Cargando…
Laboratory biomarkers of COVID-19 disease severity and outcome: Findings from a developing country
AIM: To identify laboratory biomarkers that predict disease severity and outcome among COVID-19 patients admitted to the Millennium COVID-19 Care Center in Ethiopia. METHODS: A retrospective cohort study was conducted among 429 COVID-19 patients who were on follow up from July to October 2020. Data...
Autores principales: | , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7959358/ https://www.ncbi.nlm.nih.gov/pubmed/33720944 http://dx.doi.org/10.1371/journal.pone.0246087 |
_version_ | 1783664953235865600 |
---|---|
author | Leulseged, Tigist W. Hassen, Ishmael S. Ayele, Birhanu T. Tsegay, Yakob G. Abebe, Daniel S. Edo, Mesay G. Maru, Endalkachew H. Zewde, Wuletaw C. Naylor, Lydia K. Semane, Dejene F. Dresse, Menayit T. Tezera, Bereket B. |
author_facet | Leulseged, Tigist W. Hassen, Ishmael S. Ayele, Birhanu T. Tsegay, Yakob G. Abebe, Daniel S. Edo, Mesay G. Maru, Endalkachew H. Zewde, Wuletaw C. Naylor, Lydia K. Semane, Dejene F. Dresse, Menayit T. Tezera, Bereket B. |
author_sort | Leulseged, Tigist W. |
collection | PubMed |
description | AIM: To identify laboratory biomarkers that predict disease severity and outcome among COVID-19 patients admitted to the Millennium COVID-19 Care Center in Ethiopia. METHODS: A retrospective cohort study was conducted among 429 COVID-19 patients who were on follow up from July to October 2020. Data was described using frequency tables. Robust Poisson regression model was used to identify predictors of COVID-19 severity where adjusted relative risk (ARR), P-value and 95 CI for ARR were used to test significance. Binary Logistic regression model was used to assess the presence of statistically significant association between the explanatory variables and COVID-19 outcome where adjusted odds ratio (AOR), P-value and 95%CI for AOR were used for testing significance. RESULTS: Among the 429 patients studied, 182 (42.4%) had Severe disease at admission and the rest 247 (57.6%) had Non-severe disease. Regarding disease outcome, 45 (10.5%) died and 384 (89.5%) were discharged alive. Age group (ARR = 1.779, 95%CI = 1.405–2.252, p-value <0.0001), Neutrophil to Lymphocyte ratio (NLR) (ARR = 4.769, 95%CI = 2.419–9.402 p-value <0.0001), Serum glutamic oxaloacetic transaminase (SGOT) (ARR = 1.358, 95%CI = 1.109–1.662 p-value = 0.003), Sodium (ARR = 1.321, 95%CI = 1.091–1.600 p-value = 0.004) and Potassium (ARR = 1.269, 95%CI = 1.059–1.521 p-value = 0.010) were found to be significant predictors of COVID-19 severity. The following factors were significantly associated with COVID-19 outcome; age group (AOR = 2.767, 95%CI = 1.099–6.067, p-value = 0.031), white blood cell count (WBC) (AOR = 4.253, 95%CI = 1.918–9.429, p-value = 0.0001) and sodium level (AOR = 3.435, 95%CI = 1.439–8.198, p-value = 0.005). CONCLUSIONS: Assessing and monitoring the laboratory markers of WBC, NLR, SGOT, sodium and potassium levels at the earliest stage of the disease could have a considerable role in halting disease progression and death. |
format | Online Article Text |
id | pubmed-7959358 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-79593582021-03-25 Laboratory biomarkers of COVID-19 disease severity and outcome: Findings from a developing country Leulseged, Tigist W. Hassen, Ishmael S. Ayele, Birhanu T. Tsegay, Yakob G. Abebe, Daniel S. Edo, Mesay G. Maru, Endalkachew H. Zewde, Wuletaw C. Naylor, Lydia K. Semane, Dejene F. Dresse, Menayit T. Tezera, Bereket B. PLoS One Research Article AIM: To identify laboratory biomarkers that predict disease severity and outcome among COVID-19 patients admitted to the Millennium COVID-19 Care Center in Ethiopia. METHODS: A retrospective cohort study was conducted among 429 COVID-19 patients who were on follow up from July to October 2020. Data was described using frequency tables. Robust Poisson regression model was used to identify predictors of COVID-19 severity where adjusted relative risk (ARR), P-value and 95 CI for ARR were used to test significance. Binary