Screening for Transcatheter Mitral Valve Replacement: A Decision Tree Algorithm
High frequency of screen 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 is scarce. The present study aimed to develop a...
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| Vydané v: | EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology Ročník 16; číslo 3; s. 251 |
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| Hlavní autori: | , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
France
01.06.2020
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| ISSN: | 1969-6213, 1969-6213 |
| On-line prístup: | Zistit podrobnosti o prístupe |
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| Shrnutí: | High frequency of screen 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 is scarce. The present study aimed to develop a screening algorithm based on TMVR screening data.
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 screen failure were assessed, and a decision tree algorithm was statistically derived. Reasons for screen 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).
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 screen failure, this algorithm may facilitate the identification of potential TMVR candidates. |
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| Bibliografia: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1969-6213 1969-6213 |
| DOI: | 10.4244/EIJ-D-19-01051 |