ArticleNorthern clinics of Istanbul2023
Plasminogen activator inhibitor-1 levels as an indicator of severity and mortality for COVID-19.
Article in Northern clinics of Istanbul, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Inflammatory and Endothelial Dysfunction Biomarkers Predict Severe COVID-19 in Hospitalized Patients: Development of the CCBR Model.Biomedicines · 2026Article
- Article
- Blood Coagulation in COVID-19: Systems-Biology Evidence, Clinical Implications, and Therapeutic Opportunities in an Evolving Pandemic.ACS omega · 2026Article
- Current Insights into Clinical, Molecular, and Therapeutic Approaches to Acute Respiratory Distress Syndrome.Medical sciences (Basel, Switzerland) · 2026Review
- Clot formation, structure, and fibrinolysis of plasma from pancreatic cancer patients.Journal of thrombosis and thrombolysis · 2025Article
- Review
- Biomarkers of Endothelial Damage and Disease Severity in COVID-19 Patients.Current issues in molecular biology · 2025Article
- Vascular Pathogenesis in Acute and Long COVID: Current Insights and Therapeutic Outlook.Seminars in thrombosis and hemostasis · 2025Review
- The Role of the VWF/ADAMTS13 Axis in the Thromboinflammatory Response in Ischemic Stroke After SARS-CoV2 Infection.Brain and behavior · 2025Article
- Immunity and Coagulation in COVID-19.International journal of molecular sciences · 2024Review
- Mechanisms of endothelial activation, hypercoagulation and thrombosis in COVID-19: a link with diabetes mellitus.Cardiovascular diabetology · 2024Review
- Article
- VEGFR and DPP-IV as Markers of Severe COVID-19 and Predictors of ICU Admission.International journal of molecular sciences · 2023Article
- COVID-19 and the Concept of Thrombo-Inflammation: Review of the Relationship between Immune Response, Endothelium and Coagulation.Journal of clinical medicine · 2023Review
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Abstract
objectiveCoronavirus disease-19 (COVID-19) is a multisystemic disease that can cause severe illness and mortality by exacerbating symptoms such as thrombosis, fibrinolysis, and inflammation. Plasminogen activator inhibitor-1 (PAI-1) plays an important role in regulating fibrinolysis and may cause thrombotic events to develop. The goal of this study is to examine the relationship between PAI-1 levels and disease severity and mortality in relation to COVID-19.
methodsA total of 71 hospitalized patients were diagnosed with COVID-19 using real time-polymerase chain reaction tests. Each patient underwent chest computerized tomography (CT). Data from an additional 20 volunteers without COVID-19 were included in this single-center study. Each patient's PAI-1 data were collected at admission, and the CT severity score (CT-SS) was then calculated for each patient.
resultsThe patients were categorized into the control group (n=20), the survivor group (n=47), and the non-survivor group (n=24). In the non-survivor group, the mean age was 75.3±13.8, which is higher than in the survivor group (61.7±16.9) and in the control group (59.5±11.2), (p=0.001). When the PAI-1 levels were compared between each group, the non-survivor group showed the highest levels, followed by the survivor group and then the control group (p<0.001). Logistic regression analysis revealed that age, PAI-1, and disease severity independently predicted COVID-19 mortality rates. In this study, it was observed that PAI-1 levels with >10.2 ng/mL had 83% sensitivity and an 83% specificity rate when used to predict mortality after COVID-19. Then, patients were divided into severe (n=33) and non-severe (n=38) groups according to disease severity levels. The PAI-1 levels found were higher in the severe group (p<0.001) than in the non-severe group. In the regression analysis that followed, high sensitive troponin I and PAI-1 were found to indicate disease severity levels. The CT-SS was estimated as significantly higher in the non-survivor group compared to the survivor group (p<0.001). When comparing CT-SS between the severe group and the non-severe group, this was significantly higher in the severe group (p<0.001). In addition, a strong statistically significant positive correlation was found between CT-SS and PAI-1 levels (r: 0.838, p<0.001).
conclusionAnticipating poor clinical outcomes in relation to COVID-19 is crucial. This study showed that PAI-1 levels could independently predict disease severity and mortality rates for patients with COVID-19.
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