Long-Term Valve Durability in Patients Undergoing Transcatheter Aortic Valve Implantation

AIMS To evaluate the long-term incidence of structural valve deterioration (SVD) in patients who underwent transcatheter aortic valve implantation (TAVI). METHOD AND RESULTS Between 2008 and 2018, 693 underwent TAVI at two centres. Four hundred and twenty-one (421) patients (mean age 83.6±6.0 yrs) survived for ≥2 years post TAVI and had at least two consecutive transthoracic echocardiographies (TTEs) with the latest TTE no less than 2 years after TAVI, and were therefore included in the analysis for SVD. Median follow-up was 4.7 (3.6-6.0) years and median echocardiography follow-up 3 (3.0-4.0) years. All-cause mortality was 30.9% (130) with a median time to death of 4.1 (3.0-5.6) years. The cumulative incidence of SVD increased from 1.7% (95% CI, 0.4-2.9) at 3 years to 3.5% (95% CI, 1.5-5.8) at 5 years and 4.7% (95% CI, 1.6-7.9) at 10 years. The overall median time to SVD was 3 (2-4) years. Twelve (12) patients demonstrated SVD stage 2, and 1 patient stage 3. No SVD required re-intervention. All other patients showed no significant changes in valve parameters over time. CONCLUSIONS Structural valve deterioration is an uncommon event, occurring in 5% over a total follow-up of 10 years. Most patients show stable valve parameters. However, the analysis is limited by the loss of follow-up (owing to patient mortality), which renders extrapolation of the data to a younger patient population difficult

Transcatheter aortic valve-in-valve implantation for failed surgical bioprosthetic valves. A minimalist approach without contrast aortography or echocardiographic guidance

Objectives: To demonstrate safety, feasibility and short-term clinical outcomes after transcatheter aortic valve-in-valve (ViV) implantation under local anesthesia without contrast aortography or echocardiographic guidance. Background: Transcatheter ViV implantation is an emerging treatment modality for patients with degenerative surgical bioprostheses. Given the radiopaque properties of the surgical aortic valve (SAV) frame, ViV procedures can often be performed with fluoroscopic guidance alone. Methods: ViV implantation was performed in 37 patients with SAV failure under local anesthesia without contrast aortography. Clinical and echocardiographic data were obtained at baseline, discharge, and 30 days. Results: Mean age was 74 ± 10 years and STS predicted risk of mortality was 5.6 ± 2.4%. Mean transaortic gradient decreased from 39.4 ± 15.5 mmHg to 13 ± 6.3 mmHg at discharge (

Impact of Gender on Transcatheter Aortic Valve Implantation Outcomes

Previous studies indicate that women who underwentwho underwent transcatheter aortic valve implantation (TAVI) have poorer 30-day outcomes compared with men. However, the effect of gender as a prognostic factor for long-term outcomes following TAVI remains unclear. Between 2008 and 2018, all patients (n = 683) who underwent TAVI in 2 centres in Melbourne, Australia were prospectively included in a registry. The primary end-point was long-term mortality. The secondary end points were Valve Academic Research Consortium-2 (VARC-2) in-hospital complications and mortality at 30-days and 1-year. Of 683 patients, 328 (48%) were women. Women had a higher mean STS-PROM score (5.2 ± 3.1 vs 4.6 ± 3.5, p < 0.001) but less co-morbidities than men. Women had a significantly higher in-hospital bleeding rates (3.3% vs 1.0%, Odds Ratio 4.21, 95% confidence interval [CI] 1.16 to15.25, p = 0.027) and higher 30-day mortality (2.4% vs 0.3%, hazard ratio [HR] 8.75, 95% CI 1.09 to 69.6, p = 0.040) than men. Other VARC-2 outcomes were similar between genders. Overall mortality rate was 36% (246) over a median follow up of 2.7 (interquartile rang [IQR] 1.7 to 4.2) years. Median time to death was 5.3 (95% CI 4.7 to 5.7) years. One-year mortality was similar between genders (8.3% vs 7.8%), as was long-term mortality (HR = 0.91, 95% CI 0.71 to 1.17, p = 0.38). On multivariable analysis, female gender was an independent predictor for 1-year mortality (HR = 2.33, 95% CI 1.11 to 4.92, p = 0.026), but not long-term mortality (HR = 0.78, 95% CI 0.54 to 1.14, p = 0.20). In the women only cohort, STS-PROM was the only independent predictor of long-term mortality (HR 1.88, 95% CI 1.42 to 2.48, p < 0.001). In conclusion, women had higher rates of peri-procedural major bleeding and 30-day mortality following TAVI. However, long-term outcomes were similar between genders

