“The Rodney Dangerfield of Stylistic Devices”: End-to-End Detection and Extraction of Vossian Antonomasia Using Neural Networks

Vossian Antonomasia (VA) is a well-known stylistic device based on attributing a certain property to a person by relating them to another person who is famous for this property. Although the morphological and semantic characteristics of this phenomenon have long been the subject of linguistic research, little is known about its distribution. In this paper, we describe end-to-end approaches for detecting and extracting VA expressions from large news corpora in order to study VA more broadly. We present two types of approaches: binary sentence classifiers that detect whether or not a sentence contains a VA expression, and sequence tagging of all parts of a VA on the word level, enabling their extraction. All models are based on neural networks and outperform previous approaches, best results are obtained with a fine-tuned BERT model. Furthermore, we study the impact of training data size and class imbalance by adding negative (and possibly noisy) instances to the training data. We also evaluate the models' performance on out-of-corpus and real-world data and analyze the ability of the sequence tagging model to generalize in terms of new entity types and syntactic patterns.Peer Reviewe

Small sample sizes : A big data problem in high-dimensional data analysis

Acknowledgements The authors are grateful to the Editor, Associate Editor and three anonymous referees for their helpful suggestions, which greatly improved the manuscript. Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research is supported by the German Science Foundation awards number DFG KO 4680/3-2 and PA 2409/3-2.Peer reviewedPublisher PD

Nosocomial methicillin resistant Staphylococcus aureus pneumonia - epidemiology and trends based on data of a network of 586 German ICUs (2005-2009)

The epidemiology of MRSA pneumonia varies across countries. One of the most import risk factors for the development of nosocomial MRSA pneumonia is mechanical ventilation. Methicillin resistance in S. aureus ventilator associated pneumonia (VAP) ranged between 37% in German, 54% in the US American and 78% in Asian and Latin American ICUs. In 2009, the incidence density of nosocomial VAP caused by MRSA was 0.28 per 1000 ventilation days in a network of 586 German ICUs. Incidences peaked in neurological and neurosurgical ICUs. Crude hospital mortality in studies performed after 2005 lay between 27% and 59% and attributable MRSA pneumonia mortality at 40%. Since 2005, US American and German data indicate decreasing trends for MRSA pneumonia. Measures to reduce MRSA pneumonia or to control the spread of MRSA include hand hygiene, standard and contact precautions, oral contamination with chlor hexidine, skin decontamination with antiseptics, screening, and (possibly) patient isolation in a single room

“The Rodney Dangerfield of Stylistic Devices”: End-to-End Detection and Extraction of Vossian Antonomasia Using Neural Networks

Vossian Antonomasia (VA) is a well-known stylistic device based on attributing a certain property to a person by relating them to another person who is famous for this property. Although the morphological and semantic characteristics of this phenomenon have long been the subject of linguistic research, little is known about its distribution. In this paper, we describe end-to-end approaches for detecting and extracting VA expressions from large news corpora in order to study VA more broadly. We present two types of approaches: binary sentence classifiers that detect whether or not a sentence contains a VA expression, and sequence tagging of all parts of a VA on the word level, enabling their extraction. All models are based on neural networks and outperform previous approaches, best results are obtained with a fine-tuned BERT model. Furthermore, we study the impact of training data size and class imbalance by adding negative (and possibly noisy) instances to the training data. We also evaluate the models' performance on out-of-corpus and real-world data and analyze the ability of the sequence tagging model to generalize in terms of new entity types and syntactic patterns. Copyright © 2022 Schwab, Jäschke and Fischer

Staphylococcus Aureus Bacteriuria as a Predictor of In-Hospital Mortality in Patients with Staphylococcus Aureus Bacteremia. Results of a Retrospective Cohort Study

Staphylococcus aureus bloodstream infection (SA-BSI) is an infection with increasing morbidity and mortality. Concomitant Staphylococcus aureus bacteriuria (SABU) frequently occurs in patients with SA-BSI. It is considered as either a sign of exacerbation of SA-BSI or a primary source in terms of urosepsis. The clinical implications are still under investigation. In this study, we investigated the role of SABU in patients with SA-BSI and its effect on the patients' mortality. We performed a retrospective cohort study that included all patients in our university hospital (Charité Universitätsmedizin Berlin) between 1 January 2014 and 31 March 2017. We included all patients with positive blood cultures for Staphylococcus aureus who had a urine culture 48 h before or after the first positive blood culture. We identified cases while using the microbiology database and collected additional demographic and clinical parameters, retrospectively, from patient files and charts. We conducted univariate analyses and multivariable Cox regression analysis to evaluate the risk factors for in-hospital mortality. 202 patients met the eligibility criteria. Overall, 55 patients (27.5%) died during their hospital stay. Cox regression showed SABU (OR 2.3), Pitt Bacteremia Score (OR 1.2), as well as moderate to severe liver disease (OR 2.1) to be independent risk factors for in-hospital mortality. Our data indicates that SABU in patients with concurrent SA-BSI is a prognostic marker for in-hospital death. Further studies are needed for evaluating implications for therapeutic optimization

