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Authors' ORCID iD

https://orcid.org/0000-0002-9606-7669

Article Type

Original Study

Abstract

Background: The COVID-19 pandemic is associated with prothrombotic complications, leading to increased morbidity and mortality. D-dimer, a fibrin degradation product, serves as a biomarker for coagulation abnormalities. This study evaluates the role of D-dimer in predicting disease severity and hospitalization in COVID-19 patients. Aim: To assess correlations between D-dimer levels and age, gender, comorbidities, disease severity, and hospitalization needs in COVID-19 patients. Methods: A retrospective analysis of 78 COVID-19-positive patients admitted to an outpatient clinic was conducted. Data on demographics, comorbidities, vaccination status, disease severity, and admission D-dimer levels were analyzed using statistical tests (t-tests, chi-square, Mann-Whitney U). Results: The mean age of participants was 49 years, with 56.4% males and 43.6% females. Approximately 52% of patients had a comorbid disease, primarily hypertension and diabetes. Older patients and those with coexisting diseases had significantly higher D-dimer levels (p-values 0.017 and 0.045, respectively), with non-significant differences between males and females (p-value 0.648). Older patients had a significantly higher need for hospitalization during acute COVID-19 infection (p-value 0.002). Additionally, patients with elevated admission D-dimer levels showed a greater prevalence of severe disease (p-value 0.01) and a higher need for hospitalization (p-value 0.028). Conclusions: Elevated admission D-dimer levels are strongly linked to severe COVID-19 outcomes and hospitalization, highlighting their utility as an early prognostic marker. Clinical management of COVID-19 patients may be guided by D-dimer assessment, which may help predict disease severity.

Keywords

COVID-19, D-dimer, prognostic marker, thrombosis, hospitalization, disease severity.

Creative Commons License

Creative Commons Attribution-NonCommercial 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

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