Model-driven Test Engineering: A Practical Analysis in the AQUA-WS Project

The effective application of test phases has been one of the most relevant, critical and cost phases in the life cycle of software projects in the last years. During the test phase, the test team has to assure the quality of the system and the concordance with the initial requirements of the system. The model driven paradigm is offering suitable results in some areas and the test phase could be one of them. This paper presents how the application of this paradigm can help to improve this aspect in the functional test generation and it analyses the experience in a real project developed under this approach.Ministerio de Ciencia e Innovación TIN2010-20057-C03-02Ministerio de Ciencia e Innovación TIN 2010-12312-EJunta de Andalucía TIC-578

A Framework to Evaluate Software Developer’s Productivity The VALORTIA Project

Currently, there is a lack in companies developing software in relation to assessing their staff’s productivity before executing software projects, with the aim of improving effectiveness and efficiency. QuEF (Quality Evaluation Framework) is a framework that allows defining quality management tasks based on a model. The main purpose of this framework is twofold: improve an entity’s continuous quality, and given a context, decide between a set of entity’s instances on the most appropriate one. Thus, the aim of this paper is to make this framework available to evaluate productivity of professionals along software development and select the most appropriate experts to implement the suggested project. For this goal, Valortia platform, capable of carrying out this task by following the QuEF framework guidelines, is designed. Valortia is a platform to certify users' knowledge on a specific area and centralize all certification management in its model by means of providing protocols and methods for a suitable management, improving efficiency and effectiveness, reducing cost and ensuring continuous quality.Ministerio de Ciencia e Innovación TIN2013-46928-C3-3-

Considerations about quality in model-driven engineering

The final publication is available at Springer via http://dx.doi.org/10.1007/s11219-016-9350-6The virtue of quality is not itself a subject; it depends on a subject. In the software engineering field, quality means good software products that meet customer expectations, constraints, and requirements. Despite the numerous approaches, methods, descriptive models, and tools, that have been developed, a level of consensus has been reached by software practitioners. However, in the model-driven engineering (MDE) field, which has emerged from software engineering paradigms, quality continues to be a great challenge since the subject is not fully defined. The use of models alone is not enough to manage all of the quality issues at the modeling language level. In this work, we present the current state and some relevant considerations regarding quality in MDE, by identifying current categories in quality conception and by highlighting quality issues in real applications of the model-driven initiatives. We identified 16 categories in the definition of quality in MDE. From this identification, by applying an adaptive sampling approach, we discovered the five most influential authors for the works that propose definitions of quality. These include (in order): the OMG standards (e.g., MDA, UML, MOF, OCL, SysML), the ISO standards for software quality models (e.g., 9126 and 25,000), Krogstie, Lindland, and Moody. We also discovered families of works about quality, i.e., works that belong to the same author or topic. Seventy-three works were found with evidence of the mismatch between the academic/research field of quality evaluation of modeling languages and actual MDE practice in industry. We demonstrate that this field does not currently solve quality issues reported in industrial scenarios. The evidence of the mismatch was grouped in eight categories, four for academic/research evidence and four for industrial reports. These categories were detected based on the scope proposed in each one of the academic/research works and from the questions and issues raised by real practitioners. We then proposed a scenario to illustrate quality issues in a real information system project in which multiple modeling languages were used. For the evaluation of the quality of this MDE scenario, we chose one of the most cited and