Bist du schlau? Dann guckst du(,) logo! Ein Vergleich der Wissensvermittlung durch die Nachrichtensendungen Tagesschau und logo! und ihrer sprachlichen Gestaltung

Die vorliegende empirische Studie beschäftigt sich mit dem Vergleich der Tagesschau mit den Kindernachrichten von logo! Es wurde vermutet, dass der Wissenserwerb durch logo! höher ausfällt und sich logo! durch ein niedrigeres Sprachniveau auszeichnet, was zu höherem Wissen beitragen könnte. Zur Überprüfung der Annahmen wurde ein Online-Experiment konzipiert, welches das durch beide Sendungen in Form konkreter Beiträge vermittelte Wissen von 260 Versuchspersonen empirisch überprüfte. Die verwendete Sprache wurde mit der Software LIWC analysiert; zudem wurde der Flesch-Index bestimmt. Die Ergebnisse zeigen, dass logo! zu einem höheren Wissen führt, allerdings nicht für alle Beiträge gleichermassen, und teils ein niedrigeres Sprachniveau aufweist (geringere Wortkomplexität und kürzere Sätze sowie höherer Flesch-Index). Das höhere Wissen in der logo!-Bedingung könnte dabei teils durch die eingesetzte Sprache erklärbar sein, obwohl die Befunde nicht eindeutig sind. Schliesslich zeigte sich, dass der logo!-Vorteil bei Personen mit Hochschulabschluss grösser war als bei anderen Personen, was vor dem Hintergrund der Wissenskluft-Hypothese verständlich wird. Aus unseren Befunden lassen sich Praxisempfehlungen u. a. zur sprachlichen Gestaltung von TV-Nachrichten ableiten, um den Wissenserwerb zu verbessern. The present empirical study deals with the comparison of the Tagesschau with the children’s news from logo! It was assumed that the acquisition of knowledge by logo! is higher and that logo! is characterized by a lower language level, which could contribute to higher knowledge. To test the assumptions, an online experiment was designed which empirically tested the knowledge conveyed by both programs in the form of concrete contributions from 260 study participants. The language used was analyzed with the LIWC software; the Flesch-Index was also determined. The results show that logo! leads to a higher level of knowledge, although not equally for all contributions, and in some cases has a lower language level (lower word complexity and shorter sentences as well as a higher Flesch-Index). The higher knowledge in the logo! condition could thereby be partly explained by the language used, although the findings are not entirely clear. Finally, the logo! advantage was found to be greater for individuals with a university degree than for others, which becomes understandable in light of the knowledge gap hypothesis. From our findings, practical recommendations can be derived, among other things, for the linguistic design of TV news in order to improve knowledge acquisition

Sprachniveau in Online- und TV-Nachrichten: Eine quantitative computergestützte Textanalyse der Online- und TV-Berichterstattung von ARD, ZDF, Sat.1 und RTL

Nachrichten stellen ein beliebtes Forschungsfeld der Kommunikationsforschung dar. In der entsprechenden deutschsprachigen Forschung werden vielfach die Hauptnachrichten der beiden deutschen Rundfunksysteme (öffentlich-rechtlich vs. privat) miteinander verglichen – zuletzt z. B. hinsichtlich ihres Sprachniveaus. Allerdings existiert wenig Forschung, die sich dem Online-Nachrichtenangebot widmet. Daher lag unser Ziel in der Analyse des Sprachniveaus von deutschen Online-Nachrichtenangeboten beider Systeme sowie einzelner Sender (ARD, ZDF, RTL SAT.1) mit Hilfe von vier Kategorien des Textanalyseprogramms Linguistic Inquiry and Word Count sowie von zwei weiteren Massen (Umgangssprache, Flesch-Index), die unterschiedliche Dimensionen des Sprachniveaus erfassen. In Form einer künstlichen Nachrichtenwoche wurden insgesamt 84 Online-Nachrichtentexte hinsichtlich ihres Sprachniveaus analysiert. Online-Nachrichten der Privatsender wiesen durchschnittlich längere Texte und mehr Wörter pro Satz auf. Ein Unterschied hinsichtlich Wortschatzdiversität und Wortkomplexität konnte nicht gefunden werden. Die Ergebnisse zum Flesch-Index zeigen, dass Online-Nachrichten beider Systeme ähnlich schwer verständlich sind. Diese Ergebnisse wurden aktuellen Daten zum Sprachniveau klassischer TV-Nachrichten gegenübergestellt. Dabei wurde evident, dass Online-Nachrichten höhere Werte bei einigen Markern des Sprachniveaus aufwiesen, was u. a. mit Hilfe des Kontinuums Mündlichkeit-Schriftlichkeit kontextualisierbar ist, und dass sich das Sprachniveau in Online-Nachrichten zwischen den Systemen und Sendern, im Unterschied zu TV-Nachrichten, eher ähnelte, was im ersten Fall als Konvergenz, im zweiten als Konkurrenz interpretiert werden kann

