The Prognostic Value of Right Atrial and Right Ventricular Functional Parameters in Systemic Sclerosis

FRONTIERS IN CARDIOVASCULAR MEDICINE(2022)

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摘要
IntroductionRight ventricular (RV) function is of particular importance in systemic sclerosis (SSc), since common SSc complications, such as interstitial lung disease and pulmonary hypertension may affect RV afterload. Cardiovascular magnetic resonance (CMR) is the gold standard for measuring RV function. CMR-derived RV and right atrial (RA) strain is a promising tool to detect subtle changes in RV function, and might have incremental value, however, prognostic data is lacking. Therefore, the aim of this study was to evaluate the prognostic value of RA and RV strain in SSc. MethodsIn this retrospective study, performed at two Dutch hospitals, consecutive SSc patients who underwent CMR were included. RV longitudinal strain (LS) and RA strain were measured. Unadjusted cox proportional hazard regression analysis and likelihood ratio tests were used to evaluate the association and incremental value of strain parameters with all-cause mortality. ResultsA total of 100 patients (median age 54 [46-64] years, 42% male) were included. Twenty-four patients (24%) died during a follow-up of 3.1 [1.8-5.2] years. RA reservoir [Hazard Ratio (HR) = 0.95, 95% CI 0.91-0.99, p = 0.009] and conduit strain (HR = 0.93, 95% CI 0.88-0.98, p = 0.008) were univariable predictors of all-cause mortality, while RV LS and RA booster strain were not. RA conduit strain proved to be of incremental value to sex, atrial fibrillation, NYHA class, RA maximum volume indexed, and late gadolinium enhancement (p < 0.05 for all). ConclusionRA reservoir and conduit strain are predictors of all-cause mortality in SSc patients, whereas RV LS is not. In addition, RA conduit strain showed incremental prognostic value to all evaluated clinical and imaging parameters. Therefore, RA conduit strain may be a useful prognostic marker in SSc patients.
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关键词
systemic sclerosis, right ventricular function, right atrial strain, feature tracking, prognosis
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