influential quality frameworks; it was detected from the information obtained in the identification of the categories about quality definition for MDE. We demonstrated that the selected framework falls short in addressing the quality issues. Finally, based on the findings, we derive eight challenges for quality evaluation in MDE projects that current quality initiatives do not address sufficiently.F.G, would like to thank COLCIENCIAS (Colombia) for funding this work through the Colciencias Grant call 512-2010. This work has been supported by the Gene-ralitat Valenciana Project IDEO (PROMETEOII/2014/039), the European Commission FP7 Project CaaS (611351), and ERDF structural funds.Giraldo-Velásquez, FD.; España Cubillo, S.; Pastor López, O.; Giraldo, WJ. (2016). Considerations about quality in model-driven engineering. Software Quality Journal. 1-66. https://doi.org/10.1007/s11219-016-9350-6S166(1985). Iso information processing—documentation symbols and conventions for data, program and system flowcharts, program network charts and system resources charts. ISO 5807:1985(E) (pp. 1–25).(2011). Iso/iec/ieee systems and software engineering – architecture description. ISO/IEC/IEEE 42010:2011(E) (Revision of ISO/IEC 42010:2007 and IEEE Std 1471-2000) (pp. 1–46).Abran, A., Moore, J.W., Bourque, P., Dupuis, R., & Tripp, L.L. (2013). Guide to the Software Engineering Body of Knowledge (SWEBOK) version 3 public review. IEEE. ISO Technical Report ISO/IEC TR 19759.Agner, L.T.W., Soares, I.W., Stadzisz, P.C., & Simão, J.M. (2013). A brazilian survey on {UML} and model-driven practices for embedded software development. Journal of Systems and Software, 86(4), 997–1005. {SI} : Software Engineering in Brazil: Retrospective and Prospective Views.Amstel, M.F.V. (2010). The right tool for the right job: assessing model transformation quality. pages 69–74. Affiliation: Eindhoven University of Technology, P.O. Box 513, 5600 MB, Eindhoven, Netherlands. Cited By (since 1996):1.Aranda, J., Damian, D., & Borici, A. (2012). Transition to model-driven engineering: what is revolutionary, what remains the same?. In Proceedings of the 15th international conference on model driven engineering languages and systems, MODELS’12 (pp. 692–708). Berlin, Heidelberg: Springer.Arendt, T., & Taentzer, G. (2013). A tool environment for quality assurance based on the eclipse modeling framework. Automated Software Engineering, 20(2), 141–184.Atkinson, C., Bunse, C., & Wüst, J. (2003). Driving component-based software development through quality modelling, volume 2693. Cited By (since 1996):3.Baker, P., Loh, S., & Weil, F. (2005). Model-driven engineering in a large industrial context—motorola case study. In Briand, L., & Williams, C. (Eds.) Model Driven Engineering Languages and Systems, volume 3713 of Lecture Notes in Computer Science (pp. 476–491). Berlin, Heidelberg: Springer.Barišić, A., Amaral, V., Goulão, M., & Barroca, B. (2011). Quality in use of domain-specific languages: a case study. In Proceedings of the 3rd ACM SIGPLAN workshop on evaluation and usability of programming languages and tools, PLATEAU ’11 (pp. 65–72). New York: ACM.Becker, J., Bergener, P., Breuker, D., & Rackers, M. (2010). Evaluating the expressiveness of domain specific modeling languages using the bunge-wand-weber ontology. In 2010 43rd Hawaii international conference on system sciences (HICSS) (pp. 1–10).Bertrand Portier, L.A. (2009). Model driven development misperceptions and challenges.Bézivin, J., & Kurtev, I. (2005). Model-based technology integration with the technical space concept. In Proceedings of the Metainformatics Symposium: Springer.Brambilla, M. (2016). How mature is of model-driven engineering as an engineering discipline @ONLINE.Brambilla, M., & Fraternali, P. (2014). Large-scale model-driven engineering of web user interaction: The webml and webratio experience. Science of Computer Programming, 89 Part B(0), 71 – 87. Special issue on Success Stories in Model Driven Engineering.Brown, A. (2009). Simple and practical model driven architecture (mda) @ONLINE.Bruel, J.