Assessment of chronic aortic regurgitation using end-diastolic flow reversal in the upper descending aorta: diagnostic accuracy and prediction of aortic valve surgery in a prospective echocardiography and cardiac magnetic resonance imaging study
摘要
This study aimed to assess the utility of end-diastolic flow reversal in the upper descending aorta (EFR) for echocardiographic grading of aortic regurgitation (AR) severity, using cardiac magnetic resonance imaging (CMRI) as the reference. Additionally, we evaluated the role of EFR in predicting the need for aortic valve (AV) surgery during mid-term follow-up.
MethodsSixty-six patients (mean age 53 ± 15.0 years, 73% men) underwent echocardiographic assessment, including (semi-)quantitative parameters such as proximal isovelocity surface area (PISA), effective regurgitation orifice area (EROA), AR volume (AR-Vol), vena contracta (VC) and EFR, compared against CMR-derived regurgitant fraction (RF). Multivariable regression analysis was applied evaluating predictors for severe AR and AV surgery.
ResultsAccording to CMRI, 13 patients had no, 16 mild, 18 moderate and 19 severe AR. All echocardiographic parameters demonstrated good diagnostic accuracy (AUC: EFR 0.84, VC 0.82, PISA 0.84, EROA 0.83, AR-Vol 0.86; all p < 0.001). Logistic regression identified EFR (p = 0.022) and VC (p = 0. 015) as significant predictors of severe AR. During 62 months follow-up, 16 of 53 patients (24%) underwent AV surgery. All echocardiographic parameters, except PHT, were significantly different between patients receiving AV surgery compared to patients without surgery (PISA, EROA, AR-Vol and VC p < 0.001, EFR p = 0.043). However, VC remained the only parameter significantly associated with time to AV surgery (Cox-regression analysis, p = 0.024).
ConclusionsEFR is a robust and reliable parameter for AR assessment, particularly in distinguishing moderate from severe AR, and should be incorporated into comprehensive echocardiographic assessment. However, VC demonstrated stronger prognostic relevance for predicting surgical intervention.