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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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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. |
format | Online Article Text |
id | pubmed-10021136 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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