-M., Combemale, B., Ober, I., & Raynal, H. (2015). Mde in practice for computational science. Procedia Computer Science, 51, 660–669.Budgen, D., Burn, A.J., Brereton, O.P., Kitchenham, B.A., & Pretorius, R. (2011). Empirical evidence about the uml: a systematic literature review. Software: Practice and Experience, 41(4), 363–392.Burden, H., Heldal, R., & Whittle, J. (2014). Comparing and contrasting model-driven engineering at three large companies. In Proceedings of the 8th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM ’14 (pp. 14:1–14:10). New York: ACM.Cabot, J. Has mda been abandoned (by the omg)?Cabot, J. (2009). Modeling will be commonplace in three years time @ONLINE.Cachero, C., Poels, G., Calero, C., & Marhuenda, Y. (2007). Towards a Quality-Aware Engineering Process for the Development of Web Applications. Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/462, Ghent University, Faculty of Economics and Business Administration.Challenger, M., Kardas, G., & Tekinerdogan, B. (2015). A systematic approach to evaluating domain-specific modeling language environments for multi-agent systems. Software Quality Journal, 1–41.Chaudron, M.V., Heijstek, W., & Nugroho, A. (2012). How effective is uml modeling? Software & Systems Modeling, 11(4), 571–580. J2: Softw Syst Model.Chenouard, R., Granvilliers, L., & Soto, R. (2008). Model-driven constraint programming. pages 236–246. Affiliation: CNRS, LINA, Universit de Nantes, France; Affiliation: Pontificia Universidad Catlica de, Valparaiso, Chile. Cited By (since 1996):8.Clark, T., & Muller, P.-A. (2012). Exploiting model driven technology: a tale of two startups. Software and Systems Modeling, 11(4), 481–493.Corneliussen, L. (2008). What do you think of model-driven software development?Costal, D., Gómez, C., & Guizzardi, G. (2011). Formal semantics and ontological analysis for understanding subsetting, specialization and redefinition of associations in uml. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6998 LNCS:189–203. cited By (since 1996)3.Cruz-Lemus, J.A., Maes, A., Género, M., Poels, G., & Piattini, M. (2010). The impact of structural complexity on the understandability of uml statechart diagrams. Information Sciences, 180(11), 2209–2220. Cited By (since 1996):14.Cuadrado, J.S., Izquierdo, J.L.C., & Molina, J.G. (2014). Applying model-driven engineering in small software enterprises. Science of Computer Programming, 89 Part B(0), 176 – 198. Special issue on Success Stories in Model Driven Engineering.Da Silva, A.R. (2015). Model-driven engineering: a survey supported by the unified conceptual model. Computer Languages Systems and Structures, 43, 139–155.Da Silva Teixeira, D.G.M., Quirino, G.K., Gailly, F., De Almeida Falbo, R., Guizzardi, G., & Perini Barcellos, M. (2016). PoN-S: a Systematic Approach for Applying the Physics of Notation (PoN), (pp. 432–447). Cham: Springer International Publishing.Davies, I., Green, P., Rosemann, M., Indulska, M., & Gallo, S. (2006). How do practitioners use conceptual modeling in practice? Data and Knowledge Engineering, 58(3), 358 – 380. Including the special issue : {ER} 2004ER 2004.Davies, J., Milward, D., Wang, C.-W., & Welch, J. (2015). Formal model-driven engineering of critical information systems. Science of Computer Programming, 103(0), 88 – 113. Selected papers from the First International Workshop on Formal Techniques for Safety-Critical Systems (FTSCS 2012).De Oca, I.M.-M., Snoeck, M., Reijers, H.A., & Rodríguez-Morffi, A. (2015). A systematic literature review of studies on business process modeling quality. Information and Software Technology, 58, 187–205.DenHaan, J. (2009). 8 reasons why model driven development is dangerous @ONLINE.DenHaan, J. (2010). Model driven engineering vs the commando pattern @ONLINE.DenHaan, J. (2011a). Why aren’t we all doing model driven development yet @ONLINE.DenHaan, J. (2011b). Why there is no future model driven development @ONLINE.Di Ruscio, D., Iovino, L., & Pierantonio, A. (2013). Managing the coupled evolution of metamodels and textual concrete syntax specifications. cited By (since 1996)0.Dijkman, R.M., Dumas, M., & Ouyang, C. (2008). Semantics and analysis of business process models in {BPMN}. Information and Software Technology, 50(12), 1281–1294.Domínguez-Mayo, F.J., Escalona, M.J., Mejías, M., Ramos, I., & Fernández, L. (2011). A framework for the quality evaluation of mdwe methodologies and information technology infrastructures. International Journal of Human Capital and Information Technology Professionals, 2(4), 11–22.Domínguez-Mayo, F.J., Escalona, M.J., Mejías, M., & Torres, A.H. (2010). A quality model in a quality evaluation framework for mdwe methodologies. pages 495–506. Affiliation: Departamento de Lenguajes y Sistemas Informíticos, University of Seville, Seville, Spain., Cited By (since 1996):1.Dubray, J.