Prediction of time to prosthesis implantation as a function of joint anatomy in patients with developmental dysplasia of the hip

BACKGROUND: Developmental dysplasia of the hip (DDH) can lead to pain and premature secondary osteoarthritis at an early stage. Joint-preserving osteotomy is an established solution to this problem. In contrast, a conservative approach would result in pain persistence, ultimately raising the patients question for a possible date of expected prosthesis implantation. The aim of the study was to identify the relationship between the dysplastic hip anatomy and the time of prosthesis implantation in order to enable prognostic predictions in younger patients with symptomatic DDH. MATERIALS AND METHODS: Data from 129 hips who received THA due to secondary DDH osteoarthritis were evaluated. The preoperative hip anatomy was evaluated for AI and LCE angle. Multiple linear regression analyses were then used to correlate the influence of these parameters with the patient's age at the time of surgery. In addition, a graphical relationship was derived by the method of power least squares curve fitting with second-degree polynomials. RESULTS: The mean age for THA was 54.3 ± 11 years. The time of surgery correlated significantly with LCE (0.37) and AI (- 0.3) (p < 0.001). The mean age of patients with LCE angle ≤ 10° was 41.9 ± 14.0 years, for LCE 11-20° 52.7 ± 9.5 years, and for LCE 21-30° 57.0 ± 10.3 years. The following formula could then be determined for the calculation of the potential patient age at the time of THA as a function of LCE angle: age pTHA = 40.2 + 0.8 × LCE angle - 0.01 × (LCE angle)2. CONCLUSION: A significant correlation between the extent of dysplasia and the time of prosthesis implantation was identified. In particular, the LCE and the AI correlated strongly with the time of implantation. The more dysplastic the angles were, the sooner the THA was necessary. Using the calculations presented in this study, the probable age of prosthesis implantation can be prognosticated and included in a counseling session about treatment options for DD

TOWARDS A MATURITY MODEL: BED MANAGEMENT CAPABILITIES IN HOSPITALS

As instrumental healthcare institutions providing high quality patient care, hospitals are currently facing multiple challenges ranging from pressure to reduce costs to a rapidly increasing elderly population. From a process perspective hospitals feature support and management processes, which enable the core process of providing patient care. One of the most crucial process areas – bed management – refers primarily to logistics processes related to the physical beds in hospitals. However, these are closely intertwined with diverse management and support processes (e.g., occupancy management). In order to conceptualize bed management as a process area from a holistic perspective, we develop a capability framework based on a thorough literature review as well as subsequent evaluation of the framework’s relevance, completeness, and practical applicability in two German hospitals. The capability framework includes 30 capabilities grouped into six overarching capability areas. It suggests that efficient and effective bed management is predicated on pooling organizational resources from various organizational units and functional areas. Our work serves as a foundation for the development of a respective maturity model. It enables practitioners to systematically manage capabilities related to bed management and supports them in deriving roadmaps, conducting fit/gap analyses, and prioritizing topics, while accounting for the hospital-specific context

Reality bites:An analysis of corona deniers in Germany over time

The COVID-19 pandemic resulted in unprecedented government interventions in many people's lives. Opposition to these measures was not only based on policy disagreements but for some founded in an outright denial of basic facts surrounding the pandemic, challenging social cohesion. Conspiracy beliefs have been prolific within various protest groups and require attention, as such attitudes have been shown to be associated with lower rule compliance. Several studies have shown that the characteristics linked to holding COVID-19 conspiracy beliefs are complex and manifold; however, those insights usually rest on cross-sectional studies only. We have less knowledge on whether these cross-sectional correlates also reveal which parts of the population have been newly convinced by conspiracy theories or have dropped their support for them as the pandemic evolved. Using a unique panel data set from Germany, this paper explores a wide range of characteristics and compares the insights gained from cross-sectional associations on the one hand and links to the ways in which people change their views on the other hand. The findings show that cross-sectional analyses miss out on nuanced differences between different groups of temporary and more consistent conspiracy supporters. Specifically, this paper identifies major differences in the profiles of people who have been denying COVID-19 consistently compared to those who changed their minds on the question and those who assessed the reality correctly throughout. In doing so, socio-political and perception-based dimensions are differentiated and distinctions between respondents from East and West Germany explored

Visualizing the Local Optical Response of Semiconducting Carbon Nanotubes to DNA-Wrapping

