coronavirus, 357 suffered heart injury, and an increase in their cTn levels was observed. 26 Approximately, 45% of COVID-19 patients had above-normal levels of cTn. 27 Similarly, in another study, 107 of the 463 patients with COVID-19 had above-normal levels of cTn. 28 In a systematic review of 22 studies, the total incidence of HF, myocardial injury, and arrhythmia in COVID-19 patients was 22.24%, 17.85%, and 10.14%, respectively. 29 In a retrospective study, of the 339 patients infected with the new coronavirus, 70, 58, and 35 patients were found to have experienced acute heart injury, HF, and arrhythmia, respectively. 30 These patients were also at risk of complications such as myocarditis and reduced ejection fraction. 4 , 31 - 35 Cases of cardiac tamponade were also reported. 4 , 36 , 37

The cardiovascular consequences of COVID-19 are often serious, and increased awareness can significantly aid the treatment and care of those infected. Several studies have addressed cardiovascular complications in COVID-19 patients. 16 , 17 , 21 , 28 , 30 , 32 , 34 - 41 Organized presentation of the findings of these studies in the form of a systematic review and meta-analysis can be helpful in raising awareness of the complications, and early diagnosis and treatment. Therefore, the present study aimed to investigate the prevalence of different types of cardiovascular complications in COVID-19 adult patients through a systematic review and meta-analysis.

Materials and Methods

Search Strategy

A systematic review and meta-analysis were conducted using observational studies published in English between December 2019 and February 2021. A complete search was performed in PubMed (PubMed Central and MEDLINE), Google Scholar, Cochrane Library, Science Direct, Ovid, Embase, Scopus, CINAHL, Web of Science, and WILEY, as well as BioRXiv, MedRXiv, and gray literature. The sources were managed to remove duplicates using Mendeley reference management software version 1.19.8 (Elsevier, Amsterdam, The Netherlands). Using the syntax of various databases, the authors searched for medical subject headings (MeSH), keywords, and phrases in English: “COVID 19 virus OR COVID-19 virus OR coronavirus disease 2019 virus OR SARS-CoV-2 OR 2019 novel coronavirus OR 2019-nCoV AND comorbidities OR cardiovascular complications OR cardiovascular diseases OR cardiac injury OR myocardial damage OR myocarditis OR Cardiovascular outcome OR cardiac arrhythmias (dysrhythmia) OR heart failure OR troponin, lactate dehydrogenase (LDH), creatine kinase (CK) OR creatine kinase-myocardial band (CK-MB), etc.” An example of a search syntax for Scopus has been provided in appendix 1.

Two of the authors (HH and RI) reviewed the articles independently. Any inconsistencies were resolved by the third author (CT). The articles underwent full-text screening according to the inclusion and exclusion criteria. Moreover, the reference lists of the included articles were reviewed manually for other relevant articles that may have been overlooked in the electronic search. All observational studies, published in English, with a retrospective, prospective, and cross-sectional designs focusing on the clinical characteristics and laboratory outcomes of COVID-19-induced cardiovascular complications were used for analysis. Repeated and irrelevant studies and studies of animals and children were excluded. Besides, studies in which the target variables were measured using methods such as biopsy/autopsy were excluded from the analysis.

Data Extraction

Two of the authors independently extracted data from the included studies. To minimize selection bias, the articles were verified by the second and fourth authors. The extracted data included the name of the first author, year and month of publication, research site, research method, sample size, average age, male-to-female ratio, underlying medical condition (healthy, CVD, kidney and liver disorders, DM, chronic pulmonary diseases [CPD]), signs and symptoms, cardiovascular complications (tachycardia, bradycardia, hypotension, chest pain, acute myocardial injury, myocarditis, HF, cardiac tamponade, CMP, cardiac dysrhythmia), and cardiac markers (cTn, LDH, CK, CK-MB). The present study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines 42 and was approved by the Ethics Committee of Shiraz University of Medical Sciences, Shiraz, Iran, (code: IR.SUMS.REC.1399.763).

Statistical Analysis

The distribution of target variables, as reported by the included studies, were presented in the form of descriptive variables and expressed as percentages and mean±SD. A random effect analysis was performed to examine the prevalence of cardiovascular complications in COVID-19 patients using the package meta (R version 4.0.2, 2020-06-22, Copyright 2020, The R Foundation for Statistical Computing Platform). The I2 test was used to evaluate heterogeneity across the included studies. A value of 0% indicated no observed heterogeneity, and larger values showed increasing heterogeneity (low: 0-25%, moderate: 25-50%, high: 50-75%). To explain the heterogeneity of the sources, meta-regression was applied based on the country, sex, and age of the patients. Linear regression test of funnel plot asymmetry was used to examine publication bias. The cut-off for type I error (statistically significant results) was set at 0.05.

Results

Description of Studies

In total, 3,873 records were screened through Web of Science (n=978), Scopus (n=579), PubMed (n=196), Google Scholar, and other sources (n=2,120). A total of 228 publications were identified in the search after duplicates, and unrelated titles were removed. Out of these, 74 studies involving a total of 34,379 participants were found to be eligible for the systematic review and meta-analysis (figure 1). The analysis included all the studies published from December 2019 until February 2021. All studies were observational, of which 67 were retrospective cohorts. As shown in table 1, the majority of the studies were conducted in China (n=50, 67.56%) followed by the USA (n=9, 12.16%), Italy (n=7, 9.45%), Spain (n=2, 2.70%), Germany (n=1, 1.35%), South Korea (n=1, 1.35%), UK (n=1, 1.35%), Mexico (n=1, 1.35%), Iran (n=1, 1.35%), and a multi-country study (n=1, 1.35%). The mean age of the participants in these studies was 61.30±14.75 years. A summary of the reviewed studies is presented in table 1.

Figure 1. The flow diagram shows the study selection strategies according to the PRISMA guidelines.

