P1764 A unifying concept for the quantitative definition of functional mitral regurgitation. (17th January 2020) - Bartko, P; Arfsten, H; Heitzinger, G; Pavo, N; Toma, A; Strunk, G; Hengstenberg, C; Huelsmann, M; Goliasch, G
Abstract: Background: Diverging guideline definitions for the quantitative assessment of severe secondary mitral regurgitation (sMR) reflect the lacking link of the sMR spectrum to mortality and has introduced a source of uncertainty and continuing debate. Objectives: The current study aimed to define improved risk-thresholds specifically tailored to the complex nature of sMR that provide a unifying solution to the ongoing guideline-controversy. Methods: We enrolled 423 heart failure patients under guideline directed medical therapy and assessed sMR by effective regurgitant orifice area (EROA), regurgitant volume (RegVol) and regurgitant fraction (RegFrac). Results: Measures of sMR severity were consistently associated with 5-year mortality with a HR for a 1-SD increase of 1.42 (95%CI 1.25-1.63, P < 0.001) for EROA, 1.37 (95%CI 1.20-1.56, P < 0.001) for RegVol and 1.50 (95%CI 1.30-1.73, P < 0.001) for RegFrac. Results remained statistically significant after bootstrap- or clinical confounder-based adjustment. Spline-curve analyses (Figure 1A-C) showed a linearly increasing risk enabling to stratify in low-risk (EROA < 20mm2 and RegVol < 30ml), intermediate-risk (EROA 20-30mm2 and RegVol 30-45ml) and, high-risk (EROA≥30mm2 and RegVol≥45ml). In the intermediate-risk group, a RegFrac ≥50% as indicator for hemodynamic severe sMR was associated with poor outcome (P = 0.017). A unifying concept based on combined assessment of the EROA, the RegVol, and the RegFrac (Figure 1D) showed a significantly better discrimination compared to the currently established algorithms (Table 1). Conclusions: Risk-based thresholds tailored to the pathophysiological concept of sMR provide a unifying solution to the ongoing guideline controversy. An algorithm based on the combined assessment of the unifying cut-offs for EROA, RegVol and RegFrac improves risk prediction compared to currently established grading.