ArticleAfrican journal of laboratory medicine2025
Thromboelastography in COVID-19 patients: An observational study in the South African context.
Article in African journal of laboratory medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Coronavirus disease 2019 (COVID-19) increases the risk of venous thromboembolism, requiring monitoring of low molecular weight heparin (LMWH) via a time-consuming, costly and often unavailable test - anti-factor Xa (anti-Xa). An affordable, rapid point-of-care alternative, the thromboelastogram, is available, but performance comparisons to anti-Xa are lacking. Objective: This study evaluated the relationship between anti-Xa and thromboelastogram in patients with COVID-19 receiving LMWH. Methods: This was a retrospective study of patients with COVID-19 receiving LMWH at Chris Hani Baragwanath Academic Hospital, Johannesburg, South Africa, between November 2020 and January 2021. Blood samples tested with thromboelastogram and anti-Xa were drawn at three timepoints (one prior to and two after administration of LMWH). Thromboelastogram parameters comprised reaction time (R-time; onset of testing to the start of clot formation), kinetics time (K-time; start of clot formation until the clot reached 20 mm), and thromboelastogram coagulation index (overall coagulation status of whole blood). Results: Forty-two patients with COVID-19 (15 male and 27 female) met the study criteria. There was a statistically significant, low to moderate correlation (Spearman's correlation coefficient [ Conclusion: Thromboelastogram coagulation index, R-times and K-times had a statistically significant association with anti-Xa levels in patients with COVID-19. Further research is required regarding their clinical utility. What this study adds: Thromboelastograms may represent a more cost-effective and accessible option to the conventional anti-Xa test in patients receiving LMWH. However, future research with larger sample sizes, varying disease profiles, and severity of illness is required.
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