No Author Country Study method N Sex (M/F ratio) Comorbidities (N) Cardiovascular symptoms (N) Cardiovascular complications (N) Cardiac markers rise (N)
1 Chen et al. 43 China Retrospective cohort 99 2.09 CVD: 40, CPD: 1 CP: 2 HF: 1 LDH: 75, CK-MB: 13
2 Zhang et al. 44 China Retrospective cohort 82 1.60 HTN: 46, HD: 17, CKD: 4, CLD: 2, DM: 15, CPD: 12 CP: 36 ACI: 73 Tn: 52, LDH: 68, CK-MB: 21
3 Wang et al. 18 China Retrospective cohort 138 1.19 CVD: 20, HTN: 43, CKD: 4, CLD: 4, DM: 14, CPD: 4 HR: 88, MAP: 90 AMI: 10, Arrhythmia: 23 NR
4 Liu et al. 45 China Retrospective cohort 291 0.84 HTN: 54, CHD: 12, HF: 1, Arrhythmia: 2, DM: 22 CP: 1, HR: 84, SBP: 124, Palpitation: 3 ACI: 15 Tn: 15
5 Hui et al. 46 China Retrospective cohort 41 0.86 Arrhythmia: 1, CAD: 3, HTN: 5, DM: 2 Tachycardia: 3 Arrhythmia: 2, ACI: 4 Tn: 4
6 Huang et al. 12 China Prospective cohort 41 2.72 HTN: 6, CVD: 6, CLD: 1, DM: 8, CPD: 1 SBP: 125 ACI: 5 Tn: 5, LDH: 29, CK-MB: 13
7 Yang et al. 47 China Retrospective cohort 52 2.05 CHD: 5, DM: 9, CPD: 4 CP: 1, HR: 89 ACI: 12 NR
8 Ma et al. 32 China Retrospective Cohort 84 1.33 HTN: 12, Cardiopathy: 5, CKD: 1, CLD: 11, DM: 10, CPD: 5 CP: 1, Bradycardia: 3, Tachycardia: 3 Myocarditis: 4, Arrhythmia: 4, AMI: 13 Tn: 9
9 Wang et al. 30 China Retrospective cohort 339 0.95 HTN: 133, CVD: 53, CKD: 13, CLD: 2, DM: 54, CPD: 21 CP: 88, HR: 82, MAP: 94 ACI: 70, HF: 58 Arrhythmia: 35 NR
10 Liu et al. 19 China Retrospective cohort 137 0.80 HTN: 13, CVD: 10, DM: 14, CPD: 2 Palpitation: 10 NR NR
11 Zhou et al. 41 China Retrospective cohort 191 1.65 HTN: 58, CHD: 15, CKD: 2, DM: 36, CPD: 6 NR HF: 44, ACI: 33 Tn: 24, LDH: 123, CK-MB: 22
12 Wei et al. 48 China Prospective cohort 101 1.14 HTN: 21, CAD: 5, DM: 14, CPD: 1 CP: 11 AMI: 16 Tn: 16
13 Shi et al. 49 China Retrospective cohort 671 0.92 HTN: 199, CHD: 60, CHF: 22, Arrhythmia: 7, CKD: 28, DM: 97, CPD: 23 NR AMI: 20, HF: 12 NR
14 Zheng et al. 14 China Retrospective cohort 34 2.09 HTN: 22, CVD: 4, CKD: 2, CLD: 4, DM: 8, CPD: 2 HR: 79, MAP: 89 ACI: 13 NR
15 Chen et al. 21 China Retrospective cohort 274 1.66 HTN: 93, CVD: 23, CHF: 1, CKD: 4, CLD: 11, DM: 47, CPD: 18 CP: 103, HR: 94, MAP: 129 ACI: 89, HF: 43 Tn: 83, LDH: 116
16 Hong et al. 38 Korea Retrospective cohort 98 0.63 CVD: 11, HTN: 30, CLD: 1, DM: 9, CPD: 3 HR: 84.7, MAP: 96.1 ACI: 11 LDH: 47, CK-MB: 11
17 Zhang et al. 50 China Retrospective cohort 221 0.95 HTN: 54, CVD: 22, CKD: 6, CLD: 7, DM: 22, CPD: 6 HR: 84, MAP: 90 ACI: 17, Arrhythmia: 24 NR
18 Wan et al. 51 China Retrospective cohort 135 1.14 HTN: 13, CVD: 7, CLD: 2, DM: 12, CPD: 1 CP: 12, BP: 120/76, MAP: 90.66 ACI: 10 LDH: 58, CK-MB: 10
19 Zhang et al. 52 China Retrospective cohort 19 1.37 HTN: 11, CHD: 3, DM: 4, CPD: 3 NR ACI: 9 Tn: 9
20 Li et al. 53 China Retrospective cohort 54 1.70 HTN: 15, CAD: 7, DM: 7, CPD: 4 NR ACI: 23 Tn: 23
21 Shi et al. 54 China Retrospective cohort 416 0.97 HTN: 127, CHD: 44, CHF: 17, CKD: 14, CLD: 4, DM: 60, CPD: 12 CP: 14 AMI: 82 Tn: 82
22 Aggarwal et al. 55 USA Retrospective cohort 16 3 HTN: 9, CAD: 3, CHF: 4, CKD: 6, DM: 5, CPD: 2 CP: 1, HR: 94, MAP: 94, Hypotension: 5, Tachycardia: 5 AMI: 3, HF: 2, ACS: 4, Arrhythmia: 1 LDH: 13
23 Suleyman et al. 28 USA Retrospective cohort 463 0.78 HTN: 295, CAD: 59, HF: 49, CKD: 208, DM: 178, CPD: 122 HR: 96 NR Tn: 107
24 Yang et al. 56 China Retrospective cohort 114 0.96 CVD: 12, CKD: 1, CPD:1 NR NR Tn: 114, CK-MB: 8
25 Richardson et al. 57 USA Retrospective cohort 5,700 1.51 HTN: 3026, CAD: 595, HF: 371, CKD: 454, CLD: 30, DM: 1,808, CPD: 766 HR: 97, Tachycardia: 2,457 NR Tn: 801
26 Feng et al. 58 China Retrospective cohort 476 1.32 HTN: 113, CVD: 38, CKD: 4, DM: 49, CPD: 22 CP: 21 NR Tn: 86
27 Yang et al. 59 China Retrospective cohort 200 0.96 HTN: 45, HD: 11, CKD: 3, CLD: 2, DM: 21, CPD: 7 NR ACI: 20 LDH: 74, CK-MB: 5
28 Jin et al. 60 China Retrospective cohort 93 0.78 HTN: 16, CVD: 1, DM: 7, CPD: 3 CP: 5 ACI: 9 Tn: 9
29 Wang et al. 27 China Retrospective cohort 77 1.96 HTN: 33, HD: 18, CKD: 7, CLD: 4, DM: 18, CPD: 8 NR AMI: 34 Tn: 34, LDH: 68, CK-MB: 14
30 Liu et al. 61 China Retrospective cohort 1,190 1.14 HTN: 308, CHD: 86, CKD: 30, CLD: 40, DM: 144, CPD: 22 NR ACI: 82 NR
31 Lombardi et al. 62 Italy Cross-sectional 614 2.43 HTN: 350, HF: 87, Arrhythmia:100, CAD: 137, CKD: 110, DM: 148, CPD:58 HR: 86.5, MAP: 92.33 HF: 51, AMI: 17 Tn: 278
32 Li et al. 63 China Retrospective cohort 100 1.27 HTN: 40, CVD: 15, CLD: 3, DM: 21, CPD: 12 CP: 2, HR: 92.5, MAP: 99.3 ACI: 25 Tn: 10
33 Ghio et al. 64 Italy Retrospective cohort 405 2.18 CVD: 268, CKD: 38, DM: 79, CPD: 58 CP: 16, HR: 88, MAP: 98.33 AMI: 74, Arrhythmia: 29 Tn: 74
34 Lazzeri et al. 65 Italy Cross-sectional 28 3.66 HTN: 25, HD: 8, CKD: 1, DM: 11, CPD: 2 NR AMI: 11 Tn: 11
35 Fan et al. 66 China Retrospective cohort 73 2.04 HTN: 24, CVD: 7 NR ACI: 16 Tn: 16
36 Guo et al. 67 China Retrospective cohort 187 0.94 HTN: 61, CHD: 21, CMP: 8, CKD: 6, DM: 28, CPD: 4 NR AMI: 52, Arrhythmia: 11 Tn: 52
37 Ferguson et al. 68 USA Retrospective cohort 72 CVD: 43, HTN: 26, DM: 20, CPD: 10 CP: 8, Bradycardia: 2 CMP: 2, ACI: 2, Arrhythmia: 4 Tn: 2
38 Abrams et al. 69 USA Retrospective cohort 133 1.25 HTN: 110, CHF: 31, CAD: 35, Arrhythmia: 31, CKD: 35, DM: 70, CPD: 28 ACI: 91, Arrhythmia: 17 Tn: 91
39 Chen et al. 70 China Retrospective cohort 21 4.25 HTN: 5, DM: 3 CP: 11, HR: 89 ACI: 2 Tn: 2, LDH: 11
40 Xie et al. 26 China Retrospective cohort 733 1.86 HTN: 308, CHD: 93, CHF: 15, CKD: 13, CLD: 11, DM: 138, CPD: 37 NR ACI: 357 Tn: 357
41 Russo et al. 71 Italy Retrospective cohort 414 1.57 HTN: 263, HF: 46, CAD: 66, Arrhythmia: 72, CKD: 64, DM: 106, CPD: 88 NR Arrhythmia: 50 NR
42 Xiong et al. 72 China Retrospective cohort 116 2.22 HTN: 45, CHD: 17, CVD: 8, CLD: 2, DM: 19, CPD: 1 CP: 50, HR: 86, MAP: 96.7, Palpitation: 13 ACI: 23, HF: 21 Tn: 16, LDH: 69, CK-MB: 19
43 Li et al. 73 China Retrospective cohort 312 1.49 HTN: 178, CVD: 93, CKD: 10, CLD: 11, DM: 121, CPD: 27 NR Shock: 76, ACI: 103 NR
44 Guo et al. 74 China Retrospective cohort 105 0.84 HTN: 46, CD: 17, CKD: 5, CLD: 5, DM: 27, CPD: 9 NR ACI: 5 LDH: 43, CK-MB: 12
45 He et al. 75 China Retrospective cohort 288 0.83 HTN: 84, CVD: 85, CKD: 8, CLD: 10, DM: 24, CPD: 5 NR ACI: 22 Tn: 22
46 Li et al. 76 China Retrospective cohort 204 0.96 HTN: 74, CD: 44, CKD: 5, DM: 39, CPD: 21 CP: 33 ACI: 27 Tn: 60, CK-MB: 15
47 Du et al. 77 China Retrospective cohort 85 2.69 HTN: 32, CHD: 10, CKD: 3, CLD: 5, DM: 19, CPD: 2 CP: 2 AMI: 38, Arrhythmia: 51 LDH: 70, CK-MB: 31
48 Huang et al. 78 China Retrospective cohort 202 1.34 HTN: 29, CVD: 5, CLD: 4, DM: 19, CPD: 7 NR AMI: 2 Tn: 2
49 Li et al. 79 China Retrospective cohort 25 0.66 HTN: 16, HD: 8, CKD: 5, CLD: 1, DM: 10, CPD: 2 NR Tn: 11, LDH: 9
50 Palmieri et al. 80 Italy Retrospective cohort 3,032 HTN: 2,071, IHD: 856, HF: 490, Arrhythmia: 681, CKD: 618, CLD: 120, DM: 914, CPD: 498 NR ACI: 314 NR
51 Mughal et al. 81 USA Retrospective cohort 129 1.68 HTN: 56, CAD: 10, HF: 12, CKD: 10, DM: 25, CPD: 12 MAP: 94 ACI: 9, Arrhythmia: 8 NR
52 Wang et al. 82 China Retrospective cohort 59 1.81 HTN: 31, CAD: 13, CLD: 4, DM: 15, CPD: 8 CP: 31 ACI: 38, Arrhythmia: 16 NR
53 Stefanini et al. 83 Italy Retrospective cohort 397 2.05 HTN: 224, MI: 33, Arrhythmia: 39, CVD: 31, CKD: 85, CLD: 18, DM: 97, CPD: 35 Tachycardia: 72 ACI: 40 Tn: 40
54 Wang et al. 84 China Retrospective cohort 319 0.91 HTN: 139, CVD: 57, DM: 37 Tachycardia: 40, Bradycardia: 19 Arrhythmia: 20 Tn: 74
55 Heberto et al. 85 Mexico Prospective cohort 254 1.91 CHD: 14, HTN: 90, CKD: 2, DM: 80 NR Arrhythmias: 20, AMI: 73 Tn: 73
56 Li et al. 86 China Retrospective cohort 2,068 0.94 HTN: 722, HF: 14, CAD: 182, ARRHY: 24, CKD: 31, DM: 292, CPD: 32 CP: 65, HR: 90, Palpitation: 45 ACI: 181, Arrhythmia: 151 Tn: 181, CK-MB: 40
57 Cao et al. 87 China Retrospective cohort 244 1.19 HTN: 75, DM: 36 CP: 3, HR: 87.26, MAP: 87.26 AMI: 45 Tn: 45, CK-MB: 153
58 Lorente-Ros et al. 88 Spain Retrospective cohort 707 1.68 HTN: 357, HF: 290, IHD: 66, Arrhythmia: 240, CKD: 79, DM: 143, CPD: 172 NR AMI: 148 Tn: 148
59 Yang et al. 89 China Retrospective cohort 203 1.30 HTN: 80, CVD: 9, DM: 29, CPD: 6 NR AMI: 38 NR
60 Qian et al. 90 China Retrospective cohort 77 2.20 HTN: 39, CVD: 18, CAD: 11, HF: 2, CKD: 4, DM: 17, CPD: 3 NR AMI: 41, Arrhythmia: 19 NR
61 Shah et al. 24 USA Retrospective cohort 309 0.74 HTN: 261, HF: 65, CKD: 48, CLD: 5, DM: 143, CPD: 88 NR AMI: 116 Tn: 116
62 Zhao et al. 91 China Retrospective cohort 83 2.32 HTN: 42, CVD: 13, CKD: 4, CLD: 5, DM: 30, CPD: 7 HR: 99, MAP: 93 AMI: 37 Tn: 37
63 Chen et al. 92 China Retrospective cohort 681 1.13 HTN: 293, CAD: 80, CKD: 27, DM: 114, CPD: 15 Palpitation: 17 AMI: 139 Tn: 139
64 Lala et al. 93 USA Retrospective cohort 2,736 1.47 HTN: 1,065, HF: 276, CAD: 453, Arrhythmia: 206, CKD: 273, DM: 719, CPD: 387 Tachycardia: 647, Hypotension: 228 AMI: 985 Tn: 985
65 Deng et al. 23 China Retrospective cohort 264 0.97 HTN: 100, CHD: 32, CKD: 9, CLD: 14, DM: 41, CPD: 8 NR AMI: 45 Tn: 45
66 Karbalai Saleh et al. 94 Iran Prospective cohort 386 1.57 HTN: 142, CVD: 97, CKD: 16, DM: 133, CPD: 27 HR: 87.67 AMI: 115 Tn: 115
67 Xu et al. 95 China Retrospective cohort 53 1.12 HTN: 8, CVD: 6, DM: 8, CPD: 3 Tachycardia: 15, Angina: 8 AMI: 6, Arrhythmia: 4 NR
68 Argenziano et al. 96 USA Retrospective cohort 1,000 1.47 HTN: 601, CAD: 131, HF: 102, CKD: 137, CLD: 34, DM: 372, CPD: 179 NR MI: 8, HF: 24, Arrhythmia: 79 NR
69 Linschoten et al. 97 Multi-country Retrospective cohort 3,011 1.68 HTN: 1,317, CAD: 463, HF: 160, Arrhythmia: 453, CKD: 313, DM: 690, CPD: 373 NR HF: 55, ACS: 15, Myocarditis: 3, Arrhythmia: 378 NR
70 Saleh et al. 98 Germany Prospective cohort 40 1.66 HTN: 19, HD: 10, DM: 11 Chest pain: 11 HF: 5, Arrhythmia: 13 Tn: 25, CK-MB: 17
71 Papageorgiou et al. 99 UK Retrospective Cohort 613 1.50 HTN: 288, HD: 86, DM: 199, CPD: 142 CP: 63 HF: 44, MI: 19, AMI: 287, Arrhythmia: 47
72 Becerra-Muñoz et al. 100 Spain Retrospective Cohort 1,520 1.51 HTN: 1,047, HD: 562, Arrhythmia: 247, CKD: 164, CLD: 61, DM: 377, CPD: 380 NR HF: 143 Tn: 150
73 Yan et al. 101 China Retrospective Cohort 119 0.80 HTN: 60, CHD: 19, CKD: 4, DM: 26, CPD: 2 Chest pain: 9 NR Tn: 27
74 Arcari et al. 102 Italy Retrospective Cohort 111 0.85 HTN: 62, CVD: 35, Arrhythmia: 21, CAD: 12, HF: 8, CKD: 7, DM: 21, CPD: 26 NR NR Tn: 39
No: Number of studies; N: Number of patients; CVD: Cardiovascular diseases; IHD: Ischemic heart diseases; HTN: Hypertension; CHD: Chronic heart disease; HF: Heart failure; CAD: Coronary artery disease; CKD: Chronic kidney disease; CLD: Chronic liver disease; DM: Diabetes mellitus; CPD: Chronic pulmonary disease; HR: Heart rate; SBP: Systolic blood pressure; MAP: Mean arterial pressure; CP: Chest pain; AC(M)I: Acute cardiac (myocardial) injury; CMP: Cardiomyopathy; MI: Myocardial infarction; ACS: Acute coronary syndrome; cTn: Cardiac troponin; LDH: Lactate dehydrogenase; CK-MB: Creatine kinase–myocardial band; CK: Creatine kinase; NR: Not reported, not reported by number, or incomplete
Table 1.Summary of studies included in the review. All studies were published in the year 2020