Dissolved trace element concentrations and fluxes in the Irrawaddy, Salween, Sittaung and Kaladan Rivers.

The Irrawaddy (Ayeyarwaddy) and Salween (Thanlwin) globally rank among the largest rivers for supplying dissolved and particulate material to the ocean. Along with the Sittaung and Kaladan rivers they have societal importance to Myanmar in terms water sources and food production. Despite their importance for global biogeochemical cycles and the ~50 million people who live in their catchments, the chemistry of these rivers is poorly known. This study presents a comprehensive survey of dissolved (<0.22 μm) trace element concentrations (Sr, Fe, Al, Ba, Mn, V, Rb, Cu, Zn, As, Li, Ni, Mo, Cr, U, Pb, Sb, Co, Cs, Tl and Cd) at 38 locations within these river catchments, spanning a period of 2 years. The results highlight the global importance of the Irrawaddy and Salween rivers for trace element global biogeochemical cycles; contributing between 1 and 17 % of global dissolved riverine fluxes to the land-ocean interface for the studied elements. Area normalized dissolved fluxes in these catchments are ~2 to 10 times higher than global average values for most elements, consistent with high rates of chemical weathering. In general, anthropogenic activities have yet to significantly perturb dissolved trace element fluxes in these river systems. The presented dataset should therefore serve as a useful 'natural' baseline, against which future perturbations driven by climate change and/or the development of Myanmar's mining industry could be assessed. Exceptions to this include As in the Sittaung River and Sb, Zn, Pb and As in the Salween River, which may already be significantly impacted by anthropogenic inputs. The former represents a water quality issue of concern for public health, and so constraining the exact sources of As in the Sittaung River should be considered a priority for future research

Prediction of acute coronary syndromes by urinary proteome analysis.

Identification of individuals who are at risk of suffering from acute coronary syndromes (ACS) may allow to introduce preventative measures. We aimed to identify ACS-related urinary peptides, that combined as a pattern can be used as prognostic biomarker. Proteomic data of 252 individuals enrolled in four prospective studies from Australia, Europe and North America were analyzed. 126 of these had suffered from ACS within a period of up to 5 years post urine sampling (cases). Proteomic analysis of 84 cases and 84 matched controls resulted in the discovery of 75 ACS-related urinary peptides. Combining these to a peptide pattern, we established a prognostic biomarker named Acute Coronary Syndrome Predictor 75 (ACSP75). ACSP75 demonstrated reasonable prognostic discrimination (c-statistic = 0.664), which was similar to Framingham risk scoring (c-statistics = 0.644) in a validation cohort of 42 cases and 42 controls. However, generating by a composite algorithm named Acute Coronary Syndrome Composite Predictor (ACSCP), combining the biomarker pattern ACSP75 with the previously established urinary proteomic biomarker CAD238 characterizing coronary artery disease as the underlying aetiology, and age as a risk factor, further improved discrimination (c-statistic = 0.751) resulting in an added prognostic value over Framingham risk scoring expressed by an integrated discrimination improvement of 0.273 ± 0.048 (P < 0.0001) and net reclassification improvement of 0.405 ± 0.113 (P = 0.0007). In conclusion, we demonstrate that urinary peptide biomarkers have the potential to predict future ACS events in asymptomatic patients. Further large scale studies are warranted to determine the role of urinary biomarkers in clinical practice