•RSV is the second most prevalent respiratory virus in adults before the COVID pandemic.•85% of RSV patients had risk factors, with COPD and kidney disease found particularly frequently in RSV ...infections.•RSV infections are more severe compared to influenza, but less severe cmpared to SARS-CoV-2.
The role and impact of RSV in the adult population is not well understood and comparative data of RSV infection, influenza A/B and SARS-CoV-2 in the elderly hospitalized for respiratory infections is limited.
In a retrospective, monocentric study we analyzed data of adult patients with respiratory infections tested positive by PCR for RSV, Influenza A/B and SARS-CoV-2 over a four-year period from 2017 to 2020. Symptoms on admission, laboratory results, and risk factors were assessed, and the clinical course and outcomes were studied.
A total of 1541 patients hospitalized with respiratory disease and PCR positive for one of the 4 viruses were enrolled in the study. RSV was the second most prevalent virus before the COVID-19 pandemic and RSV patients represent the oldest group in this study with an average age of 75 years. Neither clinical nor laboratory characteristics differ clearly between RSV, Influenza A / B and SARS-CoV-2 infections. Up to 85% of patients had risk factors, with COPD and kidney disease found particularly frequently in RSV infections. Hospital stay was 12.66 days for RSV patients and thus significantly longer than for influenza A / B (10.88 and 8.86, respectively, p < 0.001), but shorter than for SARS-CoV-2 (17.87 days, p < 0.001). The risk for ICU admission and the rate of mechanical ventilation were also higher for RSV than for influenza A (OR 1.69 (p = 0.020) and 1.59 (p = 0.050)) and influenza B: (1.98 (p = 0.018) and 2.33 (p < 0.001)), but lower than for SARS-CoV-2 (0.65 (p < 0.001) and 0.59 (p = 0.035)). The risk of hospital mortality for RSV was increased compared with influenza A (1.55 (p = 0.050)) and influenza B (1.42 (p = 0.262)), but lower compared to SARs-CoV-2 (0.37 (p < 0.001).
RSV infections in elderly are frequent and more severe than those with influenza A/B. While the impact of SARS-CoV-2 most likely decreased in the elderly population due to vaccination, RSV can be expected to continue to be problematic for elderly patients, especially those with comorbidities and thus, more awareness on the disastrous impact of RSV in this age group is urgently needed.
Clustering algorithms are usually iterative procedures. In particular, when the clustering algorithm aims to optimise an objective function like in k-means clustering or Gaussian mixture models, ...iterative heuristics are required due to the high non-linearity of the objective function. This implies higher computational costs and the risk of finding only a local optimum and not the global optimum of the objective function. In this paper, we demonstrate that in the case of one-dimensional clustering with one main and one noise cluster, one can formulate an objective function, which permits a closed-form solution with no need for an iteration scheme and the guarantee of finding the global optimum. We demonstrate how such an algorithm can be applied in the context of laboratory medicine as a method to estimate reference intervals that represent the range of “normal” values.
Fuzzy clustering, as a powerful method for pattern recognition and data analysis, often produces complex results that require careful examination of individual clusters. In this paper, advanced ...visualization techniques are presented that aim to facilitate the analysis of fuzzy clustering results by focusing on the evaluation and interpretation of individual clusters. The presented approach is based on the development of cluster-centric visualization techniques that consider the inherent uncertainty of fuzzy clustering results. The novelty is an assessment of individual clusters with the proposed visualizations. In general, three cluster-centered visualization techniques are presented. These approaches are intended not only to illustrate the overall structure of the fuzzy clustering results but also to enable detailed individual cluster analysis. The performance of the presented visualization techniques is demonstrated by their application to real data sets from different areas. The results show that the techniques provide an effective way to judge individual clusters in fuzzy clustering results for complex data structures.
Population parameters are usually determined from mark-recapture experiments requiring laborious field work. Here, we present a model-based approach that can be applied for the determination of avian ...population parameters such as average individual life expectancy, average age in the population, and generation length from age-differentiated bird counts. Moreover, the method presented can also create age-specific results from lifetime averages using a deterministic exponential function for the calculation of parameters of interest such as age-dependent mortality and age distribution in the population. The major prerequisites for application of this method are that young and adult birds are easily distinguishable in the field as well as the existence of sufficiently large data sets for error minimization. Large data sets are nowadays often available through the existence of so-called "citizen science" databases. Examples for the determination of population parameters are given for long-living migratory birds which travel as families in large groups such as the Common Crane and the Whooper Swan. Other examples include long-living partially migratory birds staying together in large flocks which do not travel as families such as the Black-headed Gull, and also short-living songbirds where at least from one sex young and adult birds are easily differentiable such as the male Black Redstart.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Large spontaneous leakages in district heating networks (DHNs) require a separation of the affected network part, as interruption of the heat supply is imminent. Measurement data of 22 real events ...was analyzed for localization, but suitable results were not always achieved. In this paper, the reasons are investigated and a model for data evaluation (MoFoDatEv) is developed for further insights. This contains prior knowledge and a simplified physical model for the reaction of the DHN in the case of a large spontaneous leakage. A model like this does not exist so far. It determines the time point and the duration of the pressure drop of the pressure wave which is caused by such leakages. Both parameters and the evaluation time frame are optimized for each event separately. The quality assessment leads to a categorization of the events based on several parameters, and correlations between the pressure and the refill mass flow are found. A minimum leakage size is deduced for successful evaluation. Furthermore, MoFoDatEv can also be used for leakage localization directly, combining two steps from previous publications. Therefore, more data contribute to the result. The application is conducted with artificial data to prove the model concept, and also with real measurement data.
