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Aspartate transferase-to-platelet ratio index-plus: A new simplified model for predicting the risk of mortality among patients with COVID-19
BACKGROUND: Coronavirus disease 2019 (COVID-19) has a spectrum of clinical syndromes with serious involvement of the lung and frequent effection of the liver and hemostatic system. Blood biomarkers are affordable, rapid, objective, and useful in the evaluation and prognostication of COVID-19 patient...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9048783/ https://www.ncbi.nlm.nih.gov/pubmed/35581967 http://dx.doi.org/10.3748/wjg.v28.i16.1671 |
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author | Madian, Ali Eliwa, Ahmed Abdalla, Hytham A Azeem Aly, Haitham |
author_facet | Madian, Ali Eliwa, Ahmed Abdalla, Hytham A Azeem Aly, Haitham |
author_sort | Madian, Ali |
collection | PubMed |
description | BACKGROUND: Coronavirus disease 2019 (COVID-19) has a spectrum of clinical syndromes with serious involvement of the lung and frequent effection of the liver and hemostatic system. Blood biomarkers are affordable, rapid, objective, and useful in the evaluation and prognostication of COVID-19 patients. AIM: To investigate the association between aspartate transferase-to-platelet ratio index (APRI) and in-hospital mortality to develop a COVID-19 mortality prediction model. METHODS: A multicenter cohort study with a retrospective design was conducted. Medical records of all consecutive adult patients admitted to Al-Azhar University Hospital (Assiut, Egypt) and Chest Hospital (Assiut, Egypt) with confirmed COVID-19 from July 1, 2020 to October 1, 2020, were retrieved and analyzed. The patient cohort was classified into the following two categories based on the APRI: (1) COVID-19 presenting with APRI ≤ 0.5; and (2) COVID-19 presenting with APRI (> 0.5 and ≤ 1.5). The association between APRI and all-cause in-hospital mortality was analyzed, and the new model was developed through logistic regression analyses. RESULTS: Of the 353 patients who satisfied the inclusion criteria, 10% were admitted to the intensive care unit (n = 36) and 7% died during the hospital stay (n = 25). The median age was 40 years and 50.7% were male. On admission, 49% had aspartate transferase-dominant liver injury. On admission, APRI (> 0.5 and ≤ 1.5) was independently associated with all-cause in-hospital mortality in unadjusted regression analysis and after adjustment for age and sex; after stepwise adjustment for several clinically relevant confounders, APRI was still significantly associated with all-cause in-hospital mortality. On admission, APRI (> 0.5 and ≤ 1.5) increased the odds of mortality by five-times (P < 0.006). From these results, we developed a new predictive model, the APRI-plus, which includes the four predictors of age, aspartate transferase, platelets, and serum ferritin. Performance for mortality was very good, with an area under the receiver operating curve of 0.90. CONCLUSION: APRI-plus is an accurate and simplified prediction model for mortality among patients with COVID-19 and is associated with in-hospital mortality, independent of other relevant predictors. |
format | Online Article Text |
id | pubmed-9048783 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-90487832022-05-16 Aspartate transferase-to-platelet ratio index-plus: A new simplified model for predicting the risk of mortality among patients with COVID-19 Madian, Ali Eliwa, Ahmed Abdalla, Hytham A Azeem Aly, Haitham World J Gastroenterol Retrospective Cohort Study BACKGROUND: Coronavirus disease 2019 (COVID-19) has a spectrum of clinical syndromes with serious involvement of the lung and frequent effection of the liver and hemostatic system. Blood biomarkers are affordable, rapid, objective, and useful in the evaluation and prognostication of COVID-19 patients. AIM: To investigate the association between aspartate transferase-to-platelet ratio index (APRI) and in-hospital mortality to develop a COVID-19 mortality prediction model. METHODS: A multicenter cohort study with a retrospective design was conducted. Medical records of all consecutive adult patients admitted to Al-Azhar University Hospital (Assiut, Egypt) and Chest Hospital (Assiut, Egypt) with confirmed COVID-19 from July 1, 2020 to October 1, 2020, were retrieved and analyzed. The patient cohort was classified into the following two categories based on the APRI: (1) COVID-19 presenting with APRI ≤ 0.5; and (2) COVID-19 presenting with APRI (> 0.5 and ≤ 1.5). The association between APRI and all-cause in-hospital mortality was analyzed, and the new model was developed through logistic regression analyses. RESULTS: Of the 353 patients who satisfied the inclusion criteria, 10% were admitted to the intensive care unit (n = 36) and 7% died during the hospital stay (n = 25). The median age was 40 years and 50.7% were male. On admission, 49% had aspartate transferase-dominant liver injury. On admission, APRI (> 0.5 and ≤ 1.5) was independently associated with all-cause in-hospital mortality in unadjusted regression analysis and after adjustment for age and sex; after stepwise adjustment for several clinically relevant confounders, APRI was still significantly associated with all-cause in-hospital mortality. On admission, APRI (> 0.5 and ≤ 1.5) increased the odds of mortality by five-times (P < 0.006). From these results, we developed a new predictive model, the APRI-plus, which includes the four predictors of age, aspartate transferase, platelets, and serum ferritin. Performance for mortality was very good, with an area under the receiver operating curve of 0.90. CONCLUSION: APRI-plus is an accurate and simplified prediction model for mortality among patients with COVID-19 and is associated with in-hospital mortality, independent of other relevant predictors. Baishideng Publishing Group Inc 2022-04-28 2022-04-28 /pmc/articles/PMC9048783/ /pubmed/35581967 http://dx.doi.org/10.3748/wjg.v28.i16.1671 Text en ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (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 and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/ |
spellingShingle | Retrospective Cohort Study Madian, Ali Eliwa, Ahmed Abdalla, Hytham A Azeem Aly, Haitham Aspartate transferase-to-platelet ratio index-plus: A new simplified model for predicting the risk of mortality among patients with COVID-19 |
title | Aspartate transferase-to-platelet ratio index-plus: A new simplified model for predicting the risk of mortality among patients with COVID-19 |
title_full | Aspartate transferase-to-platelet ratio index-plus: A new simplified model for predicting the risk of mortality among patients with COVID-19 |
title_fullStr | Aspartate transferase-to-platelet ratio index-plus: A new simplified model for predicting the risk of mortality among patients with COVID-19 |
title_full_unstemmed | Aspartate transferase-to-platelet ratio index-plus: A new simplified model for predicting the risk of mortality among patients with COVID-19 |
title_short | Aspartate transferase-to-platelet ratio index-plus: A new simplified model for predicting the risk of mortality among patients with COVID-19 |
title_sort | aspartate transferase-to-platelet ratio index-plus: a new simplified model for predicting the risk of mortality among patients with covid-19 |
topic | Retrospective Cohort Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9048783/ https://www.ncbi.nlm.nih.gov/pubmed/35581967 http://dx.doi.org/10.3748/wjg.v28.i16.1671 |
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