Optimized diagnostics for kidney transplants
Due to demographic change physicians expect an increasing number of serious kidney diseases. The result is an increasing demand for kidney transplants (NTx), which is offset by a decreasing number of available donor organs. Given this bottleneck, it is necessary to avoid transplant rejection. Improved early detection of rejection reactions can help. The right countermeasures can help prevent early transplant loss.
A diagnostic tool of this kind is being developed as part of the „Screen Reject: A Lateral Flow Test for Rejection Diagnostics“. Hanover University of Applied Sciences (HsH), Institute for Technical Chemistry of Leibniz University of Hannover (LUH), which manages the project network, and the Institute for Transfusion Medicine of Hannover Medical School (MHH) are participating in the collaborative project. All participants are working on a method for early detection of graft rejection in NTx patients. In the subproject „Screen Reject: Data Warehouse for Kidney Transplantation Diagnostics“, the HsH researchers are developing a clinical data warehouse (CDWH) based on a database optimized for analytical purposes. This database is intended to help preparing the information obtained during development of diagnostic agent and to provide to accompanying research and the development of an expert system for rejection diagnostics. The main objective is to protect patients from transplant loss due to organ rejection.
Approach
The data warehouse developed for rejection diagnostics will combine routine clinical data from NTx patients with research data from the joint project on the basis of innovative concepts based on OpenEHR archetypes to establish semantic interoperability. Based on this data, the SR-DWH provides methods and tools for hypothesis-based and hypothesis-generating data analysis. The database and analysis functionality forms the starting point for the development of an innovative expert system to support rejection diagnostics and the display of diagnostic measures according to NTx. The system processes the relevant clinical routine data of an NTx patient, visualises it as a synopsis and evaluates it according to a scoring system.
