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Criteria and potential predictors of severity in patients with COVID-19

BACKGROUND: The challenge in treating severe COVID-19 in the absence of targeted medication is enforcing physicians to search carefully for clinical predictors of severity. AIM: To define the profile of patients at risk of severe COVID-19 and to assess for certain predictors. METHODS: Confirmed COVI...

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Autores principales: Zayed, Niveen E., Abbas, Ahmad, Lutfy, Samah Mohamad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8857879/
http://dx.doi.org/10.1186/s43168-022-00116-y
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author Zayed, Niveen E.
Abbas, Ahmad
Lutfy, Samah Mohamad
author_facet Zayed, Niveen E.
Abbas, Ahmad
Lutfy, Samah Mohamad
author_sort Zayed, Niveen E.
collection PubMed
description BACKGROUND: The challenge in treating severe COVID-19 in the absence of targeted medication is enforcing physicians to search carefully for clinical predictors of severity. AIM: To define the profile of patients at risk of severe COVID-19 and to assess for certain predictors. METHODS: Confirmed COVID-19 cases were classified into the following: group A: mild/moderate cases and group B: severe/critical cases according to the selected criteria. History, radiological assessment, complete blood count, lactate dehydrogenase (LDH), myocardial enzymes, serum ferritin, and D dimer were assessed. Patients were followed for the need of ICU and mechanical ventilation. Duration till conversion, length of stay, and mortality were recorded. RESULTS: A total of 202 patients were analyzed. Group B had higher age (53.2 ± 12.6 vs 40.3 ± 10.3, P < 0.001), more prevalence of DM (60.61% vs 16.57% P < 0.001), hypertension (51.52% vs 20.12%, P < 0.001), ischemic heart (27.27% vs 3.55%, P < 0.001), bronchial asthma (36.36% vs 3.55%, P < 0.001), COPD (9.09% vs 1.18%, P = 0.03), higher mean platelet volume (MPV) (12.76 ± 7.13 vs 10.51 ± 7.78 (fL), P < 0.001), higher serum ferritin (954 ± 138 vs 447 ± 166 ng/ml, P < 0.001), higher LDH (604 ± 220 vs 384 ± 183 U/L, P-value < 0.001), higher creatine phosphokinase (24.27 ± 5.82 vs 16.4 ± 4.87 IU/L, P < 0.001), and higher mortality (30.3% vs 0.6%, P < 0.001). Multivariate regression of predictors of severity identified three predictors; age, MPV, serum ferritin, and IHD. CONCLUSIONS: The current study places of interest the characteristic host-related features of severe COVID-19 and draws attention to potential predictors.
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spelling pubmed-88578792022-02-22 Criteria and potential predictors of severity in patients with COVID-19 Zayed, Niveen E. Abbas, Ahmad Lutfy, Samah Mohamad Egypt J Bronchol Research BACKGROUND: The challenge in treating severe COVID-19 in the absence of targeted medication is enforcing physicians to search carefully for clinical predictors of severity. AIM: To define the profile of patients at risk of severe COVID-19 and to assess for certain predictors. METHODS: Confirmed COVID-19 cases were classified into the following: group A: mild/moderate cases and group B: severe/critical cases according to the selected criteria. History, radiological assessment, complete blood count, lactate dehydrogenase (LDH), myocardial enzymes, serum ferritin, and D dimer were assessed. Patients were followed for the need of ICU and mechanical ventilation. Duration till conversion, length of stay, and mortality were recorded. RESULTS: A total of 202 patients were analyzed. Group B had higher age (53.2 ± 12.6 vs 40.3 ± 10.3, P < 0.001), more prevalence of DM (60.61% vs 16.57% P < 0.001), hypertension (51.52% vs 20.12%, P < 0.001), ischemic heart (27.27% vs 3.55%, P < 0.001), bronchial asthma (36.36% vs 3.55%, P < 0.001), COPD (9.09% vs 1.18%, P = 0.03), higher mean platelet volume (MPV) (12.76 ± 7.13 vs 10.51 ± 7.78 (fL), P < 0.001), higher serum ferritin (954 ± 138 vs 447 ± 166 ng/ml, P < 0.001), higher LDH (604 ± 220 vs 384 ± 183 U/L, P-value < 0.001), higher creatine phosphokinase (24.27 ± 5.82 vs 16.4 ± 4.87 IU/L, P < 0.001), and higher mortality (30.3% vs 0.6%, P < 0.001). Multivariate regression of predictors of severity identified three predictors; age, MPV, serum ferritin, and IHD. CONCLUSIONS: The current study places of interest the characteristic host-related features of severe COVID-19 and draws attention to potential predictors. Springer Berlin Heidelberg 2022-02-19 2022 /pmc/articles/PMC8857879/ http://dx.doi.org/10.1186/s43168-022-00116-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Research
Zayed, Niveen E.
Abbas, Ahmad
Lutfy, Samah Mohamad
Criteria and potential predictors of severity in patients with COVID-19
title Criteria and potential predictors of severity in patients with COVID-19
title_full Criteria and potential predictors of severity in patients with COVID-19
title_fullStr Criteria and potential predictors of severity in patients with COVID-19
title_full_unstemmed Criteria and potential predictors of severity in patients with COVID-19
title_short Criteria and potential predictors of severity in patients with COVID-19
title_sort criteria and potential predictors of severity in patients with covid-19
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8857879/
http://dx.doi.org/10.1186/s43168-022-00116-y
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