Screening for transcatheter mitral valve replacement: a decision tree algorithm.

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.

Maintaining accuracy at the expense of speed: stimulus similarity defines odor discrimination time in mice.

Odor discrimination times and their dependence on stimulus similarity were evaluated to test temporal and spatial models of odor representation in mice. In a go/no-go operant conditioning paradigm, discrimination accuracy and time were determined for simple monomolecular odors and binary mixtures of odors. Mice discriminated simple odors with an accuracy exceeding 95%. Binary mixtures evoking highly overlapping spatiotemporal patterns of activity in the olfactory bulb were discriminated equally well. However, while discriminating simple odors in less than 200 ms, mice required 70-100 ms more time to discriminate highly similar binary mixtures. We conclude that odor discrimination in mice is fast and stimulus dependent. Thus, the underlying neuronal mechanisms act on a fast timescale, requiring only a brief epoch of odor-specific spatiotemporal representations to achieve rapid discrimination of dissimilar odors. The fine discrimination of highly similar stimuli, however, requires temporal integration of activity, suggesting a tradeoff between accuracy and speed.