Key result
A four-step decision tree algorithm based on MSCT criteria predicted anatomical eligibility for transcatheter mitral valve replacement with an AUC of 0.80 (95% CI 0.71-0.89; p<0.0001).
Why the study?
Screening failure for anatomical reasons is frequent in patients with severe MR being screened for TMVR, but data on optimal patient selection are scarce.
Does a decision tree algorithm based on MSCT criteria predict anatomical eligibility for TMVR in high-risk patients with severe MR?
Observational (n=94)
Does a decision tree algorithm based on MSCT criteria predict anatomical eligibility for TMVR in high-risk patients with severe MR?
A novel four-step decision tree algorithm based on MSCT criteria can predict anatomical eligibility for TMVR with an AUC of 0.80, potentially streamlining patient selection.
Answers are grounded in this paper and cite their sources.
May reduce anatomical screening failures for TMVR; hypothesis-generating and requires prospective validation before adoption.
AIMS: The high frequency of screening failure for anatomical reasons in patients with severe mitral valve regurgitation (MR) is a limiting factor in the screening process for transcatheter mitral valve replacement (TMVR). However, data on optimal patient selection are scarce. The present study aimed to develop a screening algorithm based on TMVR screening data. METHODS AND RESULTS: A total of 195 screenings for six different TMVR devices were performed in 94 high-risk patients with severe MR. We compared baseline echocardiographic and multislice computed tomography (MSCT) parameters between the subgroups of patients accepted (N=33) and rejected for TMVR (N=61). Reasons for screening failure were assessed, and a decision tree algorithm was statistically derived. Reasons for screening failure were small LV dimensions (30.6%), small (7.5%) or large (22.5%) annular size, potential risk of LVOT obstruction (22.0%) or mitral annulus calcification (15.6%). A four-step decision tree algorithm to assess TMVR eligibility was developed resulting in an AUC of 0.80 (95% CI: 0.71, 0.89, p<0.0001). CONCLUSIONS: This study presents the first screening algorithm to assess anatomical eligibility for TMVR in patients with severe MR, based on simple MSCT criteria. Given the high rate of TMVR screening failure, this algorithm may facilitate the identification of potential TMVR candidates.
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Ludwig et al. (2020) conducted an observational in Severe mitral valve regurgitation (n=94). Four-step decision tree algorithm was evaluated on TMVR eligibility assessment (AUC 0.80, 95% CI 0.71, 0.89, p=<0.0001). A four-step decision tree algorithm based on MSCT criteria predicted anatomical eligibility for transcatheter mitral valve replacement with an AUC of 0.80 (95% CI 0.71-0.89; p<0.0001).
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