Is screening for Factor V Leiden and Prothrombin G20210A Mutations in Renal Transplantation worthwhile? Results of a large single-center U.K. study

This single center study is the largest series of renal transplant recipients and donors screened for the commonest prothrombotic genotypes. A total of 562 transplant recipients and 457 kidney donors were genotyped for the factor V Leiden and prothrombin G20210A mutations. The prevalence of heterozygous factor V Leiden was 3.4% and 2.6% and prothrombin G20210A was 2.0% and 1.1% in recipients and donors, respectively, similar frequencies to that of the general U.K. population. The 30-day and 1-year graft survival rates in recipients with thrombophilic mutations were 93% and 93%, compared with 88% and 82% in patients without these mutations (log-rank P =0.34). Thrombophilia in recipients (odds ratio 0.55; confidence interval 0.06-2.29; P =0.56) or in donors (odds ratio 1.53; confidence interval 0.27-5.74; P =0.46) did not correlate with graft loss at 30 days after transplantation. In contrast to recent reports, this study did not demonstrate an association between thrombophilia and renal allograft loss, and routine screening is not recommended.

Extending BPM Environments of Your Choice with Performance Related Decision Support

What-if Simulations have been identified as one solution for business performance related decision support. Such support is especially useful in cases where it can be automatically generated out of Business Process Management (BPM) Environments from the existing business process models and performance parameters monitored from the executed business process instances. Currently, some of the available BPM Environments offer basic-level performance prediction capabilities. However, these functionalities are normally too limited to be generally useful for performance related decision support at business process level. In this paper, an approach is presented which allows the non-intrusive integration of sophisticated tooling for what-if simulations, analytic performance prediction tools process optimizations or a combination Of Such solutions into already existing BPM environments. The approach abstracts from process modelling techniques which enable automatic decision support spanning processes across numerous BPM Environments. For instance, this enables end-to-end decision support for composite processes modelled with the Business Process Modelling Notation (BPMN) on top of existing Enterprise Resource Planning (ERP) processes modelled with proprietary languages.