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Clinical risk score to predict in-hospital mortality in COVID-19 patients: a retrospective cohort study
OBJECTIVES: Several physiological abnormalities that develop during COVID-19 are associated with increased mortality. In the present study, we aimed to develop a clinical risk score to predict the in-hospital mortality in COVID-19 patients, based on a set of variables available soon after the hospit...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7520809/ https://www.ncbi.nlm.nih.gov/pubmed/32978207 http://dx.doi.org/10.1136/bmjopen-2020-040729 |
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author | Fumagalli, Carlo Rozzini, Renzo Vannini, Matteo Coccia, Flaminia Cesaroni, Giulia Mazzeo, Francesca Cola, Maria Bartoloni, Alessandro Fontanari, Paolo Lavorini, Federico Marcucci, Rossella Morettini, Alessandro Nozzoli, Carlo Peris, Adriano Pieralli, Filippo Pini, Riccardo Poggesi, Loredana Ungar, Andrea Fumagalli, Stefano Marchionni, Niccolò |
author_facet | Fumagalli, Carlo Rozzini, Renzo Vannini, Matteo Coccia, Flaminia Cesaroni, Giulia Mazzeo, Francesca Cola, Maria Bartoloni, Alessandro Fontanari, Paolo Lavorini, Federico Marcucci, Rossella Morettini, Alessandro Nozzoli, Carlo Peris, Adriano Pieralli, Filippo Pini, Riccardo Poggesi, Loredana Ungar, Andrea Fumagalli, Stefano Marchionni, Niccolò |
author_sort | Fumagalli, Carlo |
collection | PubMed |
description | OBJECTIVES: Several physiological abnormalities that develop during COVID-19 are associated with increased mortality. In the present study, we aimed to develop a clinical risk score to predict the in-hospital mortality in COVID-19 patients, based on a set of variables available soon after the hospitalisation triage. SETTING: Retrospective cohort study of 516 patients consecutively admitted for COVID-19 to two Italian tertiary hospitals located in Northern and Central Italy were collected from 22 February 2020 (date of first admission) to 10 April 2020. PARTICIPANTS: Consecutive patients≥18 years admitted for COVID-19. MAIN OUTCOME MEASURES: Simple clinical and laboratory findings readily available after triage were compared by patients’ survival status (‘dead’ vs ‘alive’), with the objective of identifying baseline variables associated with mortality. These were used to build a COVID-19 in-hospital mortality risk score (COVID-19MRS). RESULTS: Mean age was 67±13 years (mean±SD), and 66.9% were male. Using Cox regression analysis, tertiles of increasing age (≥75, upper vs <62 years, lower: HR 7.92; p<0.001) and number of chronic diseases (≥4 vs 0–1: HR 2.09; p=0.007), respiratory rate (HR 1.04 per unit increase; p=0.001), PaO(2)/FiO(2) (HR 0.995 per unit increase; p<0.001), serum creatinine (HR 1.34 per unit increase; p<0.001) and platelet count (HR 0.995 per unit increase; p=0.001) were predictors of mortality. All six predictors were used to build the COVID-19MRS (Area Under the Curve 0.90, 95% CI 0.87 to 0.93), which proved to be highly accurate in stratifying patients at low, intermediate and high risk of in-hospital death (p<0.001). CONCLUSIONS: The COVID-19MRS is a rapid, operator-independent and inexpensive clinical tool that objectively predicts mortality in patients with COVID-19. The score could be helpful from triage to guide earlier assignment of COVID-19 patients to the most appropriate level of care. |
format | Online Article Text |
