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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

BACKGROUND: The 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...

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Autores principales: Staessen, Jan A, Wendt, Ralph, Yu, Yu-Ling, Kalbitz, Sven, Thijs, Lutgarde, Siwy, Justyna, Raad, Julia, Metzger, Jochen, Neuhaus, Barbara, Papkalla, Armin, von der Leyen, Heiko, Mebazaa, Alexandre, Dudoignon, Emmanuel, Spasovski, Goce, Milenkova, Mimoza, Canevska-Taneska, Aleksandra, Salgueira Lazo, Mercedes, Psichogiou, Mina, Rajzer, Marek W, Fuławka, Łukasz, Dzitkowska-Zabielska, Magdalena, Weiss, Guenter, Feldt, Torsten, Stegemann, Miriam, Normark, Johan, Zoufaly, Alexander, Schmiedel, Stefan, Seilmaier, Michael, Rumpf, Benedikt, Banasik, Mirosław, Krajewska, Magdalena, Catanese, Lorenzo, Rupprecht, Harald D, Czerwieńska, Beata, Peters, Björn, Nilsson, Åsa, Rothfuss, Katja, Lübbert, Christoph, Mischak, Harald, Beige, Joachim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier Ltd. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9432869/
https://www.ncbi.nlm.nih.gov/pubmed/36057526
http://dx.doi.org/10.1016/S2589-7500(22)00150-9
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author Staessen, Jan A
Wendt, Ralph
Yu, Yu-Ling
Kalbitz, Sven
Thijs, Lutgarde
Siwy, Justyna
Raad, Julia
Metzger, Jochen
Neuhaus, Barbara
Papkalla, Armin
von der Leyen, Heiko
Mebazaa, Alexandre
Dudoignon, Emmanuel
Spasovski, Goce
Milenkova, Mimoza
Canevska-Taneska, Aleksandra
Salgueira Lazo, Mercedes
Psichogiou, Mina
Rajzer, Marek W
Fuławka, Łukasz
Dzitkowska-Zabielska, Magdalena
Weiss, Guenter
Feldt, Torsten
Stegemann, Miriam
Normark, Johan
Zoufaly, Alexander
Schmiedel, Stefan
Seilmaier, Michael
Rumpf, Benedikt
Banasik, Mirosław
Krajewska, Magdalena
Catanese, Lorenzo
Rupprecht, Harald D
Czerwieńska, Beata
Peters, Björn
Nilsson, Åsa
Rothfuss, Katja
Lübbert, Christoph
Mischak, Harald
Beige, Joachim
author_facet Staessen, Jan A
Wendt, Ralph
Yu, Yu-Ling
Kalbitz, Sven
Thijs, Lutgarde
Siwy, Justyna
Raad, Julia
Metzger, Jochen
Neuhaus, Barbara
Papkalla, Armin
von der Leyen, Heiko
Mebazaa, Alexandre
Dudoignon, Emmanuel
Spasovski, Goce
Milenkova, Mimoza
Canevska-Taneska, Aleksandra
Salgueira Lazo, Mercedes
Psichogiou, Mina
Rajzer, Marek W
Fuławka, Łukasz
Dzitkowska-Zabielska, Magdalena
Weiss, Guenter
Feldt, Torsten
Stegemann, Miriam
Normark, Johan
Zoufaly, Alexander
Schmiedel, Stefan
Seilmaier, Michael
Rumpf, Benedikt
Banasik, Mirosław
Krajewska, Magdalena
Catanese, Lorenzo
Rupprecht, Harald D
Czerwieńska, Beata
Peters, Björn
Nilsson, Åsa
Rothfuss, Katja
Lübbert, Christoph
Mischak, Harald
Beige, Joachim
author_sort Staessen, Jan A
collection PubMed
description BACKGROUND: The 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. METHODS: 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. FINDINGS: 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<0·0001 for all). The predictive accuracy of the optimised COV50 thresholds was 74·4% (71·6–77·1%) for mortality (threshold 0·47) and 67·4% (64·4–70·3%) for disease progression (threshold 0·04). When adjusted for covariables and the baseline WHO score, these thresholds improved AUCs from 0·835 to 0·853 (p=0·033) for death and from 0·697 to 0·730 (p=0·0008) for progression. Of 196 participants who received ambulatory care, 194 (99%) did not reach the 0·04 threshold. The cost reductions associated with 1 day less hospitalisation per 1000 participants were million Euro (M€) 0·887 (5–95% percentile interval 0·730–1·039) in participants at a low risk (COV50 <0·04) and M€2·098 (1·839-2·365) in participants at a high risk (COV50 ≥0·04). INTERPRETATION: 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. FUNDING: German Federal Ministry of Health.