Cluster analysis is often used to find clusters and algorithms are designed and tuned to find the “right” clusters. Instead of searching for the “best” clustering algorithm, we argue that a clear ...concept of what the aim of a cluster analysis is and a better understanding of the data – especially based on visualisations – can be more crucial than the search for the right algorithm. In this paper, we revisit a method called dynamic data assigning assessment clustering that was intended both to asses the inherent cluster structure in a data set as well as to find the clusters. Here we extend this algorithm for better visualisation of possible cluster structures and also to validate single clusters that were found by other algorithms. Although this new approach can help to identify clusters, it is supporting tool and not used as a clustering algorithm itself.
The initial idea of extending the classical k-means clustering technique to an algorithm that uses membership degrees instead of crisp assignments of data objects to clusters led to the invention of ...a large variety of new fuzzy clustering algorithms. However, most of these algorithms are concerned with cluster shapes or outliers and could have been defined without any problems in the context of crisp assignments of data objects to clusters. In this paper, we demonstrate that the use of membership degrees for these algorithms – although it is not necessary from the theoretical point of view – is essential for these algorithms to function in practice. With crisp assignments of data objects to clusters these algorithms would get stuck most of the time in a local minimum of their underlying objective function, leading to undesired clustering results. In other contributions it was shown that the use of membership degrees can avoid this problem of local minima but it also introduces new problems, especially for clusters with varying density and for high-dimensional data, at least if fuzzy clustering is carried out with the simple standard fuzzifier.
Metastases are the major cause of death from cancer. Thus, understanding the regulation of metastatic processes is of utmost importance. Here we show that mice with impaired type I IFN signaling ...(Ifnar1‐/‐) develop more lung metastases in the 4T1 mammary and LLC lung carcinoma model, compared to control mice. In Ifnar1‐/‐ mice, higher metastasis load is accompanied by massive neutrophil accumulation in lungs. Elevated G‐CSF levels in serum and enhanced CXCR2 expression on neutrophils are most likely responsible for this phenomenon. Lung infiltrating neutrophils facilitate an improved pre‐metastatic niche formation, supporting more efficient tumor cell extravasation and proliferation in this organ. This is due to the enhanced expression of pro‐metastatic proteins, like Bv8, MMP9, S100A8 and S100A9. Development of pre‐metastatic niche together with reduced neutrophil cytotoxicity against tumor cells results in enhanced metastatic processes in Ifnar1‐/‐ mice. Overall, our findings describe a novel role for IFN during metastasis development and suggest that new treatment strategies should be considered for prevention of metastasis formation in patients.
What's new?
The mechanisms regulating metastasis formation, whereby cancer cells from primary sites disseminate into target organs to form secondary tumors, remain unclear. Here, the authors show that type I IFNs hamper metastasis formation by inhibiting pre‐metastatic niche development in the lung and augmenting neutrophil cytotoxicity against tumor cells. A general shift of the neutrophil phenotype toward a pro‐metastatic phenotype is observed in absence of type I IFNs. The results confirm and extend the role of the type I IFN system in cancer immune surveillance, and reveal the therapeutic potential of type I IFNs in preventing cancer metastasis after standard surgical therapy.
During the novel coronavirus disease (COVID-19) pandemic it is crucial for hospitals to implement infection prevention strategies to reduce nosocomial transmission to the lowest possible number. This ...is all the more important because molecular tests for identifying SARS-CoV-2 infected patients are uncertain, and the resources available for them are limited. In this view, a monocentric, retrospective study with an interventional character was conducted to investigate the extent to which the introduction of a strict hygiene bundle including a general mask requirement and daily screening for suspicious patients has an impact on the SARS-CoV-2 nosocomial rate in the pandemic environment.
All inpatients from a maximum care hospital in Regensburg (Bavaria) between March 1st and June 10th 2020 were included. Patient with respiratory symptoms were tested for SARS-CoV-2 at admission, patients were managed according to a standard hygiene protocol. At the end of March a strict hygiene bundle was introduced including a general mask obligation and a daily clinical screening of inpatients for respiratory symptoms. Nosocomial infection rate for COVID-19 and the risk for infection transmission estimated by the nosocomial incidence density before and after introduction the hygiene bundle were compared. The infection pressure for the hospital during the entire observational period was characterized by the infection reports in the region in relation to the number of hospitalized COVID-19 patients and the number of infected employees.
In fact, after the introduction of a strict hygiene bundle including a general mouth and nose protection obligation and a daily clinical screening of suspicious patients, a significant reduction of the nosocomial rate from 0.28 to 0.06 (p = 0.026) was observed. Furthermore, the risk of spreading hospital-acquired infections also decreased dramatically from 0.0007 to 0.00018 (p = 0.031; rate ratio after/before 0.25 (95%CI 0.06, 1.07) despite a slow decrease of the hospital COVID 19-prevalence and an increase of infected employees.
The available data underline that a strict hygiene bundle seem to be associated with a decrease of nosocomial SARS-CoV-2 transmission in the pandemic situation.
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