-J. (2011). Why did mde miss the boat?.Escalona, M.J., Gutiérrez, J.J., Pérez-Pérez, M., Molina, A., Domínguez-Mayo, E., & Domínguez-Mayo, F.J. (2011). Measuring the Quality of Model-Driven Projects with NDT-Quality, (pp. 307–317). New York: Springer.Espinilla, M., Domínguez-Mayo, F.J., Escalona, M.J., Mejías, M., Ross, M., & Staples, G. (2011). A Method Based on AHP to Define the Quality Model of QuEF (Vol. 123, pp. 685–694). Berlin, Heidelberg: Springer.Fabra, J., Castro, V.D., Álvarez, P., & Marcos, E. (2012). Automatic execution of business process models: exploiting the benefits of model-driven engineering approaches. Journal of Systems and Software, 85(3), 607–625. Novel approaches in the design and implementation of systems/software architecture.Falkenberg, E.D., Hesse, W., Lindgreen, P., Nilsson, B.E., Oei, J.L.H., Rolland, C., Stamper, R.K., Assche, F.J.M.V., Verrijn-Stuart, A.A., & Voss, K. (1996). Frisco: a framework of information system concepts. Technical report, The IFIP WG 8. 1 Task Group FRISCO.Fettke, P., Houy, C., Vella, A.-L., & Loos, P. (2012). Towards the Reconstruction and Evaluation of Conceptual Model Quality Discourses – Methodical Framework and Application in the Context of Model Understandability, volume 113 of Lecture Notes in Business Information Processing, chapter 28, pages 406–421, Springer, Berlin, Heidelberg.Finnie, S. (2015). Modeling community: Are we missing something?Fournier, C. (2008). Is uml [email protected], R., & Rumpe, B. (2007). Model-driven development of complex software: a research roadmap. In Future of Software Engineering, 2007, FOSE ’07 (pp. 37–54).Gallego, M., Giraldo, F.D., & Hitpass, B. (2015). Adapting the pbec-otss software selection approach for bpm suites: an application case. In 2015 34th International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–10).Galvão, I., & Goknil, A. (2007). Survey of traceability approaches in model-driven engineering. cited By (since 1996)22.Giraldo, F., España, S., Giraldo, W., & Pastor, O. (2015). Modelling language quality evaluation in model-driven information systems engineering: a roadmap. In 2015 IEEE 9th International Conference on Research Challenges in Information Science (RCIS) (pp. 64–69).Giraldo, F., España, S., & Pastor, O. (2014). Analysing the concept of quality in model-driven engineering literature: a systematic review. In 2014 IEEE Eighth International Conference on Research Challenges in Information Science (RCIS) (pp. 1–12).Giraldo, F.D., España, S., & Pastor, O. (2016). Evidences of the mismatch between industry and academy on modelling language quality evaluation. arXiv: 1606.02025 .González, C., & Cabot, J. (2014). Formal verification of static software models in mde: a systematic review. Information and Software Technology, 56(8), 821–838. cited By (since 1996)0.González, C.A., Büttner, F., Clarisó, R., & Cabot, J. (2012). Emftocsp: a tool for the lightweight verification of emf models. pages 44–50. Affiliation: cole des Mines de Nantes, INRIA, LINA, Nantes, France; Affiliation: Universitat Oberta de Catalunya, Barcelona, Spain. Cited By (since 1996):1.Gorschek, T., Tempero, E., & Angelis, L. (2014). On the use of software design models in software development practice: an empirical investigation. Journal of Systems and Software, 95(0), 176– 193.Goulão, M., Amaral, V., & Mernik, M. (2016). Quality in model-driven engineering: a tertiary study. Software Quality Journal, 1–33.Grobshtein, Y., & Dori, D. (2011). Generating sysml views from an opm model: design and evaluation. Systems Engineering, 14(3), 327–340.Haan, J.d. (2008). 8 reasons why model-driven approaches (will) fail.Harel, D., & Rumpe, B. (2000). Modeling languages: Syntax, semantics and all that stuff, part i: The basic stuff, Israel. Technical report Jerusalem Israel.Harel, D., & Rumpe, B. (2004). Meaningful modeling: what’s the semantics of semantics? Computer, 37(10), 64–72.Hebig, R., & Bendraou, R. (2014). On the need to study the impact of model driven engineering on software processes. In Proceedings of the 2014 International Conference on Software and System Process, ICSSP 2014 (pp. 164–168). New York: ACM.Heidari, F., & Loucopoulos, P. (2014). Quality evaluation framework (qef): modeling and evaluating quality of business processes. International Journal of Accounting Information Systems, 15(3), 193–223. Business Process Modeling.Heymans, P., Schobbens, P.Y., Trigaux, J.C., Bontemps, Y., Matulevicius, R., & Classen, A. (2008). Evaluating formal properties of feature diagram languages. Software, IET, 2(3), 281–302. ID 2.Hindawi, M., Morel, L., Aubry, R., & Sourrouille, J.