Prevalence of Comorbidities

Meta-analysis of the included studies showed that the most prevalent comorbidities in COVID-19 patients were HTN (39.50%), DM (19.67%), CVD (15.07%), coronary artery disease (CAD) (12.98%), cardiac dysrhythmia (7.84%), HF (7.11%), CPD (6.88%), chronic kidney diseases (CKD) (5.62%), CMP (4.85%), and chronic liver diseases (CLD) (3.09%).

The highest and lowest rates of HTN among patients with COVID-19 were in Italy (89.29%, 95% CI=71.77-97.73) 65 and China (9.49%, 95% CI=5.15-15.68), 19 respectively. Based on the results of a random effect model, the pooled prevalence of HTN was 39.85% (95% CI=34.17-45.83). The Chi square test result for heterogeneity was significant for the reported prevalence of HTN (I2=97.4%, P<0.001). The highest and lowest rates of DM among patients with COVID-19 were in the USA (52.63%, 95% CI=43.79-61.35) 69 and China (4.88%, 95% CI=0.60-16.53), 46 respectively. Based on the results of a random effect model, the pooled prevalence of DM was 19.88% (95% CI=17-23.11). The Chi square test result for heterogeneity was significant for the reported prevalence of DM (I2=94.3%, P<0.001).

The highest and lowest rates of CVD among patients with COVID-19 were in Italy (66.17%, 95% CI=61.34-70.77) 64 and China (1.08%, 95% CI=0.03-5.85), 60 respectively. The results of a random effect model showed that the pooled prevalence of CVD was 15.07% (95% CI=12.05-18.68). The Chi square test result for heterogeneity was significant for the reported prevalence of CVD (I2=96.3%, P<0.001).

The highest and lowest rates of CAD among patients with COVID-19 were in the USA (26.32%, 95% CI=19.06-34.65) 69 and China (4.43%, 95% CI=2.05-8.25), 89 respectively. Based on the results of a random effect model, the pooled prevalence of CAD was 12.98% (95% CI=10.74-15.61). The Chi square test result for heterogeneity was significant for the reported prevalence of CAD (I2=91.2%, P<0.001).

The highest and lowest rates of cardiac arrhythmia among patients with COVID-19 were in Spain (33.95%, 95% CI=30.46-37.57) 88 and China (0.69%, 95% CI=0.08-2.46), 45 respectively. Based on the results of a random effect model, the pooled prevalence of cardiac arrhythmia was 7.84% (95% CI=3.79-15.50). The Chi square test result for heterogeneity was significant for the reported prevalence of cardiac arrhythmia (I2=98.3%, P<0.001).

The highest and lowest rates of HF among patients with COVID-19 were in Spain (41.02%, 95% CI=37.37-44.75), 88 and China (0.34%, 95% CI=0.01-1.90), 45 respectively. Based on the results of a random effect model, the pooled prevalence of HF was 7.11% (95% CI=4.34-11.45). The Chi square test result for heterogeneity was significant for the reported prevalence of HF (I2=98.2%, P<0.001).

The highest and lowest rates of CPD among patients with COVID-19 were in the USA (28.48%, 95% CI=23.51-33.86) 24 and China (0.74%, 95% CI=0.02-4.06), 51 respectively. Based on the results of a random effect model, the pooled prevalence of CPD was 6.88% (95% CI=5.23-8.99). The Chi square test result for heterogeneity was significant for the reported prevalence of CPD (I2=94.8%, P<0.001).

The highest and lowest rates of CKD among patients with COVID-19 were in the USA (44.92%, 95% CI=40.33-49.58) 28 and Mexico (0.79%, 95% CI=0.10-2.82), 85 respectively. Based on the results of a random effect model, the pooled prevalence of CKD was 5.62% (95% CI=4.79-6.59). The Chi square test result for heterogeneity was significant for the reported prevalence of CKD (I2=96.6%, P<0.001).

Both the highest and lowest rates of CMP (as an underlying medical condition) among patients with COVID-19 were in China (5.95%, 95%CI=1.96-13.35 32 and 4.28%, 95% CI=1.86-8.26, 67 respectively). Based on the results of a random effect model, the pooled prevalence of CMP was 4.85% (95% CI=2.84-8.18). The Chi square test result for heterogeneity was not significant for the reported prevalence of CMP (I2=0.0%, P=0.558%).

The highest and lowest rates of CLD among patients with COVID-19 were in China (13.10%, 95% CI=6.72-22.22) 32 and the USA (0.53%, 95% CI=0.36-0.75), 57 respectively. Based on the results of a random effect model, the pooled prevalence of CLD was 3.09% (95% CI=2.37-4.02). The Chi square test result for heterogeneity was significant for the reported prevalence of CLD (I2=82.9%, P<0.001).

Prevalence of Cardiovascular Signs and Symptoms

Meta-analysis of the included studies indicated that the most prevalent signs and symptoms in COVID-19 patients were hypotension (14.42%), tachycardia (9.98%), chest pain (8.80%), and bradycardia (5.24%). The highest and lowest rates of hypotension among patients with COVID-19 were 31.25% (95% CI=11.02-58.66) 55 and 8.33% (95% CI=7.32-9.43), 93 respectively. Based on the results of a random effect model, the pooled prevalence of hypotension was 14.42% (95% CI=5.54-32.59). The Chi square test result for heterogeneity was significant for the reported prevalence of hypotension (I2=88.6%, P=0.009). The highest and lowest rates of tachycardia among patients with COVID-19 were 43.11% (95% CI=41.81-44.40) 57 and 1.03% (95% CI=0.21-2.98), 45 respectively. Based on the results of a random effect model, the pooled prevalence of tachycardia was 9.98% (95% CI=5.32-17.93). The Chi square test result for heterogeneity was significant for the reported prevalence of tachycardia (I2=99%, P<0.001).

The highest and lowest rates of chest pain among patients with COVID-19 were 52.54% (95% CI=39.12-65.70) 82 and 0.34% (95% CI=0.01-1.90), 45 respectively. Based on the results of a random effect model, the pooled prevalence of chest pain was 8.80% (95% CI=5.19-14.51). The Chi square test result for heterogeneity was significant for the reported prevalence of chest pain (I2=96.4%, P<0.001). The highest and lowest rates of bradycardia among patients with COVID-19 were 5.96% (95% CI=3.62-9.15) 84 and 2.78% (95% CI=0.34-9.68), 68 respectively. Based on the results of a random effect model, the pooled prevalence of bradycardia was 5.24% (95% CI=3.53-7.69). The Chi square test result for heterogeneity was not significant for the reported prevalence of bradycardia (I2=0.0%, P=0.394).

Prevalence of Cardiovascular Complications

The results of the present meta-analysis showed that the overall pooled prevalence of cardiovascular complications was 23.45% (95% CI=16.24-32.61). The Chi square test result for heterogeneity was significant for the reported prevalence of cardiovascular complications (I2=97.8%, P<0.001) (figure 2). Since there were several articles on this type of complication, the available articles were divided into three groups according to sample size and subsequently presented in separate forest plots. The overall pooled prevalence of cardiovascular complications, based on analysis of the results of the studies, is presented in forest plots a, b, and c. The most prevalent cardiovascular complications in COVID-19 patients were, in descending order, acute cardiac (myocardial) injury (19.38%), cardiac arrhythmias (11.16%), HF (7.56%), CMP (2.78%), myocardial infarction (1.66%), and myocarditis (0.71%).

Figure 2. Forest plots show the overall prevalence of cardiovascular complications in patients with COVID-19 (pooled prevalence, as well as a, b, and c groups, are sorted by the sample size of the studies).

