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Objectives: The SAVI-TF (Symetis ACURATE neo Valve Implantation Using Transfemoral Access) registry was initiated to study the ACURATE neo transcatheter heart valve in a large patient population treated under real-world conditions.
Background: The self-expanding, supra-annular ACURATE neo prosthesis is a transcatheter heart valve that gained the Conformité Européene mark in 2014, but only limited clinical data are available so far.
Methods: This prospective, multicenter registry enrolled 1,000 patients at 25 European centers who were followed for 1 year post-procedure.
Results: Mean patient age was 81.1 ± 5.2 years; mean logistic European System for Cardiac Operative Risk Evaluation I score, European System for Cardiac Operative Risk Evaluation II score, and Society of Thoracic Surgeons score were 18.1 ± 12.5%, 6.6 ± 7.5%, and 6.0 ± 5.6%, respectively. At 1 year, 8.0% (95% confidence interval [CI]: 6.3% to 9.7%) of patients had died, 2.3% (95% CI: 1.3% to 3.2%) had disabling strokes, and 9.9% (95% CI: 8.1% to 11.8%) had permanent pacemaker implantations. Through 1 year, 5 reinterventions (0.5%; 95% CI: 0.1% to 1.0%) were performed: 3 valve-in-valve and 2 surgical aortic valve replacements. Mean effective orifice area was 1.84 ± 0.43 cm2, mean gradient was 7.3 ± 3.7 mm Hg, and greater than mild paravalvular leakage was observed in 3.6% of patients.
Conclusions: Transfemoral implantation of the ACURATE neo prosthesis resulted in favorable 1-year clinical and echocardiographic outcomes with very low mortality and new pacemaker rates.
Introduction: Langerhans Cell Histiocytosis (LCH) represents a rare benign disorder, previously designated as "Histiocytosis X", "Type II Histiocytosis" or "Langerhans Cell Granulomatosis". Clinical presentation includes osteolysis, ulcerations of skin and soft tissues but also involvement of the CNS is described.Because treatment concepts are not well defined the German Cooperative Group on Radiotherapy for Benign Diseases performed a retrospective analysis.
Methods and material: Eight closely cooperating centres collected patients' data of the past 45 years. As study endpoints disease free survival, recurrent disease, death and therapy related side effects were defined.
Results: A total of 80 patients with histologically proven LCH were irradiated within the past 45 years. According to the LCH classification of Greenberger et al. 37 patients had stage Ia, 21 patients stage Ib, 13 patients stage II and 9 patients stage IIIb and the median age was 29 years. The median Follow up was 54 months (range 9-134 months). A total of 39 patients had a surgical intervention and 23 patients a chemotherapy regimen.Radiation treatment was carried out with a median total dose of 15 Gy (range 3-50.4 Gy). The median single fraction was 2 Gy (range 1.8-3 Gy).Overall, 77% patients achieved a complete remission and 12.5% achieved a partial remission. The long-term control rate reached 80%. Within an actuarial overall 5-year survival of 90% no radiogenic side and late effects ≥EORTC/RTOG II° were observed.
Conclusion: In the present study a large collective of irradiated patients was analysed. Radiotherapy (RT) is a very effective and safe treatment option and even low RT doses show sufficient local control.
We present an architecture for the integration of shallow and deep NLP components which is aimed at flexible combination of different language technologies for a range of practical current and future applications. In particular, we describe the integration of a high-level HPSG parsing system with different high-performance shallow components, ranging from named entity recognition to chunk parsing and shallow clause recognition. The NLP components enrich a representation of natural language text with layers of new XML meta-information using a single shared data structure, called the text chart. We describe details of the integration methods, and show how information extraction and language checking applications for realworld German text benefit from a deep grammatical analysis.
Hybrid robust deep and shallow semantic processing for creativity support in document production
(2004)
The research performed in the DeepThought project (http://www.project-deepthought.net) aims at demonstrating the potential of deep linguistic processing if added to existing shallow methods that ensure robustness. Classical information retrieval is extended by high precision concept indexing and relation detection. We use this approach to demonstrate the feasibility of three ambitious applications, one of which is a tool for creativity support in document production and collective brainstorming. This application is described in detail in this paper. Common to all three applications, and the basis for their development is a platform for integrated linguistic processing. This platform is based on a generic software architecture that combines multiple NLP components and on robust minimal recursive semantics (RMRS) as a uniform representation language.
The research performed in the DeepThought project aims at demonstrating the potential of deep linguistic processing if combined with shallow methods for robustness. Classical information retrieval is extended by high precision concept indexing and relation detection. On the basis of this approach, the feasibility of three ambitious applications will be demonstrated, namely: precise information extraction for business intelligence; email response management for customer relationship management; creativity support for document production and collective brainstorming. Common to these applications, and the basis for their development is the XML-based, RMRS-enabled core architecture framework that will be described in detail in this paper. The framework is not limited to the applications envisaged in the DeepThought project, but can also be employed e.g. to generate and make use of XML standoff annotation of documents and linguistic corpora, and in general for a wide range of NLP-based applications and research purposes.
We present an effort for the development of multilingual named entity grammars in a unification-based finite-state formalism (SProUT). Following an extended version of the MUC7 standard, we have developed Named Entity Recognition grammars for German, Chinese, Japanese, French, Spanish, English, and Czech. The grammars recognize person names, organizations, geographical locations, currency, time and date expressions. Subgrammars and gazetteers are shared as much as possible for the grammars of the different languages. Multilingual corpora from the business domain are used for grammar development and evaluation. The annotation format (named entity and other linguistic information) is described. We present an evaluation tool which provides detailed statistics and diagnostics, allows for partial matching of annotations, and supports user-defined mappings between different annotation and grammar output formats.