We studied the local optical response of semiconducting single-walled carbon nanotubes to wrapping by DNA segments using high resolution tip-enhanced near-field microscopy. Photoluminescence (PL) near-field images of single nanotubes reveal large DNA-wrapping-induced red shifts of the exciton energy that are two times higher than indicated by spatially averaging confocal microscopy. Near-field PL spectra taken along nanotubes feature two distinct PL bands resulting from DNA-wrapped and unwrapped nanotube segments. The transition between the two energy levels occurs on a length scale smaller than our spatial resolution of about 15 nm

Smart technologies for effective reconfiguration: the FASTER approach

Current and future computing systems increasingly require that their functionality stays flexible after the system is operational, in order to cope with changing user requirements and improvements in system features, i.e. changing protocols and data-coding standards, evolving demands for support of different user applications, and newly emerging applications in communication, computing and consumer electronics. Therefore, extending the functionality and the lifetime of products requires the addition of new functionality to track and satisfy the customers needs and market and technology trends. Many contemporary products along with the software part incorporate hardware accelerators for reasons of performance and power efficiency. While adaptivity of software is straightforward, adaptation of the hardware to changing requirements constitutes a challenging problem requiring delicate solutions. The FASTER (Facilitating Analysis and Synthesis Technologies for Effective Reconfiguration) project aims at introducing a complete methodology to allow designers to easily implement a system specification on a platform which includes a general purpose processor combined with multiple accelerators running on an FPGA, taking as input a high-level description and fully exploiting, both at design time and at run time, the capabilities of partial dynamic reconfiguration. The goal is that for selected application domains, the FASTER toolchain will be able to reduce the design and verification time of complex reconfigurable systems providing additional novel verification features that are not available in existing tool flows

Women in Physics in the United States

Presents an overview of the status of women in physics in the U.S. Under-representation of women; Highlights of the report \u27Women in Physics, 2000\u27; Efforts to increase the number of women in the profession; Issues for women activists

LORETA With Cortical Constraint: Choosing an Adequate Surface Laplacian Operator

Low resolution electromagnetic tomography (LORETA) is a well-known method for the solution of the l2-based minimization problem for EEG/MEG source reconstruction. LORETA with a volume-based source space is widely used and much effort has been invested in the theory and the application of the method in an experimental context. However, it is especially interesting to use anatomical prior knowledge and constrain the LORETA's solution to the cortical surface. This strongly reduces the number of unknowns in the inverse approach. Unlike the Laplace operator in the volume case with a rectangular and regular grid, the mesh is triangulated and highly irregular in the surface case. Thus, it is not trivial to choose or construct a Laplace operator (termed Laplace-Beltrami operator when applied to surfaces) that has the desired properties and takes into account the geometry of the mesh. In this paper, the basic methodology behind cortical LORETA is discussed and the method is applied for source reconstruction of simulated data using different Laplace-Beltrami operators in the smoothing term. The results achieved with the different operators are compared with respect to their accuracy using various measures. Conclusions about the choice of an appropriate operator are deduced from the results

Analytical fuselage structure mass estimation using the PANDORA framework

Air traffic emissions have a significant impact on our environment and on the climate change. Since 2020, multiple research activities have been conducted at the German Aerospace Center (DLR) in the project “Exploration of Electric Aircraft Concepts and Technologies” (EXACT) to analyse the potential of eco-efficient aircraft concepts to reduce emissions. To handle the complexity on aircraft pre-design level, the usage of multidisciplinary design optimization (MDO) workflows and a common aircraft description format are an established procedure at DLR. The framework “Remote Component Environment” (RCE, [1]) is used to build MDO-workflows while the aircraft is described using the “Common Parametric Aircraft Configuration Schema” (CPACS, [2]). Different specific disciplines for aircraft design are part of the EXACT project to assess hybrid-electric aircraft concepts including the estimation of flight performance, loads and structural masses of the aircraft. At the Institute for Structures and Design (BT) the primary fuselage structural mass is estimated for different aircraft concepts using fast analytical methods based on the fuselage geometry, the definition of primary structures like frames and stringers and the application of cut-loads on the fuselage for different loadcases. This capability is implemented in the Python-based modelling and sizing framework called “Parametric Numerical Design and Optimization Routines for Aircraft” (PANDORA, [3]), which is under development since 2016. The PANDORA environment integrates developments like generating finite element (FE) models of aircraft based on CPACS parameters, converting FE models between different solver formats, creating and editing CPACS models and numerical as well as analytical sizing of aircraft models. In addition, more detailed FE models with different discretization approaches can be generated for crash and ditching simulations (EASN 2021 [4]). An overview of the PANDORA framework and some results of the EXACT project are given in this presentation