Diagnostic and prognostic value of QRS duration and QTc interval in patients with suspected myocardial infarction

Background: While prolongation of QRS duration and QTc interval during acute myocardial infarction (AMI) has been reported in animals, limited data is available for these readily available electrocardiography (ECG) markers in humans. Methods: Diagnostic and prognostic value of QRS duration and QTc interval in patients with suspected AMI in a prospective diagnostic multicentre study were prospectively assessed. Digital 12-lead ECGs were recorded at presentation. QRS duration and QTc interval were automatically calculated in a blinded fashion. Final diagnosis was adjudicated by two independent cardiologists. The prognostic endpoint was all-cause mortality during 24 months of follow-up. Results: Among 4042 patients, AMI was the final diagnosis in 19% of patients. Median QRS duration and median QTc interval were significantly greater in patients with AMI compared to those with other final diagnoses (98 ms [IQR 88–108] vs. 94 ms [IQR 86–102] and 436 ms [IQR 414–462] vs. 425 ms [IQR 407–445], p < 0.001 for both comparisons). The diagnostic value of both ECG signatures however was only modest (AUC 0.56 and 0.60). Cumulative mortality rates after 2 years were 15.9% vs. 5.6% in patients with a QRS > 120 ms compared to a QRS duration ≤ 120 ms (p < 0.001), and 11.4% vs. 4.3% in patients with a QTc > 440 ms compared to a QRS duration ≤ 440 ms (p < 0.001). After adjustment for age and important ECG and clinical parameters, the QTc interval but not QRS duration remained an independent predictor of mortality. Conclusions: Prolongation of QRS duration > 120 ms and QTc interval > 440 ms predict mortality in patients with suspected AMI, but do not add diagnostic value

Combining high sensitivity cardiac troponin I and cardiac troponin T in the early diagnosis of acute myocardial infarction

-Combining two signals of cardiomyocyte injury, cardiac troponin I (cTnI) and T (cTnT), might overcome some individual pathophysiological and analytical limitations and thereby increase diagnostic accuracy for acute myocardial infarction (AMI) with a single blood draw. We aimed to evaluate the diagnostic performance of combinations of high sensitivity (hs) cTnI and hs-cTnT for the early diagnosis of AMI. -The diagnostic performance of combining hs-cTnI (Architect, Abbott) and hs-cTnT (Elecsys, Roche) concentrations (sum, product, ratio and a combination algorithm) obtained at the time of presentation was evaluated in a large multicenter diagnostic study of patients with suspected AMI. The optimal rule out and rule in thresholds were externally validated in a second large multicenter diagnostic study. The proportion of patients eligible for early rule out was compared with the ESC 0/1 and 0/3 hour algorithms. -Combining hs-cTnI and hs-cTnT concentrations did not consistently increase overall diagnostic accuracy as compared with the individual isoforms. However, the combination improved the proportion of patients meeting criteria for very early rule-out. With the ESC 2015 guideline recommended algorithms and cut-offs, the proportion meeting rule out criteria after the baseline blood sampling was limited (6-24%) and assay dependent. Application of optimized cut-off values using the sum (9 ng/L) and product (18 ng2/L2) of hs-cTnI and hs-cTnT concentrations led to an increase in the proportion ruled-out after a single blood draw to 34-41% in the original (sum: negative predictive value (NPV) 100% (95%CI: 99.5-100%); product: NPV 100% (95%CI: 99.5-100%) and in the validation cohort (sum: NPV 99.6% (95%CI: 99.0-99.9%); product: NPV 99.4% (95%CI: 98.8-99.8%). The use of a combination algorithm (hs-cTn

New Interest Associations in a Neo-Corporatist System: Adapting the Swiss Training System to the Service Economy

Collective skill formation systems need to adapt to economic change, most notably the expansion of the service economy. However, deeply anchored in the craft and industrial sectors, these systems rely on neo‐corporatist institutions to undergird firms’ training provision, which are often missing in the service sector. We show that Switzerland's voluntaristic approach to interest intermediation provided the flexibility needed to extend vocational training to economic sectors without neo‐corporatist institutions. Yet, these adaptations resulted in the emergence of interest associations characterised by low levels of generalisability and governability. These new associations co‐exist with neo‐corporatist ones, rendering the overall training system surprisingly heterogeneous

Die vielen Motoren der Berufsbildung

Die Organisationen der Arbeitswelt sind für die Berufsbildung unverzichtbar – sie sind die Motoren der Berufsbildung. Das vom SBFI unterstützte Leading House GOVPET: Governance in Vocational and Professional Education and Training hat nun erstmals umfassende Daten über die OdA erhoben und ausgewertet. Sie zeigt, dass sich seit der Berufsbildungsreform von 2002 die Anzahl spezialisierter Berufsbildungsorganisationen stark erhöht hat. Diese vereinen oftmals heterogene Mitglieder oder Träger und unterschieden sich in vielen Aspekten von traditionellen Unternehmensverbänden, Berufsverbänden und Arbeitnehmerverbänden

