Modelling of patient journey in chronic spontaneous urticaria: Increasing awareness and education by shorten patients' disease journey in Germany.

BACKGROUND: Chronic spontaneous urticaria (CSU) is both physically and emotionally stressful, and guideline recommendations are often not optimally implemented in clinical practice. The objective of this study was to provide an overview on the patient journey in CSU and to develop a mathematical model based on solid data. METHODS: The journey of CSU patients in Germany was traced through literature review and expert meetings that included medical experts, pharmacists and representatives of patient organizations. The current situation's main challenges in the patient journey (education, collaboration and disease management) were discussed in depth. Then, a probabilistic model was developed in a co-creation approach to simulate the impact of three potential improvement strategies: (1) patient education campaign, (2) medical professional education programme and (3) implementation of a disease management programme (DMP). RESULTS: Chronic spontaneous urticaria patients are severely burdened by delays in diagnosis and optimal medical care. Our simulation indicates that in Germany, it takes on average of 3.8 years for patients to achieve disease control in Germany. Modelling all three optimization strategies resulted in a reduction to 2.5 years until CSU symptom control. On a population level, the proportion of CSU patients with disease control increased from 44.2% to 58.1%. CONCLUSION: In principle, effective CSU medications and a disease-specific guideline are available. However, implementation of recommendations is lagging in practice. The approach of quantitative modelling of the patient journey validates obstacles and shows a clear effect of multiple interventions on the patient journey. The data generated by our simulation can be used to identify strategies for improving patient care. Our approach might helping in understanding and improving the management of patients beyond CSU.

[Digitized healthcare in 2030-a possible scenario]. / Digitalisierte Gesundheitsversorgung im Jahr 2030 ­ ein mögliches Szenario.

Due to the rapidly advancing digitalization, healthcare will also change significantly in the next few years. For example, in Germany, new legal framework conditions have already set the course for the electronic patient record (ePA), the e­prescription, and the integration of digital health applications (DiGA). The new fast-track procedure of the Federal Institute for Drugs and Medical Devices (BfArM) for evaluating the reimbursability of DiGA is an important step that will be followed by others in the coming years.This article uses a future scenario for the year 2030 to describe the legal, technical, and practical changes that could occur by then. In 2030, healthcare could be organized in individual and integrated treatment pathways that offer comprehensive support to the insured. Interoperable digital components could, for example, make structured data available for research purposes. Doubts concerning data protection could become a thing of the past if data protection law is reformed and harmonized and new consent procedures for patients are developed. New professional fields could become established and market access for innovative digital medical products could be further improved.Another important aspect that can help to exploit the potential of digital healthcare is the creation of a European data space based on a technical infrastructure that upholds high ethical and social standards. Active measures on the part of legislators can create the necessary conditions for innovations to be incorporated into the system for the benefit of patients and for the German healthcare system to be able to cope with the ongoing changes in medical technology.

Potentiation of ceftazidime by avibactam against ß-lactam-resistant Pseudomonas aeruginosa in an in vitro infection model.

Objectives: This study evaluated the in vitro pharmacodynamics of combinations of ceftazidime and the non-ß-lactam ß-lactamase inhibitor, avibactam, against ceftazidime-, piperacillin/tazobactam- and meropenem-multiresistant Pseudomonas aeruginosa by a quantitative time-kill method. Methods: MICs of ceftazidime plus 0-16 mg/L avibactam were determined against eight isolates of P. aeruginosa . Single-compartment, 24 h time-kill kinetics were investigated for three isolates at 0-16 mg/L avibactam with ceftazidime at 0.25-4-fold the MIC as measured at the respective avibactam concentration. Ceftazidime and avibactam concentrations were measured by LC-MS/MS during the time-kill kinetic studies to evaluate drug degradation. Results: Avibactam alone displayed no antimicrobial activity. MICs of ceftazidime decreased by 8-16-fold in the presence of avibactam at 4 mg/L. The changes in log 10 cfu/mL at both the 10 h and 24 h timepoints (versus 0 h) revealed bacterial killing at ≥1-fold MIC. Significantly higher concentrations of ceftazidime alone, as compared with those of ceftazidime in combination, were required to produce any given kill. Without avibactam, ceftazidime degradation was significant (defined as degradation t 1/2 < 24 h), with as little as 19% ± 18% of the original concentration remaining at 8 h for the most resistant strain. In combination with avibactam, ceftazidime degradation at ≥ 1-fold MIC was negligible. Conclusion: The addition of avibactam protected ceftazidime from degradation in a dose-dependent manner and restored its cidal and static activity at concentrations in combination well below the MIC of ceftazidime alone.

Unravelling a new mechanism linking actin polymerization and gene transcription.

In the recent years, the role of actin and actin-binding proteins in gene transcription has received considerable attention. Nuclear monomeric and polymerized actin and several actin binding proteins have been detected in the mammalian cell nucleus, although their roles in transcription are just beginning to emerge. Our group recently reported that the actin-binding protein Filamin A interacts with the transcriptional coactivator MKL1 to link actin polymerization with transcriptional activity of Serum Response Factor. Here we summarize the regulation and function of MKL1, and highlight this novel mechanism of MKL1 regulation through binding to Filamin A and its implications for cell migration.

Filamin A interacts with the coactivator MKL1 to promote the activity of the transcription factor SRF and cell migration.

Megakaryoblastic leukemia 1 (MKL1) is a coactivator of serum response factor (SRF) that promotes the expression of genes associated with cell proliferation, motility, adhesion, and differentiation-processes that also involve dynamic cytoskeletal changes in the cell. MKL1 is inactive when bound to monomeric globular actin (G-actin), but signals that activate the small guanosine triphosphatase RhoA cause actin polymerization and MKL1 dissociation from G-actin. We found a new mechanism of MKL1 activation that is mediated through its binding to filamin A (FLNA), a protein that binds filamentous actin (F-actin). The interaction of FLNA and MKL1 was required for the expression of MKL1 target genes in primary fibroblasts, melanoma, mammary and hepatocellular carcinoma cells. We identified the regions of interaction between MKL1 and FLNA, and cells expressing an MKL1 mutant that was unable to bind FLNA exhibited impaired cell migration and reduced expression of MKL1-SRF target genes. Induction and repression of MKL1-SRF target genes correlated with increased or decreased MKL1-FLNA interaction, respectively. Lysophosphatidic acid-induced RhoA activation in primary human fibroblasts promoted the association of endogenous MKL1 with FLNA, whereas exposure to an actin polymerization inhibitor dissociated MKL1 from FLNA and decreased MKL1-SRF target gene expression in melanoma cells. Thus, FLNA functions as a positive cellular transducer linking actin polymerization to MKL1-SRF activity, counteracting the known repressive complex of MKL1 and monomeric G-actin.