107 research outputs found

    Estudio de calidad de vida de pacientes con coxartrosis

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    La artroplastia de cadera secundaria a artrosis es una de las intervenciones más frecuentes dentro de la cirugía ortopédica. La coxartrosis produce una limitación funcional severa, que invalida a los pacientes y los hace dependientes para sus actividades cotidianas. Se calcula la calidad de vida aportada en las intervenciones de reemplazo articular de cadera de 85 pacientes con coxartrosis utilizando el “EQ-5D”. La puntuación media preoperatoria fue 0,222 ± 0,320 y la postoperatoria 0,794 ± 0,251. El incremento de calidad de vida en función de la edad de los pacientes siguió una tendencia descendente (β= −0,010), sin diferencias significativas (p=0,214). El incremento de calidad de vida no se vió condicionado por la presencia de infección (p>0,5), duración de la intervención (p>0,5) ni tiempo de estancia hospitalaria (p>0,5). La sustitución de esta articulación ha transformado la vida de muchos de los pacientes incrementando su calidad de vida, principalmente en pacientes que ingresan por coxartrosis en comparación con otros diagnósticos.Hip replacement secondary to osteoarthritis is one of the most performed surgeries in orthopaedic surgery. Osteoarthritis produces a severe functional limitation that invalidates patients and makes them dependent for their daily activities. It is calculated the quality of life provided by hip replacement procedure in 85 osteoarthritis patients using the “EQ-5D”. The mean preoperative score was 0.222 ± 0.320 and the postoperative score 0.794 ± 0.251. The increase in quality of life according to patients age followed a descendent tendency (β= −0.010), without a statitically relationship (p=0.214). The increase in quality of life was not conditioned by infection (p>0.5), length of stay (p>0.5) or length of the procedure (p>0.5). Joint replacement has changed the lives of many patients, increasing their quality of life, mainly in osteoarthritis patients compared to patients with other diagnosis

    BIM en la universidad

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    126 páginas.La tecnología BIM (Building Information Modeling, por sus siglas en inglés) es un método innovador para facilitar la comunicación entre los sectores de la arquitectura, ingeniería y construcción, donde se genera intercambio de información de manera eficiente, se crean representaciones digitales (modelosv3d ricos en información) de todas las fases del proceso de construcción y simulan el rendimiento en la vida real, lo que perfecciona el flujo de trabajo, aumenta la productividad y mejora la calidad. En México se realizó un estudio en la industria de la construcción (Bim Forum México, encuesta 2017), que analiza las razones por las que las empresas no utilizan BIM; las que destacan que: las licencias y equipos son muy caros (29%), no se cuenta con personal calificado (23%), los clientes no lo requieren (5%), la industria mexicana no está preparada (4%), no hay capacitación en ello (3%), no hay tiempo para implementarlo (2%), etc. Ante tales razones, los desafíos a los que se enfrenta el sector académico es implementar dentro de sus programas de estudio la enseñanza la tecnología BIM para la formación de nuevas generaciones de profesionales (arquitectos e ingenieros) que cuenten con los conocimientos y habilidades necesarias para responder a los retos que se enfrenta la industria de la construcción. El presente documento se enfoca a estudios realizados por académicos de diversas universidades: Worcester Polytechnic Institute, USA; Universidad Politécnica de Madrid; Universidad Autónoma de Yucatán, México; y Universidad Autónoma Metropolitana, Unidad Azcapotzalco, México. Las investigaciones han sido acerca de la experiencia en la implementación de la tecnología BIM en la práctica y en el proceso de enseñanza aprendizaje

    Underwater Quaternary record of the Cartagena Bay (Murcia, Spain)

