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Hemostatic and liver function parameters as COVID-19 severity markers. | LitMetric

AI Article Synopsis

Article Abstract

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a disease newly discovered in December 2019 which affects coagulation cascade and liver functions. The aim of this study was to investigate the potential of hemostatic and liver function parameters as severity markers in COVID-19 patients. This study was an observational analytic with cohort retrospective design using total sampling method. Data were retrieved from medical record of COVID-19 patients admitted to provincial hospital in Banda Aceh, Indonesia from March 2020 to March 2022. There were 1208 data eligible for the study after applying certain criteria. Mann-Whitney, logistic regression, and receiving operating characteristic (ROC) analyses were used to analysis the data. Thrombocyte count (<0.001), prothrombin time (<0.001), activated partial thromboplastin time (<0.001), D-dimer (<0.001), fibrinogen (<0.001), aspartate aminotransferase (<0.001), and alanine transaminase (<0.001) significantly increased in severe compared to mild COVID-19 patients. After being adjusted, age (odds ratio (OR); 1.026 (95% confidence interval (CI): 1.016-1.037) was the most significant factor in predicting COVID-19 severity. Fibrinogen (cut-off 526.5 mg/L) was the best parameter associated with COVID-19 severity with 70% sensitivity and 66.4% specificity. Meanwhile, D-dimer (cut-off 805 ng/mL) had a sensitivity of 72.3% and specificity of 66.4%. Combining the parameters resulted in improved sensitivity to 82.0% with a slight decline of specificity to 65.5%. In conclusion, fibrinogen and D-dimer level on admission could be used as biomarkers in predicting COVID-19 prognosis. Routine monitoring and evaluation of laboratory testing especially D-dimer and fibrinogen could be implemented in order to reduce morbidity and mortality rate of COVID-19.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11125416PMC
http://dx.doi.org/10.52225/narra.v4i1.178DOI Listing

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