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dc.contributor.authorAndrés Iglesias, Cristina 
dc.contributor.authorAndaluz Ojeda, David 
dc.contributor.authorCicuendez, Ramón
dc.contributor.authorNogales, Leonor
dc.contributor.authorMartín, Silvia
dc.contributor.authorMartín Fernández, Marta 
dc.contributor.authorAlmansa Mora, Raquel 
dc.contributor.authorCalvo, Dolores
dc.contributor.authorEsteban Velasco, María Carmen
dc.contributor.authorVaquero Roncero, Luis Mario
dc.contributor.authorRíos Llorente, Alberto
dc.contributor.authorSánchez Barrado, Elisa
dc.contributor.authorMuñoz Bellvís, Luis
dc.contributor.authorAldecoa Álvarez Santullano, César Enrique 
dc.contributor.authorBermejo Martín, Jesús Francisco 
dc.date.accessioned2024-01-17T12:28:17Z
dc.date.available2024-01-17T12:28:17Z
dc.date.issued2020
dc.identifier.citationEur J Clin Invest. 2020 Jun;50(6):e13246es
dc.identifier.issn0014-2972es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/64661
dc.descriptionProducción Científicaes
dc.description.abstractBackground: Following the SEPSIS-3 consensus, detection of organ failure as assessed by the SOFA (Sequential Organ Failure Assessment) score, is mandatory to detect sepsis. Calculating SOFA outside of the Intensive Care Unit (ICU) is challenging. The alternative in this scenario, the quick SOFA, is very specific but less sensible. Biomarkers could help to detect the presence of organ failure secondary to infection either in ICU and non-ICU settings. Materials and methods: We evaluated the ability of four biomarkers (C-Reactive protein (CRP), lactate, mid-regional proadrenomedullin (MR-proADM) and procalcitonin (PCT)) to detect each kind of organ failure considered in the SOFA in 213 patients with infection, sepsis or septic shock, by using multivariate regression analysis and calculation of the area under the receiver operating curve (AUROC). Results: In the multivariate analysis, MR-proADM was an independent predictor of five different failures (respiratory, coagulation, cardiovascular, neurological and renal). In turn, lactate predicted three (coagulation, cardiovascular and neurological) and PCT two (cardiovascular and renal). CRP did not predict any of the individual components of SOFA. The highest AUROCs were those of MR-proADM and PCT to detect cardiovascular (AUROC, CI95%): MR-proADM (0.82 [0.76-0.88]), PCT (0.81 [0.75-0.87] (P < .05) and renal failure: MR-proADM (0.87 [0.82-0.92]), PCT (0.81 [0.75-0.86]), (P < .05). None of the biomarkers tested was able to detect hepatic failure. Conclusions: In patients with infection, MR-proADM was the biomarker detecting the largest number of SOFA score components, with the exception of hepatic failure.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.titleMR‐ proADM to detect specific types of organ failure in infectiones
dc.typeinfo:eu-repo/semantics/articlees
dc.identifier.doi10.1111/eci.13246es
dc.identifier.publicationissue6es
dc.identifier.publicationtitleEuropean Journal of Clinical Investigationes
dc.identifier.publicationvolume50es
dc.peerreviewedSIes
dc.identifier.essn1365-2362es
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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