The prognostic value of myocardial injury in COVID-19 patients and associated characteristics

Background: Since December 2019, coronavirus disease 2019 (COVID-19) has emerged as an international pandemic. COVID-19 patients with myocardial injury might need special attention. However, an understanding on this aspect remains unclear. This study aimed to illustrate clinical characteristics and the prognostic value of myocardial injury to COVID-19 patients. Methods: This retrospective, single-center study finally included 304 hospitalized COVID-19 cases confirmed by real-time reverse-transcriptase polymerase chain reaction from January 11 to March 25, 2020. Myocardial injury was determined by serum high-sensitivity troponin I (Hs-TnI). The primary endpoint was COVID-19-associated mortality. Results: Of 304 COVID-19 patients (median age, 65 years; 52.6% males), 88 patients (27.3%) died (61 patients with myocardial injury, 27 patients without myocardial injury on admission). COVID-19 patients with myocardial injury had more comorbidities (hypertension, chronic obstructive pulmonary disease, cardiovascular disease, and cerebrovascular disease); lower lymphocyte counts, higher C-reactive protein (CRP; median, 84.9 vs. 28.5 mg/L; p <.001), procalcitonin levels (median, 0.29 vs. 0.06 ng/ml; p <.001), inflammatory and immune response markers; more frequent need for noninvasive ventilation, invasive mechanical ventilation; and was associated with higher mortality incidence (hazard ratio [HR] = 7.02; 95% confidence interval [CI], 4.45-11.08; p <.001) than those without myocardial injury. Myocardial injury (HR = 4.55; 95% CI, 2.49-8.31; p <.001), senior age, CRP levels, and novel coronavirus pneumonia types on admission were independent predictors to mortality in COVID-19 patients. Conclusions: COVID-19 patients with myocardial injury on admission is associated with more severe clinical presentation and biomarkers. Myocardial injury and higher Hs-TnI are both strongest independent predictors to COVID-19-related mortality after adjusting confounding factors.