Both the highest and lowest rates of acute cardiac (myocardial) injury among patients with COVID-19 were in China (89.02%, 95% CI=80.18-94.86 44 and 0.99%, 95% CI=0.12-3.53, 78 respectively). Based on the results of a random effect model, the pooled prevalence of acute cardiac (myocardial) injury was 19.38% (95% CI=13.62-26.81). The Chi square test result for heterogeneity was significant for the reported prevalence of acute cardiac (myocardial) injury (I2=97.5%, P<0.001) (figure 3). Since there were several articles on this type of complication, the available articles were divided into three groups according to sample size and subsequently presented in separate forest plots. The total pooled prevalence of acute cardiac (myocardial) injury, based on analysis of the results of the included studies, is presented in forest plots a, b, and c.

Figure 3. Forest plots show the prevalence of acute cardiac (myocardial) injury (ACI/AMI) in patients with COVID-19 (pooled prevalence, as well as a, b, and c groups, are sorted by the sample size of the studies).

The highest and lowest rates of cardiac arrhythmia among patients with COVID-19 were both in China (60%, 95% CI=48.80-70.48 77 and 4.76%, 95% CI=1.31-11.75, 32 respectively). Based on the results of a random effect model, the pooled prevalence of arrhythmia was 11.16% (95% CI=8.23-14.96). The Chi square test result for heterogeneity was significant for the reported prevalence of arrhythmia (I2=91.5%, P<0.001) (figure 4).

Figure 4. The forest plot shows the prevalence of cardiac arrhythmia in patients with COVID-19.

Both the highest and lowest rates of HF among patients with COVID-19 were in China (23.04%, 95% CI=17.27-29.66 41 and 1.01%, 95% CI=0.03-5.50, 43 respectively). Based on the results of a random effect model, the pooled prevalence of HF was 7.56% (95% CI=4.50-12.45). The Chi square test result for heterogeneity was significant for the reported prevalence of HF (I2=96.3%, P<0.001) (figure 5). The prevalence of CMP among patients with COVID-19 in one study that met the inclusion criteria was 2.78% (95% CI=0.34-9.68). 68

Figure 5. The forest plot shows the prevalence of heart failure in patients with COVID-19.

The highest and lowest rates of myocardial infarction among patients with COVID-19 were in the UK (3.10%, 95% CI=1.88-4.80) 99 and the USA (0.80%, 95% CI=0.35-1.57), 96 respectively. Based on the results of a random effect model, the pooled prevalence of myocardial infarction was 1.66% (95% CI=0.65-4.19). The Chi square test result for heterogeneity was significant for the reported prevalence of myocardial infarction (I2=90.5%, P<0.001) (figure 6).

Figure 6. The forest plot shows the prevalence of myocardial infarction (M.Inf.) in patients with COVID-19.

The highest and lowest rates of myocarditis among patients with COVID-19 were in China (4.76%, 95% CI=1.31-11.75) 32 and a multi-country study (0.10%, 95% CI=0.02-0.29), 97 respectively. Based on the results of a random effect model, the pooled prevalence of myocarditis was 0.71% (95% CI=0.05-9.78). The Chi square test result for heterogeneity was significant for the reported prevalence of myocarditis (I2=96.1%, P<0.001) (figure 7).

Figure 7. The forest plot shows the prevalence of myocarditis in patients with COVID-19.

The meta-analysis of the included studies showed that the most prevalent elevated cardiac markers in COVID-19 patients were, in order of frequency, LDH (61.45%), cTnI(T) (23.10%), and CK or CK-MB (14.52%). Both the highest and lowest rates of increased LDH among patients with COVID-19 were in China (88.31%, 95% CI=78.97-94.51 27 and 36%, 95% CI=17.97-57.48, 79 respectively). Based on the results of a random effect model, the pooled prevalence of increased LDH was 61.45% (95% CI=51.11-70.85). The Chi square test result for heterogeneity was significant for the reported prevalence of increased LDH (I2=91.5%, P<0.001) (figure 8).

Figure 8. The forest plot shows the prevalence of increased lactate dehydrogenase levels in patients with COVID-19.

The highest and lowest rates of increased cTnI(T) among patients with COVID-19 were both in China (100%, 95% CI=96.82-100.00 56 and 0.99%, 95% CI=0.12-3.53, 78 respectively). Based on the results of a random effect model, the pooled prevalence of increased TnI(T) was 23.10% (95% CI; 20.78-25.60). Chi square test result for heterogeneity was significant for the reported prevalence of increased cTnI(T) (I2=97.4%, P<0.001) (figure 9). Since there were several articles for this variable, the available articles were divided into three groups according to sample size and subsequently presented in separate forest plots. The total pooled prevalence of cTnI(T), based on analysis of the results of the studies, is presented in forest plots a, b, and c.

Figure 9. Forest plots show the prevalence of increased cTnI(T) level in patients with COVID-19 (pooled prevalence, as well as a, b, and c groups, were sorted by the sample size of the studies).

Both the highest and lowest rates of increased CK and/or CK-MB among patients with COVID-19 were in China (62.70%, 95% CI=56.31-68.79 87 and 1.93%, 95% CI=1.39-2.62, 86 respectively). Based on the results of a random effect model, the pooled prevalence of increased CK or CK-MB was 14.52% (95% CI=8.82-22.98). The Chi square test result for heterogeneity was significant for the reported prevalence of increased CK and/or CK-MB (I2=97.4%, P<0.001) (figure 10).

Figure 10. The forest plot shows the prevalence of increased creatine kinase or creatine kinase-myocardial band level in patients with COVID-19.

Publication Bias and Heterogeneity of the Study Results

Linear regression test of funnel plot asymmetry suggested no statistically significant publication bias for HR (t=-1.93, P=0.075). However, the heterogeneity of the results of the included studies was highly significant (I2=98%, P<0.001). Regarding the MAP level in the participants, the test of funnel plot asymmetry suggested no statistically significant publication bias (t=-0.55, P=0.594). Again, the heterogeneity of the results of the included studies was highly significant (I2=99%, P<0.001). Evaluation of the effect of country, sex, and age of the participants on the results of the included studies, using meta-regression, revealed no significant contribution of these variables on the prevalence of cardiovascular comorbidities and the observed heterogeneity (P>0.05 for all) (tables 2 and 3).

Estimate B SE Z-value 95% CI P value
Intercept -5.44 0.74 -7.2893 -6.91 to -3.98 <0.001
Country Korea 0.24 0.66 0.3610 -1.07 to 1.55 0.718
Italy 0.76 0.35 2.1976 0.08 to 1.45 0.028
Germany 0.39 0.69 0.5757 -0.95 to 1.74 0.564
Others -0.07 0.28 -0.2687 -0.64 to 0.48 0.788
Mean age (years) 0.05 0.01 4.5849 0.03 to 0.08 <0.001
Sex ratio 0.19 0.16 1.2138 -0.11 to 0.49 0.224
B: Regression coefficient; SE: Standard error; CI: Confidence interval; Amount of heterogeneity accounted for (R2=15.63%); Estimated amount of residual heterogeneity (tau^2=23.37); Test for residual heterogeneity (QE=220.55, P<0.001); Test of moderators (QM=8.49, P=0.20)
Table 2.Results of meta-regression for cardiovascular diseases
Estimate B SE Z-value 95% CI P value
Intercept -5.43 0.98 -5.5307 -7.35 to -3.50 <0.001
Country USA -0.94 0.28 -3.3093 -1.50 to -0.39 0.0009
Italy -1.14 0.33 -3.4644 -1.79 to -0.50 0.0005
Germany 0.63 0.51 1.2208 -0.38 to 1.63 0.222
Others -0.99 0.31 -3.1178 -1.61 to -0.37 0.001
Multicenter -0.57 0.38 -1.4800 -1.33 to 0.18 0.138
Mean age (years) 0.03 0.01 2.2105 0.00 to 0.06 0.027
Sex ratio 1.04 0.19 5.3994 0.66 to 1.41 <0.001
B: Regression coefficient; SE: Standard error; CI: Confidence interval; Amount of heterogeneity accounted for (R2=15.63%); Estimated amount of residual heterogeneity (tau^2=23.37); Test for residual heterogeneity based on Likelihood-ratio test (I2=89.219, P<0.001); Test of moderators based on Chi square test (QM=40.59, P=0.20)
Table 3.Results of meta-regression for cardiac arrhythmia

Discussion

In this meta-analysis, 74 studies involving 34,379 COVID-19 patients were analyzed. Meta-analysis of the included studies showed that the most prevalent comorbidities in COVID-19 patients were HTN, DM, CVD, CAD, cardiac dysrhythmia, HF, CPD, CKD, CMP, and CLD. The most prevalent signs and symptoms in COVID-19 patients were hypotension, tachycardia, chest pain, and bradycardia. The results showed that the overall pooled prevalence of cardiovascular complications was 23.45%. The most prevalent cardiovascular complications in COVID-19 patients were, in descending order, acute cardiac (myocardial) injury, cardiac arrhythmias, HF, CMP, myocardial infarction, and myocarditis. In addition, the most prevalent underlying medical condition in COVID-19 patients was HTN. According to previous studies on SARS-CoV-2, the presence of comorbidities increases the risk of mortality, with cardiac diseases and DM being the most important predictors of adverse outcomes. 103 A large-scale study of 44,672 patients reported that CVD was a major risk factor for mortality in COVID-19 patients. 104

According to previous systematic reviews and meta-analyses, HTN was the most prevalent underlying disease in hospitalized COVID-19 patients. 105 - 107 Moreover, the severity and mortality of COVID-19 were found to be higher in patients with HTN. HTN was even reported to increase the mortality rate associated with COVID-19 by a factor of 2.5. 105 Research findings also show that, in addition to HTN, CVD is among the prevalent underlying medical conditions in COVID-19 patients. Several studies reported a correlation between the severity/mortality of the infection and the above-mentioned underlying diseases. 47 , 67 , 106 - 112

DM was found to be the second most prevalent underlying medical condition in COVID-19 patients. In the present meta-analysis, the third and fourth most prevalent underlying conditions were CVD and CAD, respectively. CVD and HTN in COVID-19 patients were associated with ACE2 receptors. 113 The entry of the new coronavirus into cells through membrane fusion results in a significant decrease in the efficacy of ACE2 receptors and loss of their catalytic function on the outer membrane. Elevated pulmonary inflammation and vasoconstriction were reported as undesirable consequences of an increase and lack of response to angiotensin II in COVID-19. Clinical reports of COVID-19 patients showed that several factors associated with infection severity (old age, HTN, DM, and cardiac disease) correlated with some degree of ACE2 deficiency. 114

A meta-analysis of 1,527 patients with COVID-19, conducted to determine the prevalence and impact of cardiovascular metabolic diseases on COVID-19 patients in China, showed that the frequency of HTN and cardiac disease was 17.1% and 16.4%, respectively, and also patients with these conditions were more likely to require critical care. 115 HTN, DM, and ischemic heart disease are prevalent in people hospitalized for infection with the new coronavirus and correlate with an increased risk of disease progression and death. 116