-L. (2009). Description and Implementation of a UML Style Guide (Vol. 5421, pp. 291–302). Berlin: Springer.Hoang, D. (2012). Current limitations of mdd and its implications @ONLINE.Hodges, W. (2013). Model theory Zalta, E.N. (Ed.) The Stanford Encyclopedia of Philosophy. Fall 2013 edition.Hutchinson, J., Rouncefield, M., & Whittle, J. (2011a). Model-driven engineering practices in industry. In Proceedings of the 33rd International Conference on Software Engineering, ICSE’11 (pp. 633–642). New York: ACM.Hutchinson, J., Whittle, J., & Rouncefield, M. (2014). Model-driven engineering practices in industry: social, organizational and managerial factors that lead to success or failure. Science of Computer Programming, 89 Part B(0), 144–161. Special issue on Success Stories in Model Driven Engineering.Hutchinson, J., Whittle, J., Rouncefield, M., & Kristoffersen, S. (2011b). Empirical assessment of mde in industry. In Proceedings of the 33rd International Conference on Software Engineering, ICSE’11 (pp. 471–480). New York: ACM.Igarza, I.M.H., Boada, D.H.G., & Valdés, A.P. (2012). Una introducción al desarrollo de software dirigido por modelos. Serie Científica, 5(3).ISO/IEC (2001). ISO/IEC 9126. Software engineering—Product quality. ISO/IEC.Izurieta, C., Rojas, G., & Griffith, I. (2015). Preemptive management of model driven technical debt for improving software quality. In Proceedings of the 11th International ACM SIGSOFT Conference on Quality of Software Architectures, QoSA’15 (pp. 31–36). New York: ACM.Jalali, S., & Wohlin, C. (2012). Systematic literature studies: Database searches vs. backward snowballing. In Proceedings of the ACM-IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM’12 (pp. 29–38). New York: ACM.Kahraman, G., & Bilgen, S. (2013). A framework for qualitative assessment of domain-specific languages. Software & Systems Modeling, 1–22.Kessentini, M., Langer, P., & Wimmer, M. (2013). Searching models, modeling search: On the synergies of sbse and mde (pp. 51–54).Kitchenham, B., & Charters, S. (2007). Guidelines for performing Systematic Literature Reviews in Software Engineering. Technical Report EBSE 2007-001, Keele University and Durham University Joint Report.Kitchenham, B., Pfleeger, S., Pickard, L., Jones, P., Hoaglin, D., El Emam, K., & Rosenberg, J. (2002). Preliminary guidelines for empirical research in software engineering. IEEE Transactions on Software Engineering, 28(8), 721–734.Klinke, M. (2008). Do you use mda/mdd/mdsd, any kind of model-driven approach? Will it be the future?Köhnlein, J. (2013). Eclipse diagram editors from a user’s perspective.Kolovos, D.S., Paige, R.F., & Polack, F.A. (2008). The grand challenge of scalability for model driven engineering. In Models in Software Engineering (pp. 48–53): Springer.Kolovos, D.S., Rose, L.M., Matragkas, N., Paige, R.F., Guerra, E., Cuadrado, J.S., De Lara, J., Ráth, I., Varró, D., Tisi, M., & Cabot, J. (2013). A research roadmap towards achieving scalability in model driven engineering. In Proceedings of the Workshop on Scalability in Model Driven Engineering, BigMDE’13 (pp. 2:1–2:10). New York: ACM.Krill, P. (2016). Uml to be ejected from microsoft visual studio (infoworld).Krogstie, J. (2012a). Model-based development and evolution of information systems: a quality approach, Springer Publishing Company, Incorporated.Krogstie, J. (2012b). Quality of modelling languages, (pp. 249–280). London: Springer.Krogstie, J. (2012c). Quality of models, (pp. 205–247). London: Springer.Krogstie, J. (2012d). Specialisations of SEQUAL, (pp. 281–326). London: Springer.Krogstie, J., Lindland, O.I., & Sindre, G. (1995). Defining quality aspects for conceptual models. In Proceedings of the IFIP International Working Conference on Information System Concepts: Towards a Consolidation of Views (pp. 216–231). London: Chapman & Hall, Ltd.Kruchten, P. (2000). The rational unified process: an introduction, 2nd edn. Boston: Addison-Wesley Longman Publishing Co., Inc.Kruchten, P., Nord, R., & Ozkaya, I. (2012). Technical debt: from metaphor to theory and practice. Software, IEEE, 29(6), 18–21.Kulkarni, V., Reddy, S., & Rajbhoj, A. (2010). Scaling up model driven engineering – experience and lessons learnt. In Petriu, D., Rouquette, N., & Haugen, y. (Eds.) Model Driven Engineering Languages and Systems, volume 6395 of Lecture Notes in Computer Science (pp. 331–345). Berlin, Heidelberg: Springer.Laguna, M.A., & Marqués, J.M. (2010). Uml support for designing software product lines: the package merge mechanism, 16(17), 2313–2332.Lange, C. (2007a). Model size matters. