Right Ventricular Dysfunction: Predictor Of Mortality In COVID-19 Infection

INTRODUCTION: COVID-19 infection has been associated with right ventricular (RV) dysfunction and poor prognosis. This association is thought to be due to either a direct effect of COVID-19 infection on the myocardium or indirect damage to the lung parenchyma or vasculature. Limited echocardiography protocols for operator protection against COVID-19 has made the evaluation of the RV challenging. The purpose of this study is to evaluate if RV dysfunction by qualitative assessment can be used to predict all-cause mortality. METHODS: This is a single-center retrospective analysis from March 2020 to August 2021. Patients who were older than 18 years old, hospitalized with a positive RT-PCR for COVID-19, and had an echocardiogram while inpatient were included in the study. RV parameters, including RV dilation and dysfunction, were obtained by qualitative assessment. Data analysis was performed with STATA and SPSS. RESULTS: A total of 223 patients were included in the analysis. 59.6% were male with a mean age of 64.3 years (SD +/- 16). 67.7% were Hispanic, 11.7% were non-Hispanic White, and 20.6% were Black. Severe COVID-19 infection requiring intensive care unit level of care made up 54.7% of cases (n=122) and the mortality rate was 27.8% (n=62). RV dysfunction and dilation was present in 13.5% (n=28) and 15.2% (n=33) of patients, respectively and occurred more often in patients with severe COVID-19 infection (p<0.01). Logistic binomial correlation showed an exponential increase in the probability of mortality related to RV dysfunction (OR 2.03, p=0.270; graph 1) and a mild decrease in mortality in patients with RV dilation (OR 0.88, p=0.794). However, both associations were not statistically significant. CONCLUSION: RV dysfunction by qualitative assessment could be a potential marker of mortality in patients with COVID-19 infection. The association may be stronger in studies with more power. Interestingly, RV dilation was associated with a mild decrease in mortality in this patient population; however, this may be a biased result due to the small sample size.