The fifth most prevalent underlying condition was cardiac dysrhythmias. In a study of 700 patients with COVID-19, Bhatla and colleagues reported that 6% of the infected patients had a history of atrial fibrillation. 117 In the present review, the sixth most prevalent underlying disease was HF, which is in line with other studies that refer to HF as a major underlying condition and risk factor in COVID-19 patients. 21 , 39 , 54 , 117 , 118 Other underlying conditions identified in the present study were, in descending order, a positive history of CPD, CKD, CMP, and CLD. Edler and colleagues reported that 5% of their patients with COVID-19 had CMP. 36

In the present meta-analysis, we also included the reported cardiac signs and symptoms. The most prevalent symptom in the infected patients was hypotension followed by tachycardia, chest pain, and bradycardia. Liu and colleagues studied 133 patients with COVID-19 and reported that 7.3% of the patients complained of tachycardia at the time of admission. 19 The results of the present review study showed that the most prevalent complication in COVID-19 patients was cardiac injury. Based on our review, 19.38% of COVID-19 patients suffered from an acute cardiac (myocardial) injury as a result of the infection. Some studies showed that SARS-CoV-2 can both directly and indirectly lead to cardiovascular sequelae, including myocardial injury, acute coronary syndromes (ACS), CMP, acute cor pulmonale, arrhythmias, and cardiogenic shock, as well as thrombotic complications. 2 , 119 ACE2 is regarded as one of the primary receptors leading to cardiac injury. 115 , 120 Being tissue-specific, ACE2 is found on the pulmonary, cardiovascular, gastrointestinal, and renal cells. This phenomenon results in intracellular acidosis and the production of oxygen-free radicals, in addition to the influx of calcium, which eventually leads to myocyte injury and death. 115 Thus, the close resemblance of SARS to the COVID-19 genome, alongside similarities between their receptor binding areas, can lead to myocardial damage. Another possible mechanism may be associated with the cytokine storm. Lack of balance between T-helper (Th) 1 and Th2 cells causes the overproduction of inflammatory cytokines, which may be one of the contributory factors in the pathogenesis of cardiac injury. 12 Myocardial injury, with elevated cardiac biomarkers above the 99th percentile of the upper reference limit, was reported in 20%-30% of hospitalized COVID-19 patients; those with pre-existing CVD were more prone to the injury (55%). 54 , 67 A systematic review of 22 articles showed the pooled incidence of myocardial injury to be 17.85%, 29 and that of cardiac arrhythmia was 11.16% (the second most prevalent complication). In a study by Zhang and others, 24 of the 221 observed patients had experienced cardiac arrhythmia. 50 It was reported that about 16% of patients with MERS experienced cardiac arrhythmia. 9 The results of a study by Li and colleagues showed that patients with emerging arrhythmia were at higher risk of contracting severe diseases and requiring intensive care. 121 In another review, the pooled incidence of cardiac arrhythmia was reported to be 10.14%. 29 In a study by Chen and colleagues, 1.3% of the patients had cardiac arrhythmia at the time of admission; yet, 44% indicated signs of atrial fibrillation during hospitalization. 122

In the present review, the third most prevalent complication in COVID-19 patients was HF. In a study by Zhou and colleagues, 23% of the patients experienced HF following infection with the new coronavirus. 41 In a previous systematic review of 22 articles, HF was the most prevalent complication among COVID-19 patients with an incidence rate of 22%. 29

Our findings showed that other prevalent cardiovascular complications associated with COVID-19 are, in descending order, CMP, myocardial infarction, and myocarditis. A previous study reported that five out of 76 patients with SARS had cardiac arrhythmia and CMP. 123 Because of extensive inflammation and hypercoagulability, patients with COVID-19 are at risk of acute myocardial infarction. 119 , 124 In a study of 75 inpatients with SARS, acute myocardial infarction was found to account for two out of five deaths. 125 Viral myocarditis can cause various cardiac complications, from subclinical myocarditis, with only enzyme elevation due to local myocyte necrosis, to sudden cardiac death due to arrhythmia. 126 , 127 Among ten professional athletes with SARS-CoV-2 infection, 2.3% had signs of clinical or subclinical myocarditis. 128

In the present meta-analysis, the most prevalent elevated cardiac markers in COVID-19 patients were LDH (61.45%), cTnI(T) (23.10%), and CK or CK-MB (14.52%). CK, CK-MB, and LDH were indicators associated with cardiac injury. 129 , 130 Elevated TnI and CK-MB levels showed cardiac injuries, such as viral myocarditis or myocardial infarction, as well as multiple organ injuries. 131 High-sensitivity cTnI and cTnT are the gold standard biomarkers for the diagnosis of acute myocardial infarction. 132 TnI has a very good prognostic value not only for patients with COVID-19 but also for patients with other types of influenza virus infection. 125 LDH, on the other hand, is not highly specific to the heart. 133 The results of a study of 76 patients with SARS showed that 73 and 34 patients had elevated levels of serum LDH and CK, respectively. 123 According to a systematic review and meta-analysis, patients with elevated cTnI(T), CK, CK-MB, and LDH levels were at higher risk of developing a serious illness requiring intensive care. However, LDH levels have predictive value for mortality. 121 An increase in the frequency and extent of troponin elevations in hospitalized patients was associated with greater disease severity and more serious consequences. 54 , 67

Our meta-analysis revealed significant heterogeneities in the results of the included studies regarding CVD and cardiac arrhythmia. We attempted to clarify the effect of the patients’ country, age, and sex to the heterogeneity of the results by conducting a meta-regression analysis. However, the residual heterogeneity remained significant even after the above factors were included in the meta-regression. This may suggest the impact of hidden factors (e.g., differences between studies in diagnosis, reporting, and hospital admission strategies). No publication bias was detected in the present study.

As the main limitation of the present study, we only included observational studies on adult patients. Furthermore, vascular complications (e.g., venous thrombosis) were not addressed. Therefore, it is recommended to include a review of clinical trials and thrombotic disorders for a better understanding of the cardiovascular complications caused by COVID-19.

Conclusion

The most prevalent cardiovascular complications in patients with COVID-19 were, in descending order, acute cardiac (myocardial) injury, cardiac arrhythmias, HF, and CMP. Healthcare administrators should pay closer attention to viral infection-related cardiovascular complications when treating those infected. Since the occurrence of cardiovascular complications has a negative impact on the mortality rate in patients with COVID-19, clinicians and nurses should be aware of the various types of cardiovascular complications associated with COVID-19 and include them in their patient care and treatment plan.

Acknowledgment

The study was extracted from a research project financially supported by the Vice-Chancellor for Research Affairs of Shiraz University of Medical Sciences, Shiraz, Iran (grant number: 20933).

Authors’ Contribution

CT, HH, and RI were responsible for the study conception and performed data collection; MF, HH, and RI performed the data analysis; HH and RI led the writing of the manuscript. CT, MF, and HH made critical revisions to the paper. CT and HH supervised the study. All the authors helped to conceptualize ideas, interpret findings, and review drafts of the manuscript. All authors read and approved the final manuscript and responsible for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Conflict of Interest:

None declared.