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    Se perforó un sondeo de 30 m en la Bahía de Cartagena. El doble objetivo del mismo fue obtener datos sobre el antiguo frente marítimo de la ciudad romana y establecer la cronoestratigrafía y evolución paleoambiental. El sondeo (E3) se muestreó con alta resolución. Los sedimentos de la parte inferior (30-11,3 m) con predominio de colores marrones que indican condiciones oxidantes, la fauna de aguas salobres (Cerastoderma glaucum/Cyprideis torosa) y la sedimentación dominada por fangos y arenas, permiten interpretar el medio sedimentario estudiado como una llanura fangosa costera ligada a un abanico aluvial. Las edades AAR obtenidas revelan que todo el MIS5 está incluido en el registro. La parte superior (11,3-3,0 m), correspondiente al MIS 1, consiste en fangos orgánicos negros con arena y grava. Aparece una amplia diversidad de moluscos marinos en estadios juveniles de desarrollo. Todo esto representa el “cul de sac” de una bahía protegida donde se acumulaban restos vegetales, periódicamente afectada por llegadas de detríticos aluviales. Existe una somerización a techo del depósitoA new borehole was drilled at the end of the Cartagena Bay. The twofold aim of this operation was to obtain insights into the ancient Roman city seafront, and to establish its cronostratigraphy and paleoenvironmental evolution. A continuous 30 m long core (E3) was drilled and sampled with high resolution. The sediments of the lower part (30-11.3 m) with predominant brown colour indicating oxydizing conditions, the brackish-water fauna (Cerastoderma glaucum/Cyprideis torosa) and mud/sand dominance, allow to interpret the sedimentary environment as formed in a coastal mud flat linked to an alluvial fan. Consistent AAR dating ages reveal that the whole MIS5 record is included. The upper part of the record (11.3-3.0 m), which belongs to MIS 1, is made of black muddy sand and gravel. It appears a high diversity of marine mollusk species mostly in juvenile stage of development. This represents a complex environment: a “cul-d-sac” at the protected end of the bay where plant debris accumulated, being intruded by alluvial inputs. A growing continental influence likely occurred at the to

    BIM en la construcción

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    244 páginas.En la actualidad, con la metodología BIM (Building Information Modeling), todos los sistemas de información de los procesos productivos en la obra se han integrado, la información se puede compartir a distancia y en tiempo real con todos los actores involucrados en el proyecto. En estas condiciones, las instituciones generadoras de obras y las empresas prestadoras de servicios se están rediseñando con nuevos modelos de negocios enfocados en satisfacer las actuales demandas y experiencias de los clientes. El libro que aquí se presenta reúne el trabajo de investigación referente a BIM de la Red Académica de Diseño Construcción integrada por académicos de la Facultad de Ingeniería de la Universidad Autónoma de Yucatán, México (UADY), el Worcester Polytechnical Institute (WPI) de Massachusetts, Estados Unidos y del Área de Administración y Tecnología para el Diseño de la Universidad Autónoma Metropolitana, Unidad Azcapotzalco (UAM). También han colaborado con la Red investigadores de la Universidad Politécnica de Madrid (UPM), España y, dentro de la UAM, académicos de la División de Ciencias Básicas e Ingeniería, Departamento de Materiales, del Área de Construcción. Cabe mencionar que los artículos ya han sido publicados con anterioridad en los Anuarios de Administración y Tecnología para el Diseño y las Compilaciones de Artículos de Investigación en Administración y Tecnología para la Arquitectura, Diseño e Ingeniería, productos del trabajo de investigación del Área que edita anualmente desde 1999, como se indica en el índice del presente libro

    New regulations regarding Postgraduate Medical Training in Spain: perception of the tutor's role in the Murcia Region

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    <p>Abstract</p> <p>Background</p> <p>Recently introduced regulatory changes have expanded the Tutor role to include their primary responsibility for Postgraduate Medical Training (PMT). However, accreditation and recognition of that role has been devolved to the autonomic regions. The opinions of the RT may be relevant to future decisions;</p> <p>Methods</p> <p>A comprehensive questionnaire, including demographic characteristics, academic and research achievement and personal views about their role, was sent to 201 RTs in the Murcia Region of Spain. The responses are described using median and interquartile ranges (IQR);</p> <p>Results</p> <p>There were 147 replies (response rate 73%), 69% male, mean age 45 ± 7 yrs. RTs perception of the residents' initial knowledge and commitment throughout the program was 5 (IQR 4-6) and 7 (IQR 5-8), respectively. As regards their impact on the PMT program, RTs considered that their own contribution was similar to that of senior residents. RTs perception of how their role was recognised was 5 (IQR 3-6). Only 16% did not encounter difficulties in accessing specific RT training programs. Regarding the RTs view of their various duties, supervision of patient care was accorded the greatest importance (64%) while the satisfactory completion of the PMT program and supervision of day-to-day activities were also considered important (61% and 59% respectively). The main RT requirements were: a greater professional recognition (97%), protected time (95%), specific RT training programs (95%) and financial recognition (86%);</p> <p>Conclusions</p> <p>This comprehensive study, reflecting the feelings of our RTs, provides a useful insight into the reality of their work and the findings ought to be taken into consideration in the imminent definitive regulatory document on PMT.</p

