Search

Aims Worldwide applications of extracorporeal circulation for mechanical support in cardiac and circulatory failure, which are referred to as extracorporeal life support (ECLS) or veno‐arterial extracorporeal membrane oxygenation (va‐ECMO), have dramatically increased over the past decade. In spite of the expanding use and the immense medical as well as socio‐economic impact of this therapeutic approach, there has been a lack of interdisciplinary recommendations considering the best available evidence for ECLS treatment. Methods and Results In a multiprofessional, interdisciplinary scientific effort of all scientific societies involved in the treatment of patients with acute cardiac and circulatory failure, the first evidence‐ and expert consensus‐based guideline (level S3) on ECLS/ECMO therapy was developed in a structured approach under regulations of the AWMF (Association of the Scientific Medical Societies in Germany) and under use of GRADE (Grading of Recommendations Assessment, Development and Evaluation) criteria. This article presents all recommendations created by the expert panel, addressing a multitude of aspects for ECLS initiation, continuation, weaning and aftercare as well as structural and personnel requirements. Conclusions This first evidence‐ and expert consensus‐based guideline (level S3) on ECLS/ECMO therapy should be used to apply the best available care nationwide. Beyond clinical practice advice, remaining important research aspects for future scientific efforts are formulated.

Background: Deep learning (DL)-based head and neck lymph node level (HN_LNL) autodelineation is of high relevance to radiotherapy research and clinical treatment planning but still underinvestigated in academic literature. Methods: An expert-delineated cohort of 35 planning CTs was used for training of an nnU-net 3D-fullres/2D-ensemble model for autosegmentation of 20 different HN_LNL. A second cohort acquired at the same institution later in time served as the test set (n=20). In a completely blinded evaluation, 3 clinical experts rated the quality of DL autosegmentations in a head-to-head comparison with expert-created contours. For a subgroup of 10 cases, intraobserver variability was compared to the average DL autosegmentation accuracy on the original and recontoured set of expert segmentations. A postprocessing step to adjust craniocaudal boundaries of level autosegmentations to the CT slice plane was introduced and the effect on geometric accuracy and expert rating was investigated. Results: Blinded expert ratings for DL segmentations and expert-created contours were not significantly different. DL segmentations with slice plane adjustment were rated numerically higher (mean, 81.0 vs. 79.6,p=0.185) and DL segmentations without slice plane adjustment were rated numerically lower (77.2 vs. 79.6,p=0.167) than manually drawn contours. DL segmentations with CT slice plane adjustment were rated significantly better than DL contours without slice plane adjustment (81.0 vs. 77.2,p=0.004). Geometric accuracy of DL segmentations was not different from intraobserver variability (mean, 0.76 vs. 0.77, p=0.307). Conclusions: We show that a nnU-net 3D-fullres/2D-ensemble model can be used for highly accurate autodelineation of HN_LNL using only a limited training dataset that is ideally suited for large-scale standardized autodelineation of HN_LNL in the research setting., 14 pages, 6 figures, published in Frontiers in Oncology

Testing is important in software development, but it has high cost. Thus, techniques to reduce the cost of software testing have been proposed. Model-based testing, one of such techniques, focuses on automatizing the generation of test cases. In the context of highly configurable systems, model-based testing must capture the system behavior and also encode the variability that exists among the variants. Previous research has shown promising results in applying model-based testing to configurable systems. Test models that encode variability into them directly improve the reasoning for faults from interactions. However, there is no study about the use of different variability mechanisms to encode variability in test models. In this paper, we investigate advantages and drawbacks of test model designs exploring the use of two variability mechanisms, namely preprocessor directives and feature toggles. The results are discussed in regard to run-time reasoning and re-configuration, alongside with metrics about complexity and maintainability. With this work, we contribute to the testing activity of highly configurable systems by providing engineers insights of comparing two well-known and widely used variability mechanisms, which can support informed decisions when choosing for which mechanisms to use for model-based testing. Version of record

Poster presented at the plenary meeting of the NFDI consortium Text+ on September 12, 2022 in Mannheim, Germany., Text+ receives a funding grant from the DFG under the grant agreement number 460033370. Text+ is contributing to the NFDI, the National Research Data Infrastructure (NFDI).

Poster presented at the plenary meeting of the NFDI consortium Text+ on September 12, 2022 in Mannheim, Germany., Text+ receives a funding grant from the DFG under the grant agreement number 460033370. Text+ is contributing to the NFDI, the National Research Data Infrastructure (NFDI).

Fragestellung: Ziel der Arbeit war es, Komplikations- und Revisionsraten sowie das klinische Outcome von geriatrischen prox. Humerusfrakturen (PHF) mit Beteiligung des anatomischen Halses versorgt mittels offener Reposition und winkelstabiler Plattenosteosynthese (ORIF) vs. Implantation einer Schulterprothese [zum vollständigen Text gelangen Sie über die oben angegebene URL]