References

  1. Velavan TP, Meyer CG. The COVID-19 epidemic. Trop Med Int Health. 2020; 25:278-80. Publisher Full Text | DOI | PubMed
  2. Clerkin KJ, Fried JA, Raikhelkar J, Sayer G, Griffin JM, Masoumi A, et al. COVID-19 and Cardiovascular Disease. Circulation. 2020; 141:1648-55. DOI | PubMed
  3. Patel AB, Verma A. COVID-19 and Angiotensin-Converting Enzyme Inhibitors and Angiotensin Receptor Blockers: What Is the Evidence?. JAMA. 2020; 323:1769-70. DOI | PubMed
  4. Inciardi RM, Lupi L, Zaccone G, Italia L, Raffo M, Tomasoni D, et al. Cardiac Involvement in a Patient With Coronavirus Disease 2019 (COVID-19). JAMA Cardiol. 2020; 5:819-24. Publisher Full Text | DOI | PubMed
  5. Eisenhut M. Extrapulmonary manifestations of severe respiratory syncytial virus infection--a systematic review. Crit Care. 2006; 10:R107. Publisher Full Text | DOI | PubMed
  6. Yu CM, Wong RS, Wu EB, Kong SL, Wong J, Yip GW, et al. Cardiovascular complications of severe acute respiratory syndrome. Postgrad Med J. 2006; 82:140-4. Publisher Full Text | DOI | PubMed
  7. Assiri A, Al-Tawfiq JA, Al-Rabeeah AA, Al-Rabiah FA, Al-Hajjar S, Al-Barrak A, et al. Epidemiological, demographic, and clinical characteristics of 47 cases of Middle East respiratory syndrome coronavirus disease from Saudi Arabia: a descriptive study. Lancet Infect Dis. 2013; 13:752-61. Publisher Full Text | DOI | PubMed
  8. Alhogbani T. Acute myocarditis associated with novel Middle east respiratory syndrome coronavirus. Ann Saudi Med. 2016; 36:78-80. Publisher Full Text | DOI | PubMed
  9. Saad M, Omrani AS, Baig K, Bahloul A, Elzein F, Matin MA, et al. Clinical aspects and outcomes of 70 patients with Middle East respiratory syndrome coronavirus infection: a single-center experience in Saudi Arabia. Int J Infect Dis. 2014; 29:301-6. Publisher Full Text | DOI | PubMed
  10. Petrosillo N, Viceconte G, Ergonul O, Ippolito G, Petersen E. COVID-19, SARS and MERS: are they closely related?. Clin Microbiol Infect. 2020; 26:729-34. Publisher Full Text | DOI | PubMed
  11. Peeri NC, Shrestha N, Rahman MS, Zaki R, Tan Z, Bibi S, et al. The SARS, MERS and novel coronavirus (COVID-19) epidemics, the newest and biggest global health threats: what lessons have we learned?. Int J Epidemiol. 2020; 49:717-26. Publisher Full Text | DOI | PubMed
  12. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020; 395:497-506. Publisher Full Text | DOI | PubMed
  13. Lazzerini PE, Boutjdir M, Capecchi PL. COVID-19, Arrhythmic Risk, and Inflammation: Mind the Gap!. Circulation. 2020; 142:7-9. DOI | PubMed
  14. Zheng YY, Ma YT, Zhang JY, Xie X. COVID-19 and the cardiovascular system. Nat Rev Cardiol. 2020; 17:259-60. Publisher Full Text | DOI | PubMed
  15. Aghagoli G, Gallo Marin B, Soliman LB, Sellke FW. Cardiac involvement in COVID-19 patients: Risk factors, predictors, and complications: A review. J Card Surg. 2020; 35:1302-5. Publisher Full Text | DOI | PubMed
  16. Mishra AK, Sahu KK, Lal A, Sargent J. Patterns of heart injury in COVID-19 and relation to outcome. J Med Virol. 2020; 92:1747. Publisher Full Text | DOI | PubMed
  17. Lange SJ, Ritchey MD, Goodman AB, Dias T, Twentyman E, Fuld J, et al. Potential Indirect Effects of the COVID-19 Pandemic on Use of Emergency Departments for Acute Life-Threatening Conditions - United States, January-May 2020. MMWR Morb Mortal Wkly Rep. 2020; 69:795-800. Publisher Full Text | DOI | PubMed
  18. Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA. 2020; 323:1061-9. Publisher Full Text | DOI | PubMed
  19. Liu K, Fang YY, Deng Y, Liu W, Wang MF, Ma JP, et al. Clinical characteristics of novel coronavirus cases in tertiary hospitals in Hubei Province. Chin Med J (Engl). 2020; 133:1025-31. Publisher Full Text | DOI | PubMed
  20. Bai Y, Yao L, Wei T, Tian F, Jin DY, Chen L, et al. Presumed Asymptomatic Carrier Transmission of COVID-19. JAMA. 2020; 323:1406-7. Publisher Full Text | DOI | PubMed
  21. Chen T, Wu D, Chen H, Yan W, Yang D, Chen G, et al. Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study. BMJ. 2020; 368:m1091. Publisher Full Text | DOI | PubMed
  22. Strabelli TMV, Uip DE. COVID-19 and the Heart. Arq Bras Cardiol. 2020; 114:598-600. DOI | PubMed
  23. Deng P, Ke Z, Ying B, Qiao B, Yuan L. The diagnostic and prognostic role of myocardial injury biomarkers in hospitalized patients with COVID-19. Clin Chim Acta. 2020; 510:186-90. Publisher Full Text | DOI | PubMed
  24. Shah P, Doshi R, Chenna A, Owens R, Cobb A, Ivey H, et al. Prognostic Value of Elevated Cardiac Troponin I in Hospitalized Covid-19 Patients. Am J Cardiol. 2020; 135:150-3. Publisher Full Text | DOI | PubMed
  25. Parohan M, Yaghoubi S, Seraji A. Cardiac injury is associated with severe outcome and death in patients with Coronavirus disease 2019 (COVID-19) infection: A systematic review and meta-analysis of observational studies. Eur Heart J Acute Cardiovasc Care. 2020; 9:665-77. Publisher Full Text | DOI | PubMed
  26. Xie J, Wu W, Li S, Hu Y, Hu M, Li J, et al. Clinical characteristics and outcomes of critically ill patients with novel coronavirus infectious disease (COVID-19) in China: a retrospective multicenter study. Intensive Care Med. 2020; 46:1863-72. Publisher Full Text | DOI | PubMed
  27. Wang K, Qiu Z, Liu J, Fan T, Liu C, Tian P, et al. Analysis of the clinical characteristics of 77 COVID-19 deaths. Sci Rep. 2020; 10:16384. Publisher Full Text | DOI | PubMed
  28. Suleyman G, Fadel RA, Malette KM, Hammond C, Abdulla H, Entz A, et al. Clinical Characteristics and Morbidity Associated With Coronavirus Disease 2019 in a Series of Patients in Metropolitan Detroit. JAMA Netw Open. 2020; 3:e2012270. Publisher Full Text | DOI | PubMed
  29. Sahranavard M, Akhavan Rezayat A, Zamiri Bidary M, Omranzadeh A, Rohani F, Hamidi Farahani R, et al. Cardiac Complications in COVID-19: A Systematic Review and Meta-analysis. Arch Iran Med. 2021; 24:152-63. DOI | PubMed
  30. Wang L, He W, Yu X, Hu D, Bao M, Liu H, et al. Coronavirus disease 2019 in elderly patients: Characteristics and prognostic factors based on 4-week follow-up. J Infect. 2020; 80:639-45. Publisher Full Text | DOI | PubMed
  31. Kim IC, Kim JY, Kim HA, Han S. COVID-19-related myocarditis in a 21-year-old female patient. Eur Heart J. 2020; 41:1859. Publisher Full Text | DOI | PubMed
  32. Ma K-L, Liu Z-H, Cao C-f, Liu M-K, Liao J, Zou J-B, et al. COVID-19 myocarditis and severity factors: an adult cohort study. MedRxiv. 2020; 48:773-7. DOI
  33. Zeng JH, Liu YX, Yuan J, Wang FX, Wu WB, Li JX, et al. First case of COVID-19 complicated with fulminant myocarditis: a case report and insights. Infection. 2020; 48:773-7. Publisher Full Text | DOI | PubMed
  34. Sala S, Peretto G, Gramegna M, Palmisano A, Villatore A, Vignale D, et al. Acute myocarditis presenting as a reverse Tako-Tsubo syndrome in a patient with SARS-CoV-2 respiratory infection. Eur Heart J. 2020; 41:1861-2. Publisher Full Text | DOI | PubMed
  35. Hu H, Ma F, Wei X, Fang Y. Coronavirus fulminant myocarditis treated with glucocorticoid and human immunoglobulin. Eur Heart J. 2021; 42:206. Publisher Full Text | DOI | PubMed
  36. Edler C, Schroder AS, Aepfelbacher M, Fitzek A, Heinemann A, Heinrich F, et al. Dying with SARS-CoV-2 infection-an autopsy study of the first consecutive 80 cases in Hamburg, Germany. Int J Legal Med. 2020; 134:1275-84. Publisher Full Text | DOI | PubMed
  37. Hua A, O’Gallagher K, Sado D, Byrne J. Life-threatening cardiac tamponade complicating myo-pericarditis in COVID-19. Eur Heart J. 2020; 41:2130. Publisher Full Text | DOI | PubMed
  38. Hong KS, Lee KH, Chung JH, Shin KC, Choi EY, Jin HJ, et al. Clinical Features and Outcomes of 98 Patients Hospitalized with SARS-CoV-2 Infection in Daegu, South Korea: A Brief Descriptive Study. Yonsei Med J. 2020; 61:431-7. Publisher Full Text | DOI | PubMed
  39. Arentz M, Yim E, Klaff L, Lokhandwala S, Riedo FX, Chong M, et al. Characteristics and Outcomes of 21 Critically Ill Patients With COVID-19 in Washington State. JAMA. 2020; 323:1612-4. Publisher Full Text | DOI | PubMed
  40. Zheng Y, Sun LJ, Xu M, Pan J, Zhang YT, Fang XL, et al. Clinical characteristics of 34 COVID-19 patients admitted to intensive care unit in Hangzhou, China. J Zhejiang Univ Sci B. 2020; 21:378-87. Publisher Full Text | DOI | PubMed
  41. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020; 395:1054-62. Publisher Full Text | DOI | PubMed
  42. Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev. 2015; 4:1. Publisher Full Text | DOI | PubMed
  43. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020; 395:507-13. Publisher Full Text | DOI | PubMed
  44. Zhang B, Zhou X, Qiu Y, Song Y, Feng F, Feng J, et al. Clinical characteristics of 82 cases of death from COVID-19. PLoS One. 2020; 15:e0235458. Publisher Full Text | DOI | PubMed
  45. Liu Y, Li J, Liu D, Song H, Chen C, Lv M, et al. Clinical features and outcomes of 2019 novel coronavirus–infected patients with cardiac injury. MedRxiv. 2020. DOI
  46. Hui H, Zhang Y, Yang X, Wang X, He B, Li L, et al. Clinical and radiographic features of cardiac injury in patients with 2019 novel coronavirus pneumonia. MedRxiv. 2020. DOI
  47. Yang X, Yu Y, Xu J, Shu H, Xia J, Liu H, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med. 2020; 8:475-81. Publisher Full Text | DOI | PubMed
  48. Wei JF, Huang FY, Xiong TY, Liu Q, Chen H, Wang H, et al. Acute myocardial injury is common in patients with COVID-19 and impairs their prognosis. Heart. 2020; 106:1154-9. Publisher Full Text | DOI | PubMed
  49. Shi S, Qin M, Cai Y, Liu T, Shen B, Yang F, et al. Characteristics and clinical significance of myocardial injury in patients with severe coronavirus disease 2019. Eur Heart J. 2020; 41:2070-9. Publisher Full Text | DOI | PubMed