    Exploring the potential of phone call data to characterize the relationship between social network and travel behavior

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    [EN] Social network contacts have significant influence on individual travel behavior. However, transport models rarely consider social interaction. One of the reasons is the difficulty to properly model social influence based on the limited data available. Non-conventional, passively collected data sources, such as Twitter, Facebook or mobile phones, provide large amounts of data containing both social interaction and spatiotemporal information. The analysis of such data opens an opportunity to better understand the influence of social networks on travel behavior. The main objective of this paper is to examine the relationship between travel behavior and social networks using mobile phone data. A huge dataset containing billions of registers has been used for this study. The paper analyzes the nature of co-location events and frequent locations shared by social network contacts, aiming not only to provide understanding on why users share certain locations, but also to quantify the degree in which the different types of locations are shared. Locations have been classified as frequent (home, work and other) and non-frequent. A novel approach to identify co-location events based on the intersection of users' mobility models has been proposed. Results show that other locations different from home and work are frequently associated to social interaction. Additionally, the importance of non-frequent locations in co-location events is shown. Finally, the potential application of the data analysis results to improve activity-based transport models and assess transport policies is discussed.The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the quality of the paper. The research leading to these results has received funding from the European Union Seventh Framework Programme FP7/2007-2013 under grant agreement no 318367 (EUNOIA project) and no 611307 (INSIGHT project). The work of ML has been funded under the PD/004/2013 project, from the Conselleria de Educacion, Cultura y Universidades of the Government of the Balearic Islands and from the European Social Fund through the Balearic Islands ESF operational program for 2013-2017.Picornell Tronch, M.; Ruiz Sánchez, T.; Lenormand, M.; Ramasco, JJ.; Dubernet, T.; Frías-Martínez, E. (2015). Exploring the potential of phone call data to characterize the relationship between social network and travel behavior. Transportation. 42(4):647-668. https://doi.org/10.1007/s11116-015-9594-1S647668424Ahas, R., Aasa, A., Silm, S., Tiru, M.: Daily rhythms of suburban commuters’ movements in the tallinn metropolitan area: case study with mobile positioning data. Transp. Res. Part C 18, 45–54 (2010)Arentze, T.,Timmermans, H. J.: social networks, social interactions and activity-travel behavior: a framework for micro-simulation. Paper presented at the 85th annual meeting of the Transportation Research Board, Washington, D. C., Jan 2006 (2006)Arentze, T., Timmermans, H.: Social networks, social interactions, and activity-travel behavior: a framework for microsimulation. Environ. Plan. 35, 1012–1027 (2008)Axhausen, K.W.: Social networks and travel: some hypotheses. In: Donaghy, K.P., Poppelreuter, S., Rudinger, G. (eds.) Social Aspects of Sustainable Transport: Transatlantic Perspectives, pp. 90–108. Ashgate, Aldershot (2005)Bagrow, J.P., Lin, Y.-R.: Mesoscopic structure and social aspects of human mobility. PLoS One 7(5), 1–11 (2012)Bar-Gera, H.: Evaluation of a cellular phone-based system for measurements of traffic speeds and travel times: a case study from israel. Transp. Res. Part C 15(2007), 380–391 (2007)Becker, R.A., Cáceres, R., Hanson, K., Loh, J.M., Urbanek, S., Varshavsky, A., Volinsky, C.: A tale of one city: using cellular network data for urban planning. Pervasive Comput. IEEE 10(4), 18–26 (2011)Brockmann, D., Hufnagel, L., Geisel, T.: The scaling laws of human travel. Nature 439, 462 (2006)Caceres, N., Wideberg, J.P., Benitez, F.G.: Deriving origin–destination data from a mobile phone network. IET Intell. Transp. Syst. 1(1), 5–26 (2007)Caceres, N., Wideberg, J.P., Benitez, F.G.: Review of traffic data estimations extracted from cellular networks. IET Intell. Transp. Syst. 2(3), 179–192 (2008)Caceres, N., Romero, L.M., Benitez, F.G., Castillo, J.M.D.: Traffic flow estimation models using cellular phone data. IEEE Trans. Intell. Transp. Syst. 13(3), 1430–1441 (2012)Calabrese, F., Pereira, F. C., Lorenzo, G. D., Liu, L., Ratti, C.: The geography of taste: analyzing cell-phone mobility and social events. In: Proceedings of IEEE International Conference on Pervasive Computing (2010)Calabrese, F., Smoreda, Z., Blondel, V.D., Ratti, C.: