Prediction of severe illness due to COVID-19 based on an analysis of initial Fibrinogen to Albumin Ratio and Platelet count
Concomitant coagulation disorder can occur in severe patients withCOVID-19, but in-depth studies are limited. This study aimed to describe the parameters of coagulation function of patients with COVID-19 and reveal the risk factors of developing severe disease. This study retrospectively analyzed 11...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2020-07-01
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| Series: | Platelets |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/09537104.2020.1760230 |
| _version_ | 1797684228754767872 |
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| author | Xiaojie Bi Zhengxian SU Haixi Yan Juping Du Jing Wang Linping Chen Minfei Peng Shiyong Chen Bo Shen Jun Li |
| author_facet | Xiaojie Bi Zhengxian SU Haixi Yan Juping Du Jing Wang Linping Chen Minfei Peng Shiyong Chen Bo Shen Jun Li |
| author_sort | Xiaojie Bi |
| collection | DOAJ |
| description | Concomitant coagulation disorder can occur in severe patients withCOVID-19, but in-depth studies are limited. This study aimed to describe the parameters of coagulation function of patients with COVID-19 and reveal the risk factors of developing severe disease. This study retrospectively analyzed 113patients with SARS-CoV-2 infection in Taizhou Public Health Center. Clinical characteristics and indexes of coagulation function were collected. A multivariate Cox analysis was performed to identify potential biomarkers for predicting disease progression. Based on the results of multivariate Cox analysis, a Nomogram was built and the predictive accuracy was evaluated through the calibration curve, decision curve, clinical impact curve, and Kaplan–Meier analysis. Sensitivity, specificity, predictive values were calculated to assess the clinical value. The data showed that Fibrinogen, FAR, and D-dimer were higher in the severe patients, while PLTcount, Alb were much lower. Multivariate Cox analysis revealed that FAR and PLT count were independent risk factors for disease progression. The optimal cutoff values for FAR and PLT count were 0.0883 and 135*109/L, respectively. The C-index [0.712 (95% CI = 0.610–0.814)], decision curve, clinical impact curve showed that Nomogram could be used to predict the disease progression. In addition, the Kaplan–Meier analysis revealed that potential risk decreased in patients with FAR<0.0883 and PLT count>135*109/L.The model showed a good negative predictive value [(0.9474 (95%CI = 0.845–0.986)].This study revealed that FAR and PLT count were independent risk factors for severe illness and the severity of COVID-19 might be excluded when FAR<0.0883 and PLT count>135*109/L. |
| first_indexed | 2024-03-12T00:26:38Z |
| format | Article |
| id | doaj.art-d4a90647e43447f5be87715838268fe0 |
| institution | Directory Open Access Journal |
| issn | 0953-7104 1369-1635 |
| language | English |
| last_indexed | 2024-03-12T00:26:38Z |
| publishDate | 2020-07-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Platelets |
| spelling | doaj.art-d4a90647e43447f5be87715838268fe02023-09-15T10:38:07ZengTaylor & Francis GroupPlatelets0953-71041369-16352020-07-0131567467910.1080/09537104.2020.17602301760230Prediction of severe illness due to COVID-19 based on an analysis of initial Fibrinogen to Albumin Ratio and Platelet countXiaojie Bi0Zhengxian SU1Haixi Yan2Juping Du3Jing Wang4Linping Chen5Minfei Peng6Shiyong Chen7Bo Shen8Jun Li9Wenzhou Medical UniversityWenzhou Medical UniversityWenzhou Medical UniversityWenzhou Medical UniversityWenzhou Medical UniversityWenzhou Medical UniversityWenzhou Medical UniversityWenzhou Medical UniversityWenzhou Medical UniversityWenzhou Medical UniversityConcomitant coagulation disorder can occur in severe patients withCOVID-19, but in-depth studies are limited. This study aimed to describe the parameters of coagulation function of patients with COVID-19 and reveal the risk factors of developing severe disease. This study retrospectively analyzed 113patients with SARS-CoV-2 infection in Taizhou Public Health Center. Clinical characteristics and indexes of coagulation function were collected. A multivariate Cox analysis was performed to identify potential biomarkers for predicting disease progression. Based on the results of multivariate Cox analysis, a Nomogram was built and the predictive accuracy was evaluated through the calibration curve, decision curve, clinical impact curve, and Kaplan–Meier analysis. Sensitivity, specificity, predictive values were calculated to assess the clinical value. The data showed that Fibrinogen, FAR, and D-dimer were higher in the severe patients, while PLTcount, Alb were much lower. Multivariate Cox analysis revealed that FAR and PLT count were independent risk factors for disease progression. The optimal cutoff values for FAR and PLT count were 0.0883 and 135*109/L, respectively. The C-index [0.712 (95% CI = 0.610–0.814)], decision curve, clinical impact curve showed that Nomogram could be used to predict the disease progression. In addition, the Kaplan–Meier analysis revealed that potential risk decreased in patients with FAR<0.0883 and PLT count>135*109/L.The model showed a good negative predictive value [(0.9474 (95%CI = 0.845–0.986)].This study revealed that FAR and PLT count were independent risk factors for severe illness and the severity of COVID-19 might be excluded when FAR<0.0883 and PLT count>135*109/L.http://dx.doi.org/10.1080/09537104.2020.1760230coagulation and fibrinolysiscovid-19fibrinogen-to-albumin ratio (far)non-severe survival (nss)platelet count (plt)prediction |
| spellingShingle | Xiaojie Bi Zhengxian SU Haixi Yan Juping Du Jing Wang Linping Chen Minfei Peng Shiyong Chen Bo Shen Jun Li Prediction of severe illness due to COVID-19 based on an analysis of initial Fibrinogen to Albumin Ratio and Platelet count Platelets coagulation and fibrinolysis covid-19 fibrinogen-to-albumin ratio (far) non-severe survival (nss) platelet count (plt) prediction |
| title | Prediction of severe illness due to COVID-19 based on an analysis of initial Fibrinogen to Albumin Ratio and Platelet count |
| title_full | Prediction of severe illness due to COVID-19 based on an analysis of initial Fibrinogen to Albumin Ratio and Platelet count |
| title_fullStr | Prediction of severe illness due to COVID-19 based on an analysis of initial Fibrinogen to Albumin Ratio and Platelet count |
| title_full_unstemmed | Prediction of severe illness due to COVID-19 based on an analysis of initial Fibrinogen to Albumin Ratio and Platelet count |
| title_short | Prediction of severe illness due to COVID-19 based on an analysis of initial Fibrinogen to Albumin Ratio and Platelet count |
| title_sort | prediction of severe illness due to covid 19 based on an analysis of initial fibrinogen to albumin ratio and platelet count |
| topic | coagulation and fibrinolysis covid-19 fibrinogen-to-albumin ratio (far) non-severe survival (nss) platelet count (plt) prediction |
| url | http://dx.doi.org/10.1080/09537104.2020.1760230 |
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