Cardiovascular disease in COVID-19: a systematic review and meta-analysis of 10,898 patients and proposal of a triage risk stratification tool

Coronavirus disease 2019 (COVID-19) pandemic has drastically affected global health. Despite several studies, there is yet a dearth of data regarding the mechanisms of cardiac injury, clinical presentation, risk factors, and treatment of COVID-19-associated cardiovascular disease. This systematic review and meta-analysis is aimed at defining the clinical, electrocardiographic, and pathologic spectrum of cardiovascular disease (CVD), frequency of elevated cardiac and inflammatory biomarkers, and their frequency and relationship with severity of the disease and mortality in COVID-19 patients and to develop a triage risk stratification tool (TRST) that can serve as a guide for the timely recognition of the high-risk patients and mechanism-targeted therapy. We conducted an online search in databases of PubMed and Embase to identify relevant studies. Data selection was in concordance with PRISMA guidelines. Results were presented as pooled frequencies, odds ratio, standardized mean difference (SMD), and forest and funnel plots. We gathered a total of 54 studies and included 35 of them in our meta-analysis. Acute cardiac injury occurred in more than 25% of cases, mortality was 20 times higher, and admission to intensive care unit increased by 13.5 times. Hypertension was the most common pre-existing comorbidity with a frequency of 29.2%, followed by diabetes mellitus (13.5%). The deceased group of patients had higher cardiac and inflammatory biomarkers, with statistically significant SMD, compared with survivors. Pediatric patients were predominantly mildly affected. However, less frequently, the presentation was very similar to Kawasaki disease or Kawasaki shock syndrome. This latter presentation hass been called as multisystem inflammatory syndrome in children (MIS-C). There is a wide spectrum of cardiac involvement in COVID-19 patients, and hence a Triage Risk Stratification Tool can serve as a guide for the timely recognition of the high-risk patients and mechanism-targeted therapy.