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The COVID-19 lab score: an accurate dynamic tool to predict in-hospital outcomes in COVID-19 patients

Deterioration is sometimes unexpected in SARS-CoV2 infection. The aim of our study is to establish laboratory predictors of mortality in COVID-19 disease which can help to identify high risk patients. All patients admitted to hospital due to Covid-19 disease were included. Laboratory biomarkers that...

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Autores principales: Antunez Muiños, Pablo Jose, López Otero, Diego, Amat-Santos, Ignacio J., López País, Javier, Aparisi, Alvaro, Cacho Antonio, Carla E., Catalá, Pablo, González Ferrero, Teba, Cabezón, Gonzalo, Otero García, Oscar, Gil, José Francisco, Pérez Poza, Marta, Candela, Jordi, Rojas, Gino, Jiménez Ramos, Víctor, Veras, Carlos, San Román, J. Alberto, González-Juanatey, José R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8087839/
https://www.ncbi.nlm.nih.gov/pubmed/33931677
http://dx.doi.org/10.1038/s41598-021-88679-6
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author Antunez Muiños, Pablo Jose
López Otero, Diego
Amat-Santos, Ignacio J.
López País, Javier
Aparisi, Alvaro
Cacho Antonio, Carla E.
Catalá, Pablo
González Ferrero, Teba
Cabezón, Gonzalo
Otero García, Oscar
Gil, José Francisco
Pérez Poza, Marta
Candela, Jordi
Rojas, Gino
Jiménez Ramos, Víctor
Veras, Carlos
San Román, J. Alberto
González-Juanatey, José R.
author_facet Antunez Muiños, Pablo Jose
López Otero, Diego
Amat-Santos, Ignacio J.
López País, Javier
Aparisi, Alvaro
Cacho Antonio, Carla E.
Catalá, Pablo
González Ferrero, Teba
Cabezón, Gonzalo
Otero García, Oscar
Gil, José Francisco
Pérez Poza, Marta
Candela, Jordi
Rojas, Gino
Jiménez Ramos, Víctor
Veras, Carlos
San Román, J. Alberto
González-Juanatey, José R.
author_sort Antunez Muiños, Pablo Jose
collection PubMed
description Deterioration is sometimes unexpected in SARS-CoV2 infection. The aim of our study is to establish laboratory predictors of mortality in COVID-19 disease which can help to identify high risk patients. All patients admitted to hospital due to Covid-19 disease were included. Laboratory biomarkers that contributed with significant predictive value for predicting mortality to the clinical model were included. Cut-off points were established, and finally a risk score was built. 893 patients were included. Median age was 68.2 ± 15.2 years. 87(9.7%) were admitted to Intensive Care Unit (ICU) and 72(8.1%) needed mechanical ventilation support. 171(19.1%) patients died. A Covid-19 Lab score ranging from 0 to 30 points was calculated on the basis of a multivariate logistic regression model in order to predict mortality with a weighted score that included haemoglobin, erythrocytes, leukocytes, neutrophils, lymphocytes, creatinine, C-reactive protein, interleukin-6, procalcitonin, lactate dehydrogenase (LDH), and D-dimer. Three groups were established. Low mortality risk group under 12 points, 12 to 18 were included as moderate risk, and high risk group were those with 19 or more points. Low risk group as reference, moderate and high patients showed mortality OR 4.75(CI95% 2.60–8.68) and 23.86(CI 95% 13.61–41.84), respectively. C-statistic was 0–85(0.82–0.88) and Hosmer–Lemeshow p-value 0.63. Covid-19 Lab score can very easily predict mortality in patients at any moment during admission secondary to SARS-CoV2 infection. It is a simple and dynamic score, and it can be very easily replicated. It could help physicians to identify high risk patients to foresee clinical deterioration.
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spelling pubmed-80878392021-05-03 The COVID-19 lab score: an accurate dynamic tool to predict in-hospital outcomes in COVID-19 patients Antunez Muiños, Pablo Jose López Otero, Diego Amat-Santos, Ignacio J. López País, Javier Aparisi, Alvaro Cacho Antonio, Carla E. Catalá, Pablo González Ferrero, Teba Cabezón, Gonzalo Otero García, Oscar Gil, José Francisco Pérez Poza, Marta Candela, Jordi Rojas, Gino Jiménez Ramos, Víctor Veras, Carlos San Román, J. Alberto González-Juanatey, José R. Sci Rep Article Deterioration is sometimes unexpected in SARS-CoV2 infection. The aim of our study is to establish laboratory predictors of mortality in COVID-19 disease which can help to identify high risk patients. All patients admitted to hospital due to Covid-19 disease were included. Laboratory biomarkers that contributed with significant predictive value for predicting mortality to the clinical model were included. Cut-off points were established, and finally a risk score was built. 893 patients were included. Median age was 68.2 ± 15.2 years. 87(9.7%) were admitted to Intensive Care Unit (ICU) and 72(8.1%) needed mechanical ventilation support. 171(19.1%) patients died. A Covid-19 Lab score ranging from 0 to 30 points was calculated on the basis of a multivariate logistic regression model in order to predict mortality with a weighted score that included haemoglobin, erythrocytes, leukocytes, neutrophils, lymphocytes, creatinine, C-reactive protein, interleukin-6, procalcitonin, lactate dehydrogenase (LDH), and D-dimer. Three groups were established. Low mortality risk group under 12 points, 12 to 18 were included as moderate risk, and high risk group were those with 19 or more points. Low risk group as reference, moderate and high patients showed mortality OR 4.75(CI95% 2.60–8.68) and 23.86(CI 95% 13.61–41.84), respectively. C-statistic was 0–85(0.82–0.88) and Hosmer–Lemeshow p-value 0.63. Covid-19 Lab score can very easily predict mortality in patients at any moment during admission secondary to SARS-CoV2 infection. It is a simple and dynamic score, and it can be very easily replicated. It could help physicians to identify high risk patients to foresee clinical deterioration. Nature Publishing Group UK 2021-04-30 /pmc/articles/PMC8087839/ /pubmed/33931677 http://dx.doi.org/10.1038/s41598-021-88679-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Antunez Muiños, Pablo Jose
López Otero, Diego
Amat-Santos, Ignacio J.
López País, Javier
Aparisi, Alvaro
Cacho Antonio, Carla E.
Catalá, Pablo
González Ferrero, Teba
Cabezón, Gonzalo
Otero García, Oscar
Gil, José Francisco
Pérez Poza, Marta
Candela, Jordi
Rojas, Gino
Jiménez Ramos, Víctor
Veras, Carlos
San Román, J. Alberto
González-Juanatey, José R.
The COVID-19 lab score: an accurate dynamic tool to predict in-hospital outcomes in COVID-19 patients
title The COVID-19 lab score: an accurate dynamic tool to predict in-hospital outcomes in COVID-19 patients
title_full The COVID-19 lab score: an accurate dynamic tool to predict in-hospital outcomes in COVID-19 patients
title_fullStr The COVID-19 lab score: an accurate dynamic tool to predict in-hospital outcomes in COVID-19 patients
title_full_unstemmed The COVID-19 lab score: an accurate dynamic tool to predict in-hospital outcomes in COVID-19 patients
title_short The COVID-19 lab score: an accurate dynamic tool to predict in-hospital outcomes in COVID-19 patients
title_sort covid-19 lab score: an accurate dynamic tool to predict in-hospital outcomes in covid-19 patients
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8087839/
https://www.ncbi.nlm.nih.gov/pubmed/33931677
http://dx.doi.org/10.1038/s41598-021-88679-6
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