ICU mortality following ICU-acquired primary bloodstream infections according to the type of pathogen: A prospective cohort study in 937 Germany ICUs (2006-2015)

Objective: Mortality due to intensive care unit (ICU) acquired primary blood stream infections (PBSI) is related primarily to patient co-morbidities, types of pathogens and quality of care. The objective of this study is to determine the impact of various types of pathogen on ICU mortality. Methods: Data from the German National Nosocomial Infection Surveillance System of patients with PBSI from 2006 to 2015 was used for this analysis. A BSI is primary when the pathogen recognized is not related to an infection on another site. Only mono-microbial infections stratified into the 13 pathogens most frequently causing PBSI were considered. Univariate and multivariate risk factor analyses were performed using the following risk factors: Sex, age, length of stay, device use, time until onset of PBSI, type and size of hospital, type of ICU and type of pathogen. ICU mortality following S. aureus PBSI was used as the reference value. Results: A total of 4,556,360 patients with 16,978,882 patient days from 937 ICUs were considered in the analysis. Of 14,626 PBSI in total, 12,745 mono-microbial PBSI were included. The ICU mortality was 18.6%. Compared with S. aureus and adjusted by age, sex and type of ICU, S. maltophlfia was associated with significantly higher ICU mortality (OR 1.71; 95% CI 1.19-2.47) as followed by Enterococci (OR 1.20; 95% CI 1.06-1.36), Ecoli (OR 1.24; 95% CI 1.02-1.49), C. albicans (OR 1.37; 95% CI 1.16-1.61), non albicans Candida spp. (OR 1.49; 95% CI 1.18-1.88) and P. aeruginosa (OR 1.49; 95% CI 1.21-1.84). Coagulase negative Staphylococci were associated with significant lower ICU mortality (OR 0.86; 95% Cl 0.75-0.99). Conclusion: Because of the limitation of the study in adjusting for severity of illness and appropriateness of therapy, the differences between the pathogens may not only be explained by differences in virulence, but may reflect the prognosis after receiving the microbiological results and may therefore be useful for intensive care physicians

No increase of device associated infections in German intensive care units during the start of the COVID-19 pandemic in 2020

Background: The COVID-19 pandemic may have had a substantial impact on the incidence of device-associated healthcare-associated infections (HAI), in particular in intensive care units (ICU). A significant increase of HAI was reported by US hospitals when comparing incidence rates from 2019 and 2020. The objective of this study was to investigate the development of the most relevant device-associated HAI in German ICUs during the year 2020 as compared to 2019. Methods: We utilized the data of the ICU component of the German National Reference Center for Surveillance of Nosocomial Infections (KISS = Krankenhaus-Infektions-Surveillance-System) for the period 2019-2020. We focused on central line-associated bloodstream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), ventilator-associated lower respiratory infections (VALRTI) and bloodstream infections associated with the use of Extracorporeal-Life-Support-Systems (ECLSABSI). Device use was defined as the number device days per 100 patient days; device-associated infection rates as the number of device-associated infections per 1000 device days. To compare the pooled means between the years and quarters we calculated rate ratios of device-associated infection rates with 95% confidence intervals by Poisson regression models. Results: The number of participating ICUs in the surveillance system decreased from 982 in 2019 to 921 in 2020 (6.2%). Device utilization rates increased significantly for central lines and ventilator use. VALRTI rates and CAUTI rates decreased in 2020 compared with 2019, however, no increase was shown for CLABSI or ECLSABSI. This result was also confirmed when the corresponding quarters per year were analyzed. Conclusions: The lack of an increase in device-associated healthcare associated infections (HAI) in German ICUs may be due to the lower overall incidence of COVID-19 cases in Germany in 2020 compared with US, to a very high availability of ICU beds per 100,000 inhabitants compared with many other countries, and a change in the ICU patient mix due to numerous elective procedures that were postponed during the first two waves. The primary reason seems to be that only 7% of all ICU patients in Germany in 2020 were COVID-19 patients