Logistic regression model was used to assess the presence of statistically significant association between the explanatory variables and COVID-19 outcome where adjusted odds ratio (AOR), P-value and 95%CI for AOR were used for testing significance. RESULTS: Among the 429 patients studied, 182 (42.4%) had Severe disease at admission and the rest 247 (57.6%) had Non-severe disease. Regarding disease outcome, 45 (10.5%) died and 384 (89.5%) were discharged alive. Age group (ARR = 1.779, 95%CI = 1.405–2.252, p-value <0.0001), Neutrophil to Lymphocyte ratio (NLR) (ARR = 4.769, 95%CI = 2.419–9.402 p-value <0.0001), Serum glutamic oxaloacetic transaminase (SGOT) (ARR = 1.358, 95%CI = 1.109–1.662 p-value = 0.003), Sodium (ARR = 1.321, 95%CI = 1.091–1.600 p-value = 0.004) and Potassium (ARR = 1.269, 95%CI = 1.059–1.521 p-value = 0.010) were found to be significant predictors of COVID-19 severity. The following factors were significantly associated with COVID-19 outcome; age group (AOR = 2.767, 95%CI = 1.099–6.067, p-value = 0.031), white blood cell count (WBC) (AOR = 4.253, 95%CI = 1.918–9.429, p-value = 0.0001) and sodium level (AOR = 3.435, 95%CI = 1.439–8.198, p-value = 0.005). CONCLUSIONS: Assessing and monitoring the laboratory markers of WBC, NLR, SGOT, sodium and potassium levels at the earliest stage of the disease could have a considerable role in halting disease progression and death. Public Library of Science 2021-03-15 /pmc/articles/PMC7959358/ /pubmed/33720944 http://dx.doi.org/10.1371/journal.pone.0246087 Text en © 2021 Leulseged et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://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 Leulseged, Tigist W. Hassen, Ishmael S. Ayele, Birhanu T. Tsegay, Yakob G. Abebe, Daniel S. Edo, Mesay G. Maru, Endalkachew H. Zewde, Wuletaw C. Naylor, Lydia K. Semane, Dejene F. Dresse, Menayit T. Tezera, Bereket B. Laboratory biomarkers of COVID-19 disease severity and outcome: Findings from a developing country |
title | Laboratory biomarkers of COVID-19 disease severity and outcome: Findings from a developing country |
title_full | Laboratory biomarkers of COVID-19 disease severity and outcome: Findings from a developing country |
title_fullStr | Laboratory biomarkers of COVID-19 disease severity and outcome: Findings from a developing country |
title_full_unstemmed | Laboratory biomarkers of COVID-19 disease severity and outcome: Findings from a developing country |
title_short | Laboratory biomarkers of COVID-19 disease severity and outcome: Findings from a developing country |
title_sort | laboratory biomarkers of covid-19 disease severity and outcome: findings from a developing country |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7959358/ https://www.ncbi.nlm.nih.gov/pubmed/33720944 http://dx.doi.org/10.1371/journal.pone.0246087 |
work_keys_str_mv | AT leulsegedtigistw laboratorybiomarkersofcovid19diseaseseverityandoutcomefindingsfromadevelopingcountry AT hassenishmaels laboratorybiomarkersofcovid19diseaseseverityandoutcomefindingsfromadevelopingcountry AT ayelebirhanut laboratorybiomarkersofcovid19diseaseseverityandoutcomefindingsfromadevelopingcountry AT tsegayyakobg laboratorybiomarkersofcovid19diseaseseverityandoutcomefindingsfromadevelopingcountry AT abebedaniels laboratorybiomarkersofcovid19diseaseseverityandoutcomefindingsfromadevelopingcountry AT edomesayg laboratorybiomarkersofcovid19diseaseseverityandoutcomefindingsfromadevelopingcountry AT maruendalkachewh laboratorybiomarkersofcovid19diseaseseverityandoutcomefindingsfromadevelopingcountry AT zewdewuletawc laboratorybiomarkersofcovid19diseaseseverityandoutcomefindingsfromadevelopingcountry AT naylorlydiak laboratorybiomarkersofcovid19diseaseseverityandoutcomefindingsfromadevelopingcountry AT semanedejenef laboratorybiomarkersofcovid19diseaseseverityandoutcomefindingsfromadevelopingcountry AT dressemenayitt laboratorybiomarkersofcovid19diseaseseverityandoutcomefindingsfromadevelopingcountry AT tezerabereketb laboratorybiomarkersofcovid19diseaseseverityandoutcomefindingsfromadevelopingcountry |