Laboratory biomarkers of COVID-19 disease severity and outcome: Findings from a developing country

To identify laboratory biomarkers that predict disease severity and outcome among COVID-19 patients admitted to the Millennium COVID-19 Care Center in Ethiopia. A retrospective cohort study was conducted among 429 COVID-19 patients who were on follow up from July to October 2020. Data was described...

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Bibliographic Details
Published in:PloS one 2021-03, Vol.16 (3), p.e0246087-e0246087
Main Authors: 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
Format: Article
Language:English
Subjects:
Adolescent
Adult
Age Factors
Aspartate Aminotransferases - blood
Biology and Life Sciences
Biomarkers
Biomarkers - analysis
Comorbidity
Coronaviruses
COVID-19
COVID-19 - pathology
COVID-19 - virology
Data collection
Developing Countries
Diabetes
Disease prevention
Drafting software
Editing
Epidemics
Epidemiology
Ethiopia
Female
Hospitals
Humans
Illnesses
Laboratories
LDCs
Logistic Models
Lymphocytes - cytology
Male
Medical schools
Medicine and Health Sciences
Middle Aged
Neutrophils - cytology
Odds Ratio
Pandemics
People and Places
Physical Sciences
Physiological aspects
Prognosis
Retrospective Studies
SARS-CoV-2 - isolation & purification
Severity of Illness Index
Software
Supervision
Visualization
Young Adult
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Summary:To identify laboratory biomarkers that predict disease severity and outcome among COVID-19 patients admitted to the Millennium COVID-19 Care Center in Ethiopia. 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. 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
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0246087