  50. Zhang G, Hu C, Luo L, Fang F, Chen Y, Li J, et al. Clinical features and short-term outcomes of 221 patients with COVID-19 in Wuhan, China. J Clin Virol. 2020; 127:104364. Publisher Full Text | DOI | PubMed
  51. Wan S, Xiang Y, Fang W, Zheng Y, Li B, Hu Y, et al. Clinical features and treatment of COVID-19 patients in northeast Chongqing. J Med Virol. 2020; 92:797-806. Publisher Full Text | DOI | PubMed
  52. Zhang J, Liu P, Wang M, Wang J, Chen J, Yuan W, et al. The clinical data from 19 critically ill patients with coronavirus disease 2019: a single-centered, retrospective, observational study. Z Gesundh Wiss. 2022; 30:361-4. Publisher Full Text | DOI | PubMed
  53. Li Y, Hu Y, Yu J, Ma T. Retrospective analysis of laboratory testing in 54 patients with severe- or critical-type 2019 novel coronavirus pneumonia. Lab Invest. 2020; 100:794-800. Publisher Full Text | DOI | PubMed
  54. Shi S, Qin M, Shen B, Cai Y, Liu T, Yang F, et al. Association of Cardiac Injury With Mortality in Hospitalized Patients With COVID-19 in Wuhan, China. JAMA Cardiol. 2020; 5:802-10. Publisher Full Text | DOI | PubMed
  55. Aggarwal S, Garcia-Telles N, Aggarwal G, Lavie C, Lippi G, Henry BM. Clinical features, laboratory characteristics, and outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19): Early report from the United States. Diagnosis (Berl).. 2020; 7:91-6. DOI | PubMed
  56. Yang A, Qiu Q, Kong X, Sun Y, Chen T, Zuo Y, et al. Clinical and Epidemiological Characteristics of COVID-19 Patients in Chongqing China. Front Public Health. 2020; 8:244. Publisher Full Text | DOI | PubMed
  57. Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW, et al. Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area. JAMA. 2020; 323:2052-9. Publisher Full Text | DOI | PubMed
  58. Feng Y, Ling Y, Bai T, Xie Y, Huang J, Li J, et al. COVID-19 with Different Severities: A Multicenter Study of Clinical Features. Am J Respir Crit Care Med. 2020; 201:1380-8. Publisher Full Text | DOI | PubMed
  59. Yang L, Liu J, Zhang R, Li M, Li Z, Zhou X, et al. Epidemiological and clinical features of 200 hospitalized patients with corona virus disease 2019 outside Wuhan, China: A descriptive study. J Clin Virol. 2020; 129:104475. Publisher Full Text | DOI | PubMed
  60. Jin L, Tang W, Song L, Luo L, Zhou Z, Fan X, et al. Acute cardiac injury in adult hospitalized COVID-19 patients in Zhuhai, China. Cardiovasc Diagn Ther. 2020; 10:1303-12. Publisher Full Text | DOI | PubMed
  61. Liu J, Zhang L, Chen Y, Wu Z, Dong X, Teboul JL, et al. Association of sex with clinical outcomes in COVID-19 patients: A retrospective analysis of 1190 cases. Respir Med. 2020; 173:106159. Publisher Full Text | DOI | PubMed
  62. Lombardi CM, Carubelli V, Iorio A, Inciardi RM, Bellasi A, Canale C, et al. Association of Troponin Levels With Mortality in Italian Patients Hospitalized With Coronavirus Disease 2019: Results of a Multicenter Study. JAMA Cardiol. 2020; 5:1274-80. Publisher Full Text | DOI | PubMed
  63. Li J, Zhang Y, Wang F, Liu B, Li H, Tang G, et al. Cardiac damage in patients with the severe type of coronavirus disease 2019 (COVID-19). BMC Cardiovasc Disord. 2020; 20:479. Publisher Full Text | DOI | PubMed
  64. Ghio S, Baldi E, Vicentini A, Lenti MV, Di Sabatino A, Di Matteo A, et al. Correction to: Cardiac involvement at presentation in patients hospitalized with COVID-19 and their outcome in a tertiary referral hospital in Northern Italy. Intern Emerg Med. 2021; 16:807. Publisher Full Text | DOI | PubMed
  65. Lazzeri C, Bonizzoli M, Batacchi S, Cianchi G, Franci A, Fulceri GE, et al. Cardiac Involvment in COVID-19-Related Acute Respiratory Distress Syndrome. Am J Cardiol. 2020; 132:147-9. Publisher Full Text | DOI | PubMed
  66. Fan H, Zhang L, Huang B, Zhu M, Zhou Y, Zhang H, et al. Cardiac injuries in patients with coronavirus disease 2019: Not to be ignored. Int J Infect Dis. 2020; 96:294-7. Publisher Full Text | DOI | PubMed
  67. Guo T, Fan Y, Chen M, Wu X, Zhang L, He T, et al. Cardiovascular Implications of Fatal Outcomes of Patients With Coronavirus Disease 2019 (COVID-19). JAMA Cardiol. 2020; 5:811-8. Publisher Full Text | DOI | PubMed
  68. Ferguson J, Rosser JI, Quintero O, Scott J, Subramanian A, Gumma M, et al. Characteristics and Outcomes of Coronavirus Disease Patients under Nonsurge Conditions, Northern California, USA, March-April 2020. Emerg Infect Dis. 2020; 26:1679-85. Publisher Full Text | DOI | PubMed
  69. Abrams MP, Wan EY, Waase MP, Morrow JP, Dizon JM, Yarmohammadi H, et al. Clinical and cardiac characteristics of COVID-19 mortalities in a diverse New York City Cohort. J Cardiovasc Electrophysiol. 2020; 31:3086-96. Publisher Full Text | DOI | PubMed
  70. Chen G, Wu D, Guo W, Cao Y, Huang D, Wang H, et al. Clinical and immunological features of severe and moderate coronavirus disease 2019. J Clin Invest. 2020; 130:2620-9. Publisher Full Text | DOI | PubMed
  71. Russo V, Di Maio M, Mottola FF, Pagnano G, Attena E, Verde N, et al. Clinical characteristics and prognosis of hospitalized COVID-19 patients with incident sustained tachyarrhythmias: A multicenter observational study. Eur J Clin Invest. 2020; 50:e13387. Publisher Full Text | DOI | PubMed
  72. Xiong S, Liu L, Lin F, Shi J, Han L, Liu H, et al. Clinical characteristics of 116 hospitalized patients with COVID-19 in Wuhan, China: a single-centered, retrospective, observational study. BMC Infect Dis. 2020; 20:787. Publisher Full Text | DOI | PubMed
  73. Li T, Lu L, Zhang W, Tao Y, Wang L, Bao J, et al. Clinical characteristics of 312 hospitalized older patients with COVID-19 in Wuhan, China. Arch Gerontol Geriatr. 2020; 91:104185. Publisher Full Text | DOI | PubMed
  74. Guo T, Shen Q, Guo W, He W, Li J, Zhang Y, et al. Clinical Characteristics of Elderly Patients with COVID-19 in Hunan Province, China: A Multicenter, Retrospective Study. Gerontology. 2020; 66:467-75. DOI | PubMed
  75. He F, Quan Y, Lei M, Liu R, Qin S, Zeng J, et al. Clinical features and risk factors for ICU admission in COVID-19 patients with cardiovascular diseases. Aging Dis. 2020; 11:763-9. Publisher Full Text | DOI | PubMed
  76. Li P, Chen L, Liu Z, Pan J, Zhou D, Wang H, et al. Clinical features and short-term outcomes of elderly patients with COVID-19. Int J Infect Dis. 2020; 97:245-50. Publisher Full Text | DOI | PubMed
  77. Du Y, Tu L, Zhu P, Mu M, Wang R, Yang P, et al. Clinical Features of 85 Fatal Cases of COVID-19 from Wuhan. A Retrospective Observational Study. Am J Respir Crit Care Med. 2020; 201:1372-9. Publisher Full Text | DOI | PubMed
  78. Huang R, Zhu L, Xue L, Liu L, Yan X, Wang J, et al. Clinical findings of patients with coronavirus disease 2019 in Jiangsu province, China: A retrospective, multi-center study. PLoS Negl Trop Dis. 2020; 14:e0008280. Publisher Full Text | DOI | PubMed
  79. Li X, Wang L, Yan S, Yang F, Xiang L, Zhu J, et al. Clinical characteristics of 25 death cases with COVID-19: A retrospective review of medical records in a single medical center, Wuhan, China. Int J Infect Dis. 2020; 94:128-32. Publisher Full Text | DOI | PubMed
  80. Palmieri L, Vanacore N, Donfrancesco C, Lo Noce C, Canevelli M, Punzo O, et al. Clinical Characteristics of Hospitalized Individuals Dying With COVID-19 by Age Group in Italy. J Gerontol A Biol Sci Med Sci. 2020; 75:1796-800. Publisher Full Text | DOI | PubMed
  81. Mughal MS, Kaur IP, Jaffery AR, Dalmacion DL, Wang C, Koyoda S, et al. COVID-19 patients in a tertiary US hospital: Assessment of clinical course and predictors of the disease severity. Respir Med. 2020; 172:106130. Publisher Full Text | DOI | PubMed
  82. Wang ZH, Shu C, Ran X, Xie CH, Zhang L. Critically Ill Patients with Coronavirus Disease 2019 in a Designated ICU: Clinical Features and Predictors for Mortality. Risk Manag Healthc Policy. 2020; 13:833-45. Publisher Full Text | DOI | PubMed
  83. Stefanini GG, Chiarito M, Ferrante G, Cannata F, Azzolini E, Viggiani G, et al. Early detection of elevated cardiac biomarkers to optimise risk stratification in patients with COVID-19. Heart. 2020; 106:1512-8. DOI | PubMed
  84. Wang Y, Chen L, Wang J, He X, Huang F, Chen J, et al. Electrocardiogram analysis of patients with different types of COVID-19. Ann Noninvasive Electrocardiol. 2020; 25:e12806. Publisher Full Text | DOI | PubMed
  85. Heberto AB, Carlos PCJ, Antonio CRJ, Patricia PP, Enrique TR, Danira MPJ, et al. Implications of myocardial injury in Mexican hospitalized patients with coronavirus disease 2019 (COVID-19). Int J Cardiol Heart Vasc. 2020; 30:100638. Publisher Full Text | DOI | PubMed
  86. Li C, Jiang J, Wang F, Zhou N, Veronese G, Moslehi JJ, et al. Longitudinal correlation of biomarkers of cardiac injury, inflammation, and coagulation to outcome in hospitalized COVID-19 patients. J Mol Cell Cardiol. 2020; 147:74-87. Publisher Full Text | DOI | PubMed
  87. Cao J, Zheng Y, Luo Z, Mei Z, Yao Y, Liu Z, et al. Myocardial injury and COVID-19: Serum hs-cTnI level in risk stratification and the prediction of 30-day fatality in COVID-19 patients with no prior cardiovascular disease. Theranostics. 2020; 10:9663-73. Publisher Full Text | DOI | PubMed
  88. Lorente-Ros A, Monteagudo Ruiz JM, Rincon LM, Ortega Perez R, Rivas S, Martinez-Moya R, et al. Myocardial injury determination improves risk stratification and predicts mortality in COVID-19 patients. Cardiol J. 2020; 27:489-96. Publisher Full Text | DOI | PubMed
  89. Yang C, Liu F, Liu W, Cao G, Liu J, Huang S, et al. Myocardial injury and risk factors for mortality in patients with COVID-19 pneumonia. Int J Cardiol. 2021; 326:230-6. Publisher Full Text | DOI | PubMed