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4364 LNCS:211–216. cited By (since 1996)1.Lange, C., & Chaudron, M. (2005). Managing Model Quality in UML-Based Software Development. In 13th IEEE International Workshop on Technology and Engineering Practice, 2005 (pp. 7–16).Lange, C., Chaudron, M.R.V., Muskens, J., Somers, L.J., & Dortmans, H.M. (2003). An empirical investigation in quantifying inconsistency and incompleteness of uml designs. In Incompleteness of UML Designs, Proceedings Workshop on Consistency Problems in UML-based Software Development, 6th International Conference on Unified Modeling Language, UML, 2003.Lange, C., DuBois, B., Chaudron, M., & Demeyer, S. (2006). An experimental investigation of uml modeling conventions. In Nierstrasz, O., Whittle, J., Harel, D., & Reggio, G. (Eds.) Model Driven Engineering Languages and Systems, volume 4199 of Lecture Notes in Computer Science (pp. 27–41). Berlin, Heidelberg: Springer.Lange, C.F.J., & Chaudron, M.R.V. (2006). Effe

Role of age and comorbidities in mortality of patients with infective endocarditis

Purpose: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. Methods: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015. Patients were stratified into three age groups:<65 years, 65 to 80 years, and = 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. Results: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 = 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients =80 years who underwent surgery were significantly lower compared with other age groups (14.3%, 65 years; 20.5%, 65-79 years; 31.3%, =80 years). In-hospital mortality was lower in the <65-year group (20.3%, <65 years;30.1%, 65-79 years;34.7%, =80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%, =80 years; p = 0.003).Independent predictors of mortality were age = 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI = 3 (HR:1.62; 95% CI:1.39–1.88), and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared, the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. Conclusion: There were no differences in the clinical presentation of IE between the groups. Age = 80 years, high comorbidity (measured by CCI), and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

Effectiveness of the combination elvitegravir/cobicistat/tenofovir/emtricitabine (EVG/COB/TFV/FTC) plus darunavir among treatment-experienced patients in clinical practice : A multicentre cohort study

Background: The aim of this study was to investigate the effectiveness and tolerability of the combination elvitegravir/cobicistat/tenofovir/emtricitabine plus darunavir (EVG/COB/TFV/FTC + DRV) in treatment-experienced patients from the cohort of the Spanish HIV/AIDS Research Network (CoRIS). Methods: Treatment-experienced patients starting treatment with EVG/COB/TFV/FTC + DRV during the years 2014-2018 and with more than 24 weeks of follow-up were included. TFV could be administered either as tenofovir disoproxil fumarate or tenofovir alafenamide. We evaluated virological response, defined as viral load (VL) < 50 copies/ml and < 200 copies/ml at 24 and 48 weeks after starting this regimen, stratified by baseline VL (< 50 or ≥ 50 copies/ml at the start of the regimen). Results: We included 39 patients (12.8% women). At baseline, 10 (25.6%) patients had VL < 50 copies/ml and 29 (74.4%) had ≥ 50 copies/ml. Among patients with baseline VL < 50 copies/ml, 85.7% and 80.0% had VL < 50 copies/ml at 24 and 48 weeks, respectively, and 100% had VL < 200 copies/ml at 24 and 48 weeks. Among patients with baseline VL ≥ 50 copies/ml, 42.3% and 40.9% had VL < 50 copies/ml and 69.2% and 68.2% had VL < 200 copies/ml at 24 and 48 weeks. During the first 48 weeks, no patients changed their treatment due to toxicity, and 4 patients (all with baseline VL ≥ 50 copies/ml) changed due to virological failure. Conclusions: EVG/COB/TFV/FTC + DRV was well tolerated and effective in treatment-experienced patients with undetectable viral load as a simplification strategy, allowing once-daily, two-pill regimen with three antiretroviral drug classes. Effectiveness was low in patients with detectable viral loads