Interplay between telecommunications and face-to-face interactions: a study using mobile phone data. PLoS One 6(7), e20814 (2011a). doi: 10.1371/journal.pone.0020814Calabrese, F., Lorenzo, G.D., Liu, L., Ratti, C.: Estimating origin-destination flows using mobile phone location data. Pervasive Comput. IEEE 10(4), 36–44 (2011b)Carrasco, J.A., Miller, E.J.: Exploring the propensity to perform social activities: social networks approach. Transportation 33, 463–480 (2006)Carrasco, J.A., Hogan, B., Wellman, B., Miller, E.J.: Collecting social network data to study social activity-travel behaviour: an egocentric approach. Environ. Plan. B 35(6), 961–980 (2008a)Carrasco, J.A., Hogan B., Wellman B., Miller E. J.: Agency in social activity and ICT interactions: The role of social networks in time and space, Tijdschrift voor Economische en Sociale Geografie (J. Eco. Soc. Geogr.), 99(5), 562–583 (2008b)Carrasco, J.A., Miller, E.J., Wellman, B.: How far and with whom do people socialize? Empirical evidence about the distance between social network members. Transp. Res. Rec. 2076, 114–122 (2008b)Carrasco, J.A., Miller, E.J.: The social dimension in action: a multilevel, personal networks model of social activity frequency. Transp. Res. Part A 43(1), 90–104 (2009)Chen, C., Mei, Y.: Does distance still matter in facilitating social ties? The roles of mobility patterns and the built environment. Presented at 93rd TRB annual meeting (2014)Cho E., Myers S.A., Leskovek J.: Friendship and mobility: user movement in location-based social networks. In: KDD ‘11 Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1082–1090 (2011)Clifton, K.J.: The social context of travel behavior. In: Zmud, J., et al. (eds.) Transport Survey Methods: Best Practice for Decision Making, pp. 441–448. Emerald Press, London (2013)Do T., Gatica-Perez D.: Contextual conditional models for smartphone-based human mobility prediction. In: Proceedings ACM International Conference on Ubiquitous Computing, Pittsburgh, Sept (2012)Doyle, J., Hung, P., Kelly, D., Mcloone, S., Farrell, R.: Utilising mobile phone billing records for travel mode discovery. ISSC 2011, Trinity College Dublin, June (2011)Dubernet, T., Axhausen K. W.: Solution concepts for the simulation of household-level joint descision making in multi-agent travel simulation tools, paper presented at the 14th Swiss Transport Research Conference (STRC), Ascona (2014)Dugundji, E., Walker, J.: Discrete choice with social and spatial network interdependencies: an empirical example using mixed GEV models with field and “panel” effects. Transp. Res. Rec. 1921, 70–78 (2005)Eagle, N., Pentland, A., Lazer, D.: Inferring social network structure using mobile phone data. Proc. Natl. Acad. Sci. (PNAS) 106(36), 15274–15278 (2009)González, M.C., Hidalgo, C.A., Barabási, A.-L.: Understanding individual human mobility patterns. Nature 453(2008), 779–782 (2008)Gould, J.: Cell phone enabled travel surveys: the medium moves the message. In: Zmud, J., et al. (eds.) Transport Survey Methods: Best Practice for Decision Making, pp. 51–70. Emerald Press, Bingley (2013)Habib, K.N., Carrasco, J.A.: Investigating the role of social networks in start time and duration of activities: a trivariate simultaneous econometric model. Transportation Research Record: Journal of the Transportation Research Board 2230, 1–8 (2011)Hackney, Jeremy K., Kay W. Axhausen: An agent model of social network and travel behavior interdependence. Paper presented at the 11th international conference on Travel Behaviour Research, Kyoto, Aug (2006)Hackney, J., Marchal, F.: A model for coupling multi-agent social interactions and traffic simulation, in: TRB 2009 annual meeting (2009)Hackney, J., Marchal, F.: A coupled multi-agent microsimulation of social interactions and transportation behavior. Transp. Res. Part A 45, 296–309 (2011)Horni, A.: Destination choice modeling of discretionary activities in transport microsimulations, Ph.D. Thesis, ETH Zurich, Zurich (2013)Isaacman, S.,Becker, R., Caceres, R., Kobourov, S., Martonosi, M., Rowland, J., Varshavsky, A.: Identifying important places in people’s lives from cellular network data. In: Procedings International Conference on Pervasive Computing, San Francisco, June (2011)Lane, N.D., Miluzzo, E., Lu, H., Peebles, D., Choudhury, T., Campbell, A.T.: A survey of mobile phone sensing. Commun. Mag. IEEE 48(9), 140–150 (2010)Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabasi, A.