Bring! steckt an

Was ist Viralität und welche Formen davon gibt es? Hat Viralität nur mit Marketing zu tun oder gibt es gar einen Bezug zur User Experience von Produkten? Im Rahmen der Masterarbeit für das Studium Human Computer Interaction Design an der HSR und der Uni Basel wurde das Thema Viralität in Mobile Apps am Produkt Bring! untersucht. Bring! ist eine iPhone und Android App für Personen, die einen gemeinsamen Haushalt führen und möglichst einfach die Lebensmittel- und Haushaltseinkäufe organisieren möchten. Es sollen Wege aufgezeigt werden, wie das Produkt weiter verbessert und ein Nährboden für Viralität geschaffen werden kann. Literaturrecherchen und Interviews mit Experten lieferten wichtige Erkenntnisse dazu. Das Ergebnis dieser Recherche ist im Virality Paper im Anhang dokumentiert. Viralität hat nicht nur mit Marketing zu tun, viel wichtiger ist die Viralität im Kern des Produkts. Das Konzept muss den gesamten Viralitäts-Kreislauf beinhalten. Dieser beginnt mit dem ersten Kontakt eines potentiellen Anwenders mit dem Produkt und erstreckt sich bis zu dessen «Verwandlung» in einen engagierten Benutzer, der voller Begeisterung von sich aus neue Benutzer in seinem Umfeld anwirbt. Mit den gewonnen Erkenntnissen wurden über 100 Ideen entwickelt, um den Nährboden für Viralität in Bring! zu optimieren. Die Idee, unterschiedlichen Personengruppen mehrere Einkaufslisten zur Verfügung zu stellen, birgt das grösste Potential für virales Wachstum, da nun jeder bestehende Bring!-Benutzer neue Anwender zur gemeinsamen Verwendung akquirieren kann. Mit Benutzerzentriertem-Design-Vorgehen wird ein Bedarf für dieses Feature nachgewiesen. Mittels Prototyping und Benutzertests wird die Usability validiert und stellt somit die Basis der Akzeptanz und Nutzung sicher. Die Autoren sind überzeugt, dass so die Viralität und somit die Nutzerzahl von Bring! erheblich gesteigert werden kann

A Groundwater and Runoff Formulation for Weather and Climate Models

Soil moisture modifies the state of the atmosphere and thus plays a major role in the climate system. Its spatial distribution is strongly modulated by the underlying orography. Yet the vertical transport of soil water and especially the generation of groundwater runoff at the bottom of the soil column are currently treated in a crude way in most atmospheric and climate models. This potentially leads to large biases in near‐surface temperatures during midlatitude summertime conditions, when the soils may dry out. Here we present a new formulation for groundwater and runoff formation. It is based on Richards equation, allows for saturated aquifers, includes a slope‐dependent groundwater discharge, and enables a subgrid‐scale treatment of the underlying orography. The proposed numerical implementation ensures a physically consistent treatment of the water fluxes in the soil column, using ideas from flux‐corrected transport methodologies. An implementation of this formulation into TERRA_ML, the land surface model of the regional climate model of the COnsortium for Small‐scale MOdeling (COSMO) in CLimate Mode (CCLM), is validated both in idealized and real‐case simulations. Idealized simulations demonstrate the important role of the lower boundary condition at the bottom of the soil column and display a physically meaningful recharge and discharge of the saturated zone. Validation against measurements at selected stations shows an improved seasonal evolution of soil water content. Finally, decade‐long climate simulations over Europe exhibit a realistic representation of the groundwater distribution across continental scales and mountainous areas, an improved annual cycle of surface latent heat fluxes, and as a consequence reductions of long‐standing biases in near‐surface temperatures in semiarid regions.ISSN:1942-246

Coupling the Community Land Model 5.0 with the Parallel Data Assimilation Framework

