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Validation of MuLBSTA score to derive modified MuLB score as mortality risk prediction in COVID-19 infection

COVID-19pandemic was started in December 2019. It has variable presentation from mild sore throat to severe respiratory distress. It is important to identify individuals who are likely to worsen. The Research question is how to identify patients with COVID-19 who are at high risk and to predict pati...

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Autores principales: George, Richie, Mehta, Asmita A., Paul, Tisa, Sathyapalan, Dipu T., Haridas, Nithya, Kunoor, Akhilesh, Ravindran, Greeshma C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10021136/
https://www.ncbi.nlm.nih.gov/pubmed/36962449
http://dx.doi.org/10.1371/journal.pgph.0000511
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author George, Richie
Mehta, Asmita A.
Paul, Tisa
Sathyapalan, Dipu T.
Haridas, Nithya
Kunoor, Akhilesh
Ravindran, Greeshma C.
author_facet George, Richie
Mehta, Asmita A.
Paul, Tisa
Sathyapalan, Dipu T.
Haridas, Nithya
Kunoor, Akhilesh
Ravindran, Greeshma C.
author_sort George, Richie
collection PubMed
description COVID-19pandemic was started in December 2019. It has variable presentation from mild sore throat to severe respiratory distress. It is important to identify individuals who are likely to worsen. The Research question is how to identify patients with COVID-19 who are at high risk and to predict patient outcome based on a risk stratification model? We evaluated 251 patients with COVID-19 in this prospective inception study. We used a multi-variable Cox proportional hazards model to identify the independent prognostic risk factors and created a risk score model on the basis of available MuLBSTA score. The model was validated in an independent group of patients from October2020 to December 2021. We developed a combined risk score, the MuLBA score that included the following values and scores: Multi lobar infiltrates (negative0.254, 2), lymphopenia (lymphocytes of <0.8x10(9) /L, negative0.18,2), bacterial co- infection (negative, 0.306,3). In our MuLB scoring system, score of >8 was associated with high risk of mortality and <5 was at mild risk of mortality (P < 0.001). The interpretation was that The MuLB risk score model could help to predict survival in patients with severe COVID-19 infection and to guide further clinical research on risk-based treatment.
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spelling pubmed-100211362023-03-17 Validation of MuLBSTA score to derive modified MuLB score as mortality risk prediction in COVID-19 infection George, Richie Mehta, Asmita A. Paul, Tisa Sathyapalan, Dipu T. Haridas, Nithya Kunoor, Akhilesh Ravindran, Greeshma C. PLOS Glob Public Health Research Article COVID-19pandemic was started in December 2019. It has variable presentation from mild sore throat to severe respiratory distress. It is important to identify individuals who are likely to worsen. The Research question is how to identify patients with COVID-19 who are at high risk and to predict patient outcome based on a risk stratification model? We evaluated 251 patients with COVID-19 in this prospective inception study. We used a multi-variable Cox proportional hazards model to identify the independent prognostic risk factors and created a risk score model on the basis of available MuLBSTA score. The model was validated in an independent group of patients from October2020 to December 2021. We developed a combined risk score, the MuLBA score that included the following values and scores: Multi lobar infiltrates (negative0.254, 2), lymphopenia (lymphocytes of <0.8x10(9) /L, negative0.18,2), bacterial co- infection (negative, 0.306,3). In our MuLB scoring system, score of >8 was associated with high risk of mortality and <5 was at mild risk of mortality (P < 0.001). The interpretation was that The MuLB risk score model could help to predict survival in patients with severe COVID-19 infection and to guide further clinical research on risk-based treatment. Public Library of Science 2022-08-01 /pmc/articles/PMC10021136/ /pubmed/36962449 http://dx.doi.org/10.1371/journal.pgph.0000511 Text en © 2022 George et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
George, Richie
Mehta, Asmita A.
Paul, Tisa
Sathyapalan, Dipu T.
Haridas, Nithya
Kunoor, Akhilesh
Ravindran, Greeshma C.
Validation of MuLBSTA score to derive modified MuLB score as mortality risk prediction in COVID-19 infection
title Validation of MuLBSTA score to derive modified MuLB score as mortality risk prediction in COVID-19 infection
title_full Validation of MuLBSTA score to derive modified MuLB score as mortality risk prediction in COVID-19 infection
title_fullStr Validation of MuLBSTA score to derive modified MuLB score as mortality risk prediction in COVID-19 infection
title_full_unstemmed Validation of MuLBSTA score to derive modified MuLB score as mortality risk prediction in COVID-19 infection
title_short Validation of MuLBSTA score to derive modified MuLB score as mortality risk prediction in COVID-19 infection
title_sort validation of mulbsta score to derive modified mulb score as mortality risk prediction in covid-19 infection
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10021136/
https://www.ncbi.nlm.nih.gov/pubmed/36962449
http://dx.doi.org/10.1371/journal.pgph.0000511
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