-L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M., Jebara, T., King, G., Macy, M., Roy, D., Van Alstyne, M.: Computational Social Science. Science 323, 721 (2009)Ma, H., Ronald, N., Arentze, T.A., Timmermans, H.J.P.: New credit mechanism for semicooperative agent-mediated joint activity-travel scheduling. Transp. Res. Rec. 2230, 104–110 (2011)Ma, H., Arentze, T. A., Timmermans, H. J. P.: Incorporating selfishness and altruism into dynamic joint activity-travel scheduling. Paper presented at the 13th international conference on Travel Behaviour Research (IATBR), Toronto, July (2012)Marchal, F., Nagel, K.: Allowed cooperative agents in a microsimulation to share information with each other about activity locations and about other agents, in order to optimize trip chains (2006)Molin, E.J.E., Arentze, T.A., Timmermans, H.J.P.: Social activities and travel demands : a model-based analysis of social-network data. Transp. Res. Rec. 2082, 168–175 (2007)Moore, J., Carrasco, J.A., Tudela, A.: Exploring the links between personal networks, time use, and the spatial distribution of social contacts. Transportation 40(4), 773–788 (2013)Onnela, J.-P., Saramaki, J., Hyvonen, J., Szabo, G., Lazer, D., et al.: Structure and tie strengths in mobile communication networks. Proc. Natl. Acad. Sci. U.S.A. 104, 7332–7336 (2007)Páez, A., Scott, D.M.: Social influence on travel behavior: a simulation example of the decision to telecommute. Environ. Plan. A 39(3), 647–665 (2007)Phithakkitnukoon, S., Calabrese, F., Smoreda, Z., Ratti, C.: Out of sight out of mind: how our mobile social network changes during migration. Proceedings of the IEEE International Conference on Social Computing, pp. 515–520. Cambridge University Press, Cambridge (2011)Phithakkitnukoon, S., Smoreda, Z., Olivier, P.: Socio-geography of human mobility: a study using longitudinal mobile phone data. PLoS One 7(6), e39253 (2012). doi: 10.1371/journal.pone.0039253Ronald, N.A., Arentze, T.A., Timmermans, H.J.P.: Modeling social interactions between individuals for joint activity scheduling. Transp. Res. Part B 46, 276–290 (2012a)Ronald, N.A., Dignum, V., Jonker, C., Arentze, T.A., Timmermans, H.J.P.: On the engineering of agent-based simulations of social activities with social networks. Inf. Softw. Technol. 54(6), 625–638 (2012b)Rose, G.: Mobile phones as traffic probes: practices, prospects and issues. Transp. Rev. 26(3), 275–291 (2006)Sharmeen, F., Arentze, T., Timmermans, H.: A multilevel path analysis of social network dynamics and the mutual interdependencies between face-to-face and ICT modes of social interaction in the context of life-cycle events. In: Roorda, M.J., Miller, E.J. (eds.) Travel Behaviour Research: Current Foundations, Future Prospects, pp. 411–432. Lulu Press, Toronto (2013)Sharmeen, F., Arentze, T.A., Timmermans, H.J.P.: Dynamics of face-to-face social interaction frequency: role of accessibility, urbanization, changes in geographical distance and path dependence. J. Transp. Geogr. 34, 211–220 (2014)Silm, S., Ahas, R.: The seasonal variability of population in estonian municipalities. Environ. Plan. A 42, 2527–2546 (2010)Silvis, J., Niemeier, D., D’Souza, R.: Social networks and travel behavior: report from an integrated travel diary. Paper presented at the 11th international conference on Travel Behaviour Research, Kyoto, Aug (2006)Sobolevsky, S., Szell, M., Campari, R., Couronné, T., Smoreda, Z., et al.: Delineating geographical regions with networks of human interactions in an extensive set of countries. PLoS One 8(12), e81707 (2013)Sohn, K., Kim, D.: Dynamic origin–destination flow estimation using cellular communication system. IEEE Trans. Veh. Technol. 57(5), 2703–2713 (2008)Song, C., Koren, T., Wang, P., Barabási, A.-L.: Modelling the scaling properties of human mobility. Nat. Phys. 6(2010), 818–823 (2010a)Song, C., Qu, Z., Blumm, N., Barabási, L.-L.: Limits of predictability in human mobility. Science 327(5968), 1018–1021 (2010b)Steenbruggen, J., Borzacchiello, M.T., Nijkamp, P., Scholten, H.: Mobile phone data from gsm networks for traffic parameter and urban spatial pattern assessment: A review of applications and opportunities. GeoJournal 78, 223–243 (2011). doi: 10.1007/s10708-011-9413-yVan den Berg, P., Arentze, T., Timmermans, H.J.P.: A path analysis of social networks, telecommunication and social activity–travel patterns. Transp. Res. Part C 26(2013), 256–268 (2013)Wang, H., Calabrese, F., Lorenzo, G. D., Ratti, C.: Transportation mode inference from anonymized and aggregated mobile phone call detail records. In: 13th international IEEE annual conference on intelligent transportation systems, 318–323 (2010)White, J. and Wells, I.: Extracting origin destination information from mobile phone data. Road transport information and Control, 19–21 Mar (2002)Yim, Y.: The state of cellular probes. California PATH Working Paper, UCB-ITS-PRR-2003-25 (2003)Ythier, J., Walker, J.L., Bierlaire, M.: The influence of social contacts and communication use on travel behavior: a smartphone-based study. In: Transportation Research Board annual meeting (2013