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spelling pubmed-94328692022-09-01 Predictive performance and clinical application of COV50, a urinary proteomic biomarker in early COVID-19 infection: a prospective multicentre cohort study Staessen, Jan A Wendt, Ralph Yu, Yu-Ling Kalbitz, Sven Thijs, Lutgarde Siwy, Justyna Raad, Julia Metzger, Jochen Neuhaus, Barbara Papkalla, Armin von der Leyen, Heiko Mebazaa, Alexandre Dudoignon, Emmanuel Spasovski, Goce Milenkova, Mimoza Canevska-Taneska, Aleksandra Salgueira Lazo, Mercedes Psichogiou, Mina Rajzer, Marek W Fuławka, Łukasz Dzitkowska-Zabielska, Magdalena Weiss, Guenter Feldt, Torsten Stegemann, Miriam Normark, Johan Zoufaly, Alexander Schmiedel, Stefan Seilmaier, Michael Rumpf, Benedikt Banasik, Mirosław Krajewska, Magdalena Catanese, Lorenzo Rupprecht, Harald D Czerwieńska, Beata Peters, Björn Nilsson, Åsa Rothfuss, Katja Lübbert, Christoph Mischak, Harald Beige, Joachim Lancet Digit Health Articles BACKGROUND: The 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. METHODS: 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. FINDINGS: 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<0·0001 for all). The predictive accuracy of the optimised COV50 thresholds was 74·4% (71·6–77·1%) for mortality (threshold 0·47) and 67·4% (64·4–70·3%) for disease progression (threshold 0·04). When adjusted for covariables and the baseline WHO score, these thresholds improved AUCs from 0·835 to 0·853 (p=0·033) for death and from 0·697 to 0·730 (p=0·0008) for progression. Of 196 participants who received ambulatory care, 194 (99%) did not reach the 0·04 threshold. The cost reductions associated with 1 day less hospitalisation per 1000 participants were million Euro (M€) 0·887 (5–95% percentile interval 0·730–1·039) in participants at a low risk (COV50 <0·04) and M€2·098 (1·839-2·365) in participants at a high risk (COV50 ≥0·04). INTERPRETATION: 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. FUNDING: German Federal Ministry of Health. The Author(s). Published by Elsevier Ltd. 2022-10 2022-08-31 /pmc/articles/PMC9432869/ /pubmed/36057526 http://dx.doi.org/10.1016/S2589-7500(22)00150-9 Text en © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Articles
Staessen, Jan A
Wendt, Ralph
Yu, Yu-Ling
Kalbitz, Sven
Thijs, Lutgarde
Siwy, Justyna
Raad, Julia
Metzger, Jochen
Neuhaus, Barbara
Papkalla, Armin
von der Leyen, Heiko
Mebazaa, Alexandre
Dudoignon, Emmanuel
Spasovski, Goce
Milenkova, Mimoza
Canevska-Taneska, Aleksandra
Salgueira Lazo, Mercedes
Psichogiou, Mina
Rajzer, Marek W
Fuławka, Łukasz
Dzitkowska-Zabielska, Magdalena
Weiss, Guenter
Feldt, Torsten
Stegemann, Miriam
Normark, Johan
Zoufaly, Alexander
Schmiedel, Stefan
Seilmaier, Michael
Rumpf, Benedikt
Banasik, Mirosław
Krajewska, Magdalena
Catanese, Lorenzo
Rupprecht, Harald D
Czerwieńska, Beata
Peters, Björn
Nilsson, Åsa
Rothfuss, Katja
Lübbert, Christoph
Mischak, Harald
Beige, Joachim
Predictive performance and clinical application of COV50, a urinary proteomic biomarker in early COVID-19 infection: a prospective multicentre cohort study
title Predictive performance and clinical application of COV50, a urinary proteomic biomarker in early COVID-19 infection: a prospective multicentre cohort study
title_full Predictive performance and clinical application of COV50, a urinary proteomic biomarker in early COVID-19 infection: a prospective multicentre cohort study
title_fullStr Predictive performance and clinical application of COV50, a urinary proteomic biomarker in early COVID-19 infection: a prospective multicentre cohort study
title_full_unstemmed Predictive performance and clinical application of COV50, a urinary proteomic biomarker in early COVID-19 infection: a prospective multicentre cohort study
title_short Predictive performance and clinical application of COV50, a urinary proteomic biomarker in early COVID-19 infection: a prospective multicentre cohort study
title_sort predictive performance and clinical application of cov50, a urinary proteomic biomarker in early covid-19 infection: a prospective multicentre cohort study
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9432869/
https://www.ncbi.nlm.nih.gov/pubmed/36057526
http://dx.doi.org/10.1016/S2589-7500(22)00150-9
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