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Predictive performance and clinical application of COV50, a urinary proteomic biomarker in early COVID-19 infection: a prospective multicentre cohort study.

dc.contributor.authorStaessen, Jan A
dc.contributor.authorWendt, Ralph
dc.contributor.authorYu, Yu-Ling
dc.contributor.authorKalbitz, Sven
dc.contributor.authorThijs, Lutgarde
dc.contributor.authorSiwy, Justyna
dc.contributor.authorRaad, Julia
dc.contributor.authorMetzger, Jochen
dc.contributor.authorNeuhaus, Barbara
dc.contributor.authorPapkalla, Armin
dc.contributor.authorvon der Leyen, Heiko
dc.contributor.authorMebazaa, Alexandre
dc.contributor.authorDudoignon, Emmanuel
dc.contributor.authorSpasovski, Goce
dc.contributor.authorMilenkova, Mimoza
dc.contributor.authorCanevska-Taneska, Aleksandra
dc.contributor.authorSalgueira Lazo, Mercedes
dc.contributor.authorPsichogiou, Mina
dc.contributor.authorRajzer, Marek W
dc.contributor.authorFuławka, Łukasz
dc.contributor.authorDzitkowska-Zabielska, Magdalena
dc.contributor.authorWeiss, Guenter
dc.contributor.authorFeldt, Torsten
dc.contributor.authorStegemann, Miriam
dc.contributor.authorNormark, Johan
dc.contributor.authorZoufaly, Alexander
dc.contributor.authorSchmiedel, Stefan
dc.contributor.authorSeilmaier, Michael
dc.contributor.authorRumpf, Benedikt
dc.contributor.authorBanasik, Mirosław
dc.contributor.authorKrajewska, Magdalena
dc.contributor.authorCatanese, Lorenzo
dc.contributor.authorRupprecht, Harald D
dc.contributor.authorCzerwieńska, Beata
dc.contributor.authorPeters, Björn
dc.contributor.authorNilsson, Åsa
dc.contributor.authorRothfuss, Katja
dc.contributor.authorLübbert, Christoph
dc.contributor.authorMischak, Harald
dc.contributor.authorBeige, Joachim
dc.contributor.authorCRIT-CoV-U investigators
dc.date.accessioned2023-05-03T15:20:59Z
dc.date.available2023-05-03T15:20:59Z
dc.date.issued2022-08-31
dc.description.abstractThe SARS-CoV-2 pandemic is a worldwide challenge. The CRIT-CoV-U pilot study generated a urinary proteomic biomarker consisting of 50 peptides (COV50), which predicted death and disease progression from SARS-CoV-2. After the interim analysis presented for the German Government, here, we aimed to analyse the full dataset to consolidate the findings and propose potential clinical applications of this biomarker. CRIT-CoV-U was a prospective multicentre cohort study. In eight European countries (Austria, France, Germany, Greece, North Macedonia, Poland, Spain, and Sweden), 1012 adults with PCR-confirmed COVID-19 were followed up for death and progression along the 8-point WHO scale. Capillary electrophoresis coupled with mass spectrometry was used for urinary proteomic profiling. Statistical methods included logistic regression and receiver operating characteristic curve analysis with a comparison of the area under curve (AUC) between nested models. Hospitalisation costs were derived from the care facility corresponding with the Markov chain probability of reaching WHO scores ranging from 3 to 8 and flat-rate hospitalisation costs adjusted for the gross per capita domestic product of each country. From June 30 to Nov 19, 2020, 228 participants were recruited, and from April 30, 2020, to April 14, 2021, 784 participants were recruited, resulting in a total of 1012 participants. The entry WHO scores were 1-3 in 445 (44%) participants, 4-5 in 529 (52%) participants, and 6 in 38 (4%) participants; and of all participants, 119 died and 271 had disease progression. The odds ratio (OR) associated with COV50 in all 1012 participants for death was 2·44 (95% CI 2·05-2·92) unadjusted and 1·67 (1·34-2·07) when adjusted for sex, age, BMI, comorbidities, and baseline WHO score; and for disease progression, the OR was 1·79 (1·60-2·01) when unadjusted and 1·63 (1·41-1·91) when adjusted (p The urinary proteomic COV50 marker might be predictive of adverse COVID-19 outcomes. Even in people with mild-to-moderate PCR-confirmed infections (WHO scores 1-4), the 0·04 COV50 threshold justifies earlier drug treatment, thereby potentially reducing the number of days in hospital and associated costs. German Federal Ministry of Health.
dc.identifier.doi10.1016/S2589-7500(22)00150-9
dc.identifier.essn2589-7500
dc.identifier.pmcPMC9432869
dc.identifier.pmid36057526
dc.identifier.pubmedURLhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9432869/pdf
dc.identifier.unpaywallURLhttps://doi.org/10.1016/s2589-7500(22)00150-9
dc.identifier.urihttp://hdl.handle.net/10668/22564
dc.issue.number10
dc.journal.titleThe Lancet. Digital health
dc.journal.titleabbreviationLancet Digit Health
dc.language.isoen
dc.organizationHospital Universitario Virgen Macarena
dc.page.numbere727-e737
dc.pubmedtypeJournal Article
dc.pubmedtypeMulticenter Study
dc.pubmedtypeResearch Support, Non-U.S. Gov't
dc.rightsAttribution 4.0 International
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subject.meshAdult
dc.subject.meshBiomarkers
dc.subject.meshCOVID-19
dc.subject.meshCohort Studies
dc.subject.meshDisease Progression
dc.subject.meshHumans
dc.subject.meshPilot Projects
dc.subject.meshProspective Studies
dc.subject.meshProteomics
dc.subject.meshSARS-CoV-2
dc.titlePredictive performance and clinical application of COV50, a urinary proteomic biomarker in early COVID-19 infection: a prospective multicentre cohort study.
dc.typeresearch article
dc.type.hasVersionVoR
dc.volume.number4
dspace.entity.typePublication

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