  90. Qian H, Gao P, Tian R, Yang X, Guo F, Li T, et al. Myocardial Injury on Admission as a Risk in Critically Ill COVID-19 Patients: A Retrospective in-ICU Study. J Cardiothorac Vasc Anesth. 2021; 35:846-53. Publisher Full Text | DOI | PubMed
  91. Zhao S, Lin Y, Zhou C, Wang L, Chen X, Clifford SP, et al. Short-Term Outcomes of Patients With COVID-19 Undergoing Invasive Mechanical Ventilation: A Retrospective Observational Study From Wuhan, China. Front Med (Lausanne). 2020; 7:571542. Publisher Full Text | DOI | PubMed
  92. Chen FF, Zhong M, Liu Y, Zhang Y, Zhang K, Su DZ, et al. The characteristics and outcomes of 681 severe cases with COVID-19 in China. J Crit Care. 2020; 60:32-7. Publisher Full Text | DOI | PubMed
  93. Lala A, Johnson KW, Januzzi JL, Russak AJ, Paranjpe I, Richter F, et al. Prevalence and Impact of Myocardial Injury in Patients Hospitalized With COVID-19 Infection. J Am Coll Cardiol. 2020; 76:533-46. Publisher Full Text | DOI | PubMed
  94. Karbalai Saleh S, Oraii A, Soleimani A, Hadadi A, Shajari Z, Montazeri M, et al. The association between cardiac injury and outcomes in hospitalized patients with COVID-19. Intern Emerg Med. 2020; 15:1415-24. Publisher Full Text | DOI | PubMed
  95. Xu H, Hou K, Xu H, Li Z, Chen H, Zhang N, et al. Acute myocardial injury of patients with coronavirus disease 2019. MedRxiv. 2020. DOI
  96. Argenziano MG, Bruce SL, Slater CL, Tiao JR, Baldwin MR, Barr RG, et al. Characterization and clinical course of 1000 patients with coronavirus disease 2019 in New York: retrospective case series. BMJ. 2020; 369:m1996. Publisher Full Text | DOI | PubMed
  97. Linschoten M, Peters S, van Smeden M, Jewbali LS, Schaap J, Siebelink HM, et al. Cardiac complications in patients hospitalised with COVID-19. Eur Heart J Acute Cardiovasc Care. 2020; 9:817-23. Publisher Full Text | DOI | PubMed
  98. Saleh A, Matsumori A, Abdelrazek S, Eltaweel S, Salous A, Neumann FJ, et al. Myocardial involvement in coronavirus disease 19. Herz. 2020; 45:719-25. Publisher Full Text | DOI | PubMed
  99. Papageorgiou N, Providencia R, Saberwal B, Sohrabi C, Tyrlis A, Atieh AE, et al. Ethnicity and COVID-19 cardiovascular complications: a multi-center UK cohort. Am J Cardiovasc Dis. 2020; 10:455-62. Publisher Full Text | PubMed
  100. Becerra-Munoz VM, Nunez-Gil IJ, Eid CM, Garcia Aguado M, Romero R, Huang J, et al. Clinical profile and predictors of in-hospital mortality among older patients hospitalised for COVID-19. Age Ageing. 2021; 50:326-34. Publisher Full Text | DOI | PubMed
  101. Yan X, Wang S, Ma P, Yang B, Si D, Liu G, et al. Cardiac injury is associated with inflammation in geriatric COVID-19 patients. J Clin Lab Anal. 2021; 35:e23654. Publisher Full Text | DOI | PubMed
  102. Arcari L, Luciani M, Cacciotti L, Musumeci MB, Spuntarelli V, Pistella E, et al. Incidence and determinants of high-sensitivity troponin and natriuretic peptides elevation at admission in hospitalized COVID-19 pneumonia patients. Intern Emerg Med. 2020; 15:1467-76. Publisher Full Text | DOI | PubMed
  103. Chan JW, Ng CK, Chan YH, Mok TY, Lee S, Chu SY, et al. Short term outcome and risk factors for adverse clinical outcomes in adults with severe acute respiratory syndrome (SARS). Thorax. 2003; 58:686-9. Publisher Full Text | DOI | PubMed
  104. Deng G, Yin M, Chen X, Zeng F. Clinical determinants for fatality of 44,672 patients with COVID-19. Crit Care. 2020; 24:179. Publisher Full Text | DOI | PubMed
  105. Lippi G, Wong J, Henry BM. Hypertension in patients with coronavirus disease 2019 (COVID-19): a pooled analysis. Pol Arch Intern Med. 2020; 130:304-9. DOI | PubMed
  106. Chen Y, Gong X, Wang L, Guo J. Effects of hypertension, diabetes and coronary heart disease on COVID-19 diseases severity: a systematic review and meta-analysis. MedRxiv. 2020. DOI
  107. Emami A, Javanmardi F, Pirbonyeh N, Akbari A. Prevalence of Underlying Diseases in Hospitalized Patients with COVID-19: a Systematic Review and Meta-Analysis. Arch Acad Emerg Med. 2020; 8:e35. Publisher Full Text | PubMed
  108. Schiffrin EL, Flack JM, Ito S, Muntner P, Webb RC. Hypertension and COVID-19. Am J Hypertens. 2020; 33:373-4. Publisher Full Text | DOI | PubMed
  109. Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, et al. Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China. JAMA Intern Med. 2020; 180:934-43. Publisher Full Text | DOI | PubMed
  110. Momtazmanesh S, Shobeiri P, Hanaei S, Mahmoud-Elsayed H, Dalvi B, Malakan Rad E. Cardiovascular disease in COVID-19: a systematic review and meta-analysis of 10,898 patients and proposal of a triage risk stratification tool. Egypt Heart J. 2020; 72:41. Publisher Full Text | DOI | PubMed
  111. Zou F, Qian Z, Wang Y, Zhao Y, Bai J. Cardiac Injury and COVID-19: A Systematic Review and Meta-analysis. CJC Open. 2020; 2:386-94. Publisher Full Text | DOI | PubMed
  112. Cheng Y, Luo R, Wang K, Zhang M, Wang Z, Dong L, et al. Kidney disease is associated with in-hospital death of patients with COVID-19. Kidney Int. 2020; 97:829-38. Publisher Full Text | DOI | PubMed
  113. Tomasoni D, Italia L, Adamo M, Inciardi RM, Lombardi CM, Solomon SD, et al. COVID-19 and heart failure: from infection to inflammation and angiotensin II stimulation. Searching for evidence from a new disease. Eur J Heart Fail. 2020; 22:957-66. Publisher Full Text | DOI | PubMed
  114. South AM, Diz DI, Chappell MC. COVID-19, ACE2, and the cardiovascular consequences. Am J Physiol Heart Circ Physiol. 2020; 318:H1084-H90. Publisher Full Text | DOI | PubMed
  115. Li B, Yang J, Zhao F, Zhi L, Wang X, Liu L, et al. Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China. Clin Res Cardiol. 2020; 109:531-8. Publisher Full Text | DOI | PubMed
  116. Pellicori P, Doolub G, Wong CM, Lee KS, Mangion K, Ahmad M, et al. COVID-19 and its cardiovascular effects: a systematic review of prevalence studies. Cochrane Database Syst Rev. 2021; 3:CD013879. Publisher Full Text | DOI | PubMed
  117. Bhatla A, Mayer MM, Adusumalli S, Hyman MC, Oh E, Tierney A, et al. COVID-19 and cardiac arrhythmias. Heart Rhythm. 2020; 17:1439-44. Publisher Full Text | DOI | PubMed
  118. Mancia G, Rea F, Ludergnani M, Apolone G, Corrao G. Renin-Angiotensin-Aldosterone System Blockers and the Risk of Covid-19. N Engl J Med. 2020; 382:2431-40. Publisher Full Text | DOI | PubMed
  119. Driggin E, Madhavan MV, Bikdeli B, Chuich T, Laracy J, Biondi-Zoccai G, et al. Cardiovascular Considerations for Patients, Health Care Workers, and Health Systems During the COVID-19 Pandemic. J Am Coll Cardiol. 2020; 75:2352-71. Publisher Full Text | DOI | PubMed
  120. Oudit GY, Kassiri Z, Jiang C, Liu PP, Poutanen SM, Penninger JM, et al. SARS-coronavirus modulation of myocardial ACE2 expression and inflammation in patients with SARS. Eur J Clin Invest. 2009; 39:618-25. Publisher Full Text | DOI | PubMed
  121. Li X, Pan X, Li Y, An N, Xing Y, Yang F, et al. Cardiac injury associated with severe disease or ICU admission and death in hospitalized patients with COVID-19: a meta-analysis and systematic review. Crit Care. 2020; 24:468. Publisher Full Text | DOI | PubMed
  122. Chen C, Chen C, Yan JT, Zhou N, Zhao JP, Wang DW. [Analysis of myocardial injury in patients with COVID-19 and association between concomitant cardiovascular diseases and severity of COVID-19]. Zhonghua Xin Xue Guan Bing Za Zhi. 2020; 48:567-71. DOI | PubMed
  123. Wang JT, Sheng WH, Fang CT, Chen YC, Wang JL, Yu CJ, et al. Clinical manifestations, laboratory findings, and treatment outcomes of SARS patients. Emerg Infect Dis. 2004; 10:818-24. Publisher Full Text | DOI | PubMed
  124. Welt FGP, Shah PB, Aronow HD, Bortnick AE, Henry TD, Sherwood MW, et al. Catheterization Laboratory Considerations During the Coronavirus (COVID-19) Pandemic: From the ACC’s Interventional Council and SCAI. J Am Coll Cardiol. 2020; 75:2372-5. Publisher Full Text | DOI | PubMed
  125. Peiris JS, Chu CM, Cheng VC, Chan KS, Hung IF, Poon LL, et al. Clinical progression and viral load in a community outbreak of coronavirus-associated SARS pneumonia: a prospective study. Lancet. 2003; 361:1767-72. Publisher Full Text | DOI | PubMed
  126. Cooper. Myocarditis. N Engl J Med. 2009; 360:1526-38. Publisher Full Text | DOI | PubMed
  127. Nicholson KG, Webster RG, Hay AJ. Textbook of influenza. Blackwell Science Ltd: New Jersey; 1998.
  128. Daniels CJ, Rajpal S, Greenshields JT, Rosenthal GL, Chung EH, Terrin M, et al. Prevalence of Clinical and Subclinical Myocarditis in Competitive Athletes With Recent SARS-CoV-2 Infection: Results From the Big Ten COVID-19 Cardiac Registry. JAMA Cardiol. 2021; 6:1078-87. Publisher Full Text | DOI | PubMed
  129. Vasudevan G, Mercer DW, Varat MA. Lactic dehydrogenase isoenzyme determination in the diagnosis of acute myocardial infarction. Circulation. 1978; 57:1055-7. DOI | PubMed
  130. Ndrepepa G, Kastrati A. Creatine kinase myocardial band - a biomarker to assess prognostically relevant periprocedural myocardial infarction. Int J Cardiol. 2018; 270:118-9. DOI | PubMed
  131. O’Brien PJ. Cardiac troponin is the most effective translational safety biomarker for myocardial injury in cardiotoxicity. Toxicology. 2008; 245:206-18. DOI | PubMed
  132. Aydin S, Ugur K, Aydin S, Sahin I, Yardim M. Biomarkers in acute myocardial infarction: current perspectives. Vasc Health Risk Manag. 2019; 15:1-10. Publisher Full Text | DOI | PubMed
  133. Heinova D, Rosival I, Avidar Y, Bogin E. Lactate dehydrogenase isoenzyme distribution and patterns in chicken organs. Res Vet Sci. 1999; 67:309-12. DOI | PubMed