Contemporary outcomes after surgical aortic valve replacement with bioprostheses and allografts: a systematic review and meta-analysis(aEuro)

Many observational studies have reported outcomes after surgical aortic valve replacement (AVR), but there are no recent systematic reviews and meta-analyses including all available bioprostheses and allografts. The objective of this study is to provide a comprehensive and up-to-date overview of the outcomes after AVR with bioprostheses and allografts reported in the last 15 years. We conducted a systematic literature review (PROSPERO register: CRD42015017041) of studies published between 2000–15. Inclusion criteria were observational studies or randomized controlled trials reporting on outcomes of AVR with bioprostheses (stented or stentless) or allografts, with or without coronary artery bypass grafting (CABG) or valve repair procedure, with study population size n ≥ 30 and mean follow-up length ≥5 years. Fifty-four bioprosthesis studies and 14 allograft studies were included, encompassing 55 712 and 3872 patients and 349 840 and 32 419 patient-years, respectively. We pooled early mortality risk and linearized occurrence rates of valve-related events, reintervention and late mortality in a random-effects model. Sensitivity, meta-regression and subgroup analyses were performed to investigate the influence of outliers on the pooled estimates and to explore sources of heterogeneity. Funnel plots were used to investigate publication bias. Pooled early mortality risks for bioprostheses and allografts were 4.99% (95% confidence interval [CI], 4.44–5.62) and 5.03% (95% CI, 3.61–7.01), respectively. The late mortality rate was 5.70%/patient-year (95% CI, 4.99–5.62) for bioprostheses and 1.68%/patient-year (95% CI, 1.23–2.28) for allografts. Pooled reintervention rates for bioprostheses and allografts were 0.75%/patient-year (95% CI, 0.61–0.91) and 1.87%/patient-year (95% CI, 1.52–2.31), respectively. There was substantial heterogeneity in most outcomes. Meta-regression analyses identified covariates that could explain the heterogeneity: implantation period, valve type, patient age, gender, pre-intervention New York Heart Association class III/IV, concomitant CABG, study design and follow-up length. There is possible publication bias in all outcomes. This comprehensive systematic review and meta-analysis provides an overview of the outcomes after AVR with bioprostheses and allografts reported during the last 15 years. The results of this study can support patients and doctors in the prosthetic valve choice and can be used in microsimulation models to predict patient outcomes and estimate the cost-effectiveness of AVR with bioprostheses or allografts compared with current and future heart valve prostheses

Discrete choice experiment versus swing-weighting:A head-to-head comparison of diabetic patient preferences for glucose-monitoring devices

Introduction Limited evidence exists for how patient preference elicitation methods compare directly. This study compares a discrete choice experiment (DCE) and swing-weighting (SW) by eliciting preferences for glucose-monitoring devices in a population of diabetes patients. Methods A sample of Dutch adults with type 1 or 2 diabetes (n = 459) completed an online survey assessing their preferences for glucose-monitoring devices, consisting of both a DCE and a SW exercise. Half the sample completed the DCE first; the other half completed the SW first. For the DCE, the relative importance of the attributes of the devices was determined using a mixed-logit model. For the SW, the relative importance of the attributes was based on ranks and points allocated to the ‘swing’ from the worst to the best level of the attribute. The preference outcomes and self-reported response burden were directly compared between the two methods. Results Participants reported they perceived the DCE to be easier to understand and answer compared to the SW. Both methods revealed that cost and precision of the device were the most important attributes. However, the DCE had a 14.9-fold difference between the most and least important attribute, while the SW had a 1.4-fold difference. The weights derived from the SW were almost evenly distributed between all attributes. Conclusions The DCE was better received by participants, and generated larger weight differences between each attribute level, making it the more informative method in our case study. This method comparison provides further evidence of the degree of method suitability and trustworthiness.</p