Role of right ventricular free wall longitudinal strain in prediction outcome in patients with cardiac sarcoidosis

Abstract

Abstract Introduction Right ventricular free wall longitudinal strain (RVFWLS) is a sensitive tool for right ventricular (RV) function assessment. Furthermore, it shows incremental prognostic role in various cardiac diseases. RV involvement is frequently observed along with left ventricular (LV) involvement in cardiac sarcoidosis (CS) patients, while its impact on outcome is unclear. Purpose The aim of this study is to investigate the association between RV dysfunction detected by RVFWLS and cardiovascular event in patients with CS. Methods We retrospectively evaluated 51 patients with CS who were treated with prednisone from 2012 through 2020. Diagnosis of CS was made according to the Japanese Circulation Society diagnostic criteria. We evaluated RVFWLS at baseline using vender-independent software. We considered major adverse cardiovascular event (MACE: ventricular arrhythmia, heart failure hospitalization) to be the primary outcome. Results Mean age of the study population was 63±11 years, and 61% were female. At baseline, 25 patients (49%) had reduced left ventricular (LV) ejection fraction (EF) (<50%) and 18 patients (35%) had impaired RVFWLS (<17%). Patients with impaired RVFWLS showed lower LVEF% (42±12% vs. 53±13%, P=0.005) and larger LV end-systolic volume index (54±33 vs. 37±23ml/m2, P=0.04) compared with those with preserved RVFWLS. Impaired RVFWLS patients also showed trend towards higher prevalence of basal interventricular thinning (50 vs. 28%, P=0.12). During a median follow-up of 548 days, eleven patients had MACE. In multivariable Cox-proportional hazards model analysis, RVFWLS was independently associated with MACE (HR 1.28, 95% CI: 1.07–1.10, P=0.009). Kaplan-Meier survival curves showed worse event-free survival in patients with impaired RVFWLS (log-rank test, P=0.001). Conclusions In patients with CS, RVFWLS is an independent predictor for MACE. RVFWLS may be valuable in improving risk stratification in CS. Funding Acknowledgement Type of funding sources: None. Kaplan-Meier survival curves