New solution is point-of-care test (POCT) based on electrochemical immunosensor for simultaneous determination of three significant inflammatory markers in amniotic fluid. This test results in the simultaneous electrochemical detection and quantification of three selected markers in one amniotic fluid sample simultaneously in one analysis. A miniature potentiostat with printed electrode is used for evaluation. The aim of the test is to distinguish between infectious inflammation, when it is necessary to initiate targeted antibiotic treatment, and sterile inflammation, when treatment is indicated to maintain the pregnancy without additional risk for mother and fetus. Clinical relevance of selected markers was determined based on the results of proteomic and antibody studies of amniotic fluid of pregnant women with PPROM.
University Hospital Hradec Králové, University of Pardubice (project Personmed CZ.02.1.01/0.0/0.0/17_048/0007441).
IP Status: czech patent application PV 2021-401 (priority 31. 7. 2021).
Our solution is the determination of the presence of specific bacteria in amniotic fluid collected by amniocentesis using multiplex RT-PCR test allowing the detection of multiple bacteria from amniotic fluid at the same time. The test consists of 3 panels for detection of DNA of selected bacteria, which are the cause of 88% of all intra-amniotic inflammation. Panels contain specific primer sets, and the test results are interpreted by fluorescence method. Test would determine presence of specific bacteria in amniotic fluid within few hours with sensitivity of 90% and thus allows the timely initiation of targeted therapy leading to a reduction of the risk of possible complications for both mother and fetus.
University Hospital Hradec Králové (project Personmed CZ.02.1.01/0.0/0.0/17_048/0007441).
IP Status: know-how
A set of wearable sensors and the first computing unit – assessing the overall gait quality in real time while walking, providing immediate feedback to the user or the physician. Subsequently, the second unit identifies several gait disorders, their extent and probable cause. In both cases, the evaluation is performed using machine learning modules. Both approaches show relatively great robustness of the approach used and the relative simplicity of computer performance, especially in the near future. For general use the first step processing can warn patients or elderly people on the probability of falling.
University Hospital Hradec Králové (project Personmed CZ.02.1.01/0.0/0.0/17_048/0007441).
IP Status: cezch patent application PV 2021-31 (priority 8. 7. 2021).
