Mitral valve anatomic predictors of hemodynamic success with transcatheter mitral valve repair

Background--Mitral regurgitation is a heterogeneous disease. Determining which patients derive optimal outcomes from transcatheter edge-to-edge mitral valve repair (TMVR) remains challenging. We sought to determine whether baseline mitral valve anatomic characteristics are predictive of left atrial pressure (LAP) changes during TMVR with MitraClip. Methods and Results--Consecutive patients with severe mitral regurgitation undergoing TMVR (n=112) underwent continuous intraprocedural LAP monitoring and retrospective echocardiographic analysis for specific mitral anatomic characteristics. Procedural success (optimal LAP reduction) was defined as ≥40% reduction in left atrial V-wave pressure compared with baseline. Echocardiographic predictors of optimal LAP reduction and increased postprocedure mean diastolic gradient were evaluated. Mean age was 79±14 years, and 36 patients (32%) were women. Primary, mixed, and secondary mitral regurgitation were present in 78 patients (70%), 22 patients (20%), and 12 patients (10%), respectively. Baseline mean LAP and V-wave were 22±6 and 38±13 mm Hg; after TMVR, these decreased to 19±5 and 27±10 mm Hg, respectively (P < 0.0001 for both). Independent predictors of optimal LAP reduction were the presence of a flail scallop, mitral regurgitation localized to a single scallop, and highquality 3-dimensional echocardiographic imaging. Independent predictors of elevated postprocedure mean diastolic gradient were elevated preprocedure mean diastolic gradient, mitral annular calcification, and implantation of multiple clips. Conclusions--Mitral valve pathoanatomic features, including a flail leaflet and single jet, are predictive of optimal LAP reduction with TMVR. High-quality 3-dimensional imaging may help select patients with the highest likelihood of optimal hemodynamic results with TMVR. These data expand current knowledge about patient selection for TMVR and deserve further study in larger cohorts.