ABSTRACT
Multiomics approaches need to be applied in the central Arctic Ocean to benchmark biodiversity change and to identify novel species and their genes. As part of MOSAiC, EcoOmics will therefore be essential for conservation and sustainable bioprospecting in one of the least explored ecosystems on Earth.
Subject(s)
Benchmarking , Ecosystem , Arctic Regions , Biodiversity , Oceans and SeasABSTRACT
AIMS: The objective of this study was to examine the impact of guideline-defined subtypes of severe aortic stenosis (AS) on long-term outcomes after TAVI. METHODS AND RESULTS: Four hundred (400) consecutive patients who underwent TAVI (203 transapical, 197 transfemoral) at our institution 8/2008-3/2013 were followed systematically (for up to seven years). One hundred and forty-seven (147) individuals suffered from NEF-HG AS (LV-EF ≥50%, high Pmean ≥40 mmHg), 63 from LEF-HG AS (LV-EF <50%, high gradient), 77 from PLF-LG AS (LV-EF ≥50%, low gradient, stroke volume index [SVI] <35 ml/m²), and 81 from LEF-LG AS (LV-EF <50%, low gradient). LEF-LG status was associated with the highest all-cause and cardiovascular mortality and MACCE rate, whereas NEF-HG patients exhibited the best outcome (i.e., median survival 5.1 years in NEF-HG vs. 1.3 years in LEF-LG, p=0.0006; or vs. 3.3 years in PLF-LG, p=0.02). In multivariate analysis, LEF-LG status emerged as the outcome predictor with the highest hazard ratio for all-cause mortality (HR 2.86, p=0.003), cardiovascular mortality (HR 6.53, p<0.0001), and MACCE (HR 2.44, p=0.007), whereas neither baseline EF nor SVI <35 ml/m² independently predicted these endpoints. CONCLUSIONS: These findings suggest that an assessment of LV-EF alone for outcome prediction after TAVI is inadequate; it is the guideline-defined subtype of AS that determines outcome.
