Right Ventricular Dysfunction on Transthoracic Echocardiography and Long-Term Mortality in the Critically Unwell: A...

Right ventricular dysfunction (RVD) is common in the critically ill. To date studies exploring RVD sequelae have had heterogenous definitions and diagnostic methods, with limited follow-up. Additionally much literature has been pathology specific, limiting applicability to the general critically unwell patient.

We conducted a systematic review and meta-analysis to evaluate the impact of RVD diagnosed with transthoracic echocardiography (TTE) on long-term mortality in unselected critically unwell patients compared to those without RVD. A systematic search of EMBASE, Medline and Cochrane was performed from inception to March 2022. All RVD definitions using TTE were included. Patients were those admitted to a critical or intensive care unit, irrespective of disease processes. Long-term mortality was defined as all-cause mortality occurring at least 30 days after hospital admission. A priori subgroup analyses included disease specific and delayed mortality (death after hospital discharge/after the 30^th day from hospital admission) in patients with RVD. A random effects model analysis was performed with the Dersimionian and Laird inverse variance method to generate effect estimates.

Of 5985 studies, 123 underwent full text review with 16 included (n = 3196). 1258 patients had RVD. 19 unique RVD criteria were identified. The odds ratio (OR) for long term mortality with RVD was 2.92 (95% CI 1.92-4.54, I² 76.4%) compared to no RVD. The direction and extent was similar for cardiac and COVID19 subgroups. Isolated RVD showed an increased risk of delayed mortality when compared to isolated left/biventricular dysfunction (OR 2.01, 95% CI 1.05-3.86, I² 46.8%).

RVD, irrespective of cause, is associated with increased long term mortality in the critically ill. Future studies should be aimed at understanding the pathophysiological mechanisms by which this occurs. Commonly used echocardiographic definitions of RVD show significant heterogeneity across studies, which contributes to uncertainty within this dataset.