    Contribution of Candida biomarkers and DNA detection for the diagnosis of invasive candidiasis in ICU patients with severe abdominal conditions

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    BACKGROUND: To assess the performance of Candida albicans germ tube antibody (CAGTA), (1 → 3)-ß-D-glucan (BDG), mannan antigen (mannan-Ag), anti-mannan antibodies (mannan-Ab), and Candida DNA for diagnosing invasive candidiasis (IC) in ICU patients with severe abdominal conditions (SAC). METHODS: A prospective study of 233 non-neutropenic patients with SAC on ICU admission and expected stay ≥ 7 days. CAGTA (cutoff positivity ≥ 1/160), BDG (≥80, 100 and 200 pg/mL), mannan-Ag (≥60 pg/mL), mannan-Ab (≥10 UA/mL) were measured twice a week, and Candida DNA only in patients treated with systemic antifungals. IC diagnosis required positivities of two biomarkers in a single sample or positivities of any biomarker in two consecutive samples. Patients were classified as neither colonized nor infected (n = 48), Candida spp. colonization (n = 154) (low-grade, n = 130; high-grade, n = 24), and IC (n = 31) (intra-abdominal candidiasis, n = 20; candidemia, n = 11). RESULTS: The combination of CAGTA and BDG positivities in a single sample or at least one of the two biomarkers positive in two consecutive samples showed 90.3 % (95 % CI 74.2–98.0) sensitivity, 42.1 % (95 % CI 35.2–98.8) specificity, and 96.6 % (95 % CI 90.5–98.8) negative predictive value. BDG positivities in two consecutive samples had 76.7 % (95 % CI 57.7–90.1) sensitivity and 57.2 % (95 % CI 49.9–64.3) specificity. Mannan-Ag, mannan-Ab, and Candida DNA individually or combined showed a low discriminating capacity. CONCLUSIONS: Positive Candida albicans germ tube antibody and (1 → 3)-ß-D-glucan in a single blood sample or (1 → 3)-ß-D-glucan positivity in two consecutive blood samples allowed discriminating invasive candidiasis from Candida spp. colonization in critically ill patients with severe abdominal conditions. These findings may be helpful to tailor empirical antifungal therapy in this patient population
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