id | pubmed-7520809 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-75208092020-09-28 Clinical risk score to predict in-hospital mortality in COVID-19 patients: a retrospective cohort study Fumagalli, Carlo Rozzini, Renzo Vannini, Matteo Coccia, Flaminia Cesaroni, Giulia Mazzeo, Francesca Cola, Maria Bartoloni, Alessandro Fontanari, Paolo Lavorini, Federico Marcucci, Rossella Morettini, Alessandro Nozzoli, Carlo Peris, Adriano Pieralli, Filippo Pini, Riccardo Poggesi, Loredana Ungar, Andrea Fumagalli, Stefano Marchionni, Niccolò BMJ Open Medical Management OBJECTIVES: Several physiological abnormalities that develop during COVID-19 are associated with increased mortality. In the present study, we aimed to develop a clinical risk score to predict the in-hospital mortality in COVID-19 patients, based on a set of variables available soon after the hospitalisation triage. SETTING: Retrospective cohort study of 516 patients consecutively admitted for COVID-19 to two Italian tertiary hospitals located in Northern and Central Italy were collected from 22 February 2020 (date of first admission) to 10 April 2020. PARTICIPANTS: Consecutive patients≥18 years admitted for COVID-19. MAIN OUTCOME MEASURES: Simple clinical and laboratory findings readily available after triage were compared by patients’ survival status (‘dead’ vs ‘alive’), with the objective of identifying baseline variables associated with mortality. These were used to build a COVID-19 in-hospital mortality risk score (COVID-19MRS). RESULTS: Mean age was 67±13 years (mean±SD), and 66.9% were male. Using Cox regression analysis, tertiles of increasing age (≥75, upper vs <62 years, lower: HR 7.92; p<0.001) and number of chronic diseases (≥4 vs 0–1: HR 2.09; p=0.007), respiratory rate (HR 1.04 per unit increase; p=0.001), PaO(2)/FiO(2) (HR 0.995 per unit increase; p<0.001), serum creatinine (HR 1.34 per unit increase; p<0.001) and platelet count (HR 0.995 per unit increase; p=0.001) were predictors of mortality. All six predictors were used to build the COVID-19MRS (Area Under the Curve 0.90, 95% CI 0.87 to 0.93), which proved to be highly accurate in stratifying patients at low, intermediate and high risk of in-hospital death (p<0.001). CONCLUSIONS: The COVID-19MRS is a rapid, operator-independent and inexpensive clinical tool that objectively predicts mortality in patients with COVID-19. The score could be helpful from triage to guide earlier assignment of COVID-19 patients to the most appropriate level of care. BMJ Publishing Group 2020-09-25 /pmc/articles/PMC7520809/ /pubmed/32978207 http://dx.doi.org/10.1136/bmjopen-2020-040729 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Medical Management Fumagalli, Carlo Rozzini, Renzo Vannini, Matteo Coccia, Flaminia Cesaroni, Giulia Mazzeo, Francesca Cola, Maria Bartoloni, Alessandro Fontanari, Paolo Lavorini, Federico Marcucci, Rossella Morettini, Alessandro Nozzoli, Carlo Peris, Adriano Pieralli, Filippo Pini, Riccardo Poggesi, Loredana Ungar, Andrea Fumagalli, Stefano Marchionni, Niccolò Clinical risk score to predict in-hospital mortality in COVID-19 patients: a retrospective cohort study |
title | Clinical risk score to predict in-hospital mortality in COVID-19 patients: a retrospective cohort study |
title_full | Clinical risk score to predict in-hospital mortality in COVID-19 patients: a retrospective cohort study |
title_fullStr | Clinical risk score to predict in-hospital mortality in COVID-19 patients: a retrospective cohort study |
title_full_unstemmed | Clinical risk score to predict in-hospital mortality in COVID-19 patients: a retrospective cohort study |
title_short | Clinical risk score to predict in-hospital mortality in COVID-19 patients: a retrospective cohort study |
title_sort | clinical risk score to predict in-hospital mortality in covid-19 patients: a retrospective cohort study |
topic | Medical Management |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7520809/ https://www.ncbi.nlm.nih.gov/pubmed/32978207 http://dx.doi.org/10.1136/bmjopen-2020-040729 |
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