Land surface models are important tools to improve our understanding of interacting ecosystem processes, but their predictions are associated with uncertainties related to model forcings, parameters and process simplifications. As high-quality observations become more and more available, they can be used to constrain the uncertainty of land surface model predictions. In this study, we use data assimilation for the fusion of data into the Community Land Model 5.0 (CLM5). CLM5 simulates a broad variety of important land surface processes including moisture and energy partitioning, surface runoff, subsurface runoff, photosynthesis and carbon and nitrogen storage in vegetation and soil. Here, we focus on water movement in soils and related soil hydraulic parameters and assimilate in-situ soil moisture data into CLM5 to improve the estimate of model states and soil hydraulic parameters. To do this, we have coupled the Parallel Data Assimilation Framework (PDAF) with CLM5. This coupling is based on the online variant of PDAF, i.e., data assimilation occurs during simulation runtime in the main memory and not via input/output files. Online coupling requires modification of the model source code, but we aim to keep the modifications to the CLM5 code minimal so that maintenance of the ongoing CLM5 developments remains straightforward. To this end, our approach reuses the existing CLM5 ensemble mode with only necessary adjustments to connect the PDAF parallel communicators. Furthermore, we developed the coupling in the framework of the Terrestrial System Modeling Platform (TSMP). TSMP is a highly modular modeling system for the fully integrated soil-vegetation-atmosphere system. To illustrate the potential of this coupling, we use the ensemble Kalman Filter to perform simultaneous state and parameter updates in a forest headwater catchment.</p

Data assimilation aided land surface simulations for the future risk of droughts and fires in European forests

Land surface models are important tools to improve our understanding of interacting ecosystem processes and for the prediction of future risk ofdroughts and fires, but their predictions are associated with uncertainties related to model forcings, parameters and process simplifications. Theincreasing availability of high-quality observations can be used to improve the accuracy of land surface model predictions. In this study, we use the EnsembleKalman Filter for the fusion of in-situ observations into the Community Land Model 5.0 (CLM5). CLM5 simulates a broad variety of important land surfaceprocesses including water and energy partitioning, surface runoff, subsurface runoff, photosynthesis and carbon and nitrogen storage in vegetation and soil.Here, we focus on simulation of soil water content dynamics and related soil hydraulic parameters. We use CLM5 coupled to the Parallel Data AssimilationFramework (PDAF) to assimilate soil moisture data into CLM5 during simulation runtime. We perform simultaneous state and parameter updates to improvethe estimate of model states and parameters. In this study, we specifically focus on European forested study sites where both in-situ soil moisture andevapotranspiration observations are available for the period from 2009 to 2019. We demonstrate the value and limitation of assimilating soil moisturedata for assessing drought stress using eddy covariance data from multiple sites of different observation networks across Europe (e.g. eLTER, FLUXNET,TERENO, ICOS) covering different regional climates and forest types and focusing on recent drought events in 2018 and 2019

Coupling the Community Land Model version 5.0 to the parallel data assimilation framework PDAF: Description and applications

Abstract. Land surface models are important for improving our understanding of the earth system. They are continuously improving and becoming more accurate in describing the varied surface processes, e.g. the Community Land Model version 5 (CLM5). Similarly, observational networks and remote sensing operations are increasingly providing more and higher quality data. For the optimal combination of land surface models and observation data, data assimilation techniques have been developed in the past decades that incorporate observations to update modeled states and parameters. The Parallel Data Assimilation Framework (PDAF) is a software environment that enables ensemble data assimilation and simplifies the implementation of data assimilation systems in numerical models. In this paper, we present the further development of the PDAF to enable its application in combination with CLM5. This novel coupling adapts the optional CLM5 ensemble mode to enable integration of PDAF filter routines while keeping changes to the pre-existing parallel communication infrastructure to a minimum. Soil water content observations from an extensive in-situ measurement network in the Wüstebach catchment in Germany are used to illustrate the application of the coupled CLM5+PDAF system. The results show overall reductions in root mean square error of soil water content from 7 % up to 35 % compared to simulations without data assimilation. We expect the coupled CLM5+PDAF system to provide a basis for improved regional to global land surface modelling by enabling the assimilation of globally available observational data

Coupling the Community Land Model version 5.0 to the parallel data assimilation framework PDAF: description and applications

Land surface models are important for improving our understanding of the Earth system. They are continuously improving and becoming better in representing the different land surface processes, e.g., the Community Land Model version 5 (CLM5). Similarly, observational networks and remote sensing operations are increasingly providing more data, e.g., from new satellite products and new in situ measurement sites, with increasingly higher quality for a range of important variables of the Earth system. For the optimal combination of land surface models and observation data, data assimilation techniques have been developed in recent decades that incorporate observations to update modeled states and parameters. The Parallel Data Assimilation Framework (PDAF) is a software environment that enables ensemble data assimilation and simplifies the implementation of data assimilation systems in numerical models. In this study, we present the development of the new interface between PDAF and CLM5. This newly implemented coupling integrates the PDAF functionality into CLM5 by modifying the CLM5 ensemble mode to keep changes to the pre-existing parallel communication infrastructure to a minimum. Soil water content observations from an extensive in situ measurement network in the Wüstebach catchment in Germany are used to illustrate the application of the coupled CLM5-PDAF system. The results show overall reductions in root mean square error of soil water content from 7 % up to 35 % compared to simulations without data assimilation. We expect the coupled CLM5-PDAF system to provide a basis for improved regional to global land surface modeling by enabling the assimilation of globally available observational data