Literature DB >> 33030047

A Retrospective Analysis of the Coagulation Dysfunction in COVID-19 Patients.

Xu Chen1, Qinghua Wang2, Min Xu3, Chengbin Li1.   

Abstract

To discuss the coagulation dysfunction in COVID-19 patients and to find new biomarkers to separate severe COVID-19 patients from mild ones. We use a retrospective analysis of 88 COVID-19 patients, and compare the coagulation function between severe and mild groups. We found the prothrombin time (PT), thrombin time (TT), D-dimer were significantly higher in the severe group (P < 0.05), and the highest area under the curve (AUC) is 0.91 for D-dimer, while the AUC of PT and TT were 0.80 and 0.61 respectively. We identified that D-dimer has a better value in predicting patients who are likely to develop into severe cases, with the sensitivity and specificity were 84.4% and 88.8%, respectively. D-dimer may be a good biomarker to separate the severe COVID-19 patients from the mild ones.

Entities:  

Keywords:  biomarkers; blood coagulation factors; coagulation

Mesh:

Substances:

Year:  2020        PMID: 33030047      PMCID: PMC7549161          DOI: 10.1177/1076029620964868

Source DB:  PubMed          Journal:  Clin Appl Thromb Hemost        ISSN: 1076-0296            Impact factor:   2.389


Background

Since December 2019, an outbreak of coronavirus disease 2019 in Wuhan, has spread throughout the world.[1] Till now, about 19 million COVID-19 cases leading to 713,829 deaths have been reported worldwild, including 89,026 cases and 4,687 deaths in China. The pathogen has been identified as a β-coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and this virus can spread from human to human(SARS-CoV-2).[2] As a single-stranded RNA virus, SARS-CoV-2 infection may present with various manifestations, such as fever, dry coughing, fatigue, shortness of breath and some of patients may develop into respiratory failure or even death. Old-aged patients with underlying medical conditions such as hypertension, diabetes, cardiovascular and cerebrovascular diseases are more likely to develop into sever cases which are associated with worse outcome.[3-5] So far, neither specific therapeutic drug nor preventive vaccine is available and treatment has been limited to supportive measures.[4] Although fast and accurate identification of the patients who will develop into severe condition is important in patient management, no specific biomarker has been identified so far. SARS-CoV-2 infection may cause coagulation dysfunction but the results are quite varied. Results from a retrospective analysis of 99 COVID-19 patients revealed that 16% of the patients had an reduced activated partial thromboplastin time (APTT) while 6% showed an extended APTT, 30% presented with a shortened PT, and 5% of extended PT.[6] Another study showed that 4 of 7 COVID-19 patients had an extended PT and 4 were diagnosed with Disseminated Intravascular Coagulation (DIC).[7] Interestingly, D-dimer and extended PT were identified in 99 severe COVID-19 patients who received low molecular weight heparin treatment for 7 days or longer.[8] In line with this observation, 4 of 30 medical workers infected with SARS-CoV-2, D-dimer was also significantly increased.[9] COVID-19 patients with D-dimer levels ≥2.0 µg/ml had a higher incidence of mortality when compared to those with D-dimer levels <2.0 µg/ml.[10] A retrospective analysis also found that fibrinogen (Fib) and D-dimer were higher while PLT count, Alb were much lower in severe patients.[11] In this study, we performed a retrospective analysis on the coagulation function in mild and severe COVID-19 patients, trying to identify a biomarker that can be used to predict the severity of this pandemic disease.

Methods

We have retrospectively analyzed 58 mild and 30 severe COVID-19 patients who were confirmed to have SARS-CoV-2 infection by RNA detection and were enrolled in Jingzhou central hospital, Hubei Province from February 1 to March 6, 2020. The diagnosis and classification of COVID-19 were based on the guidelines on the novel coronavirus-infected pneumonia diagnosis and treatment (trial version 7) issued by the National Health Commission of China. COVID-19 patients who had one of the following conditions at the time of admission were classified as severe cases: (I) respiratory distress (≥30 breaths/min); (II) oxygen saturation at rest ≤93%; (III) PaO2/FiO2 ratio ≤300 mmHg; (IV) lung imaging progress >50% during 24-48 hours. The coagulation tests from plasma samples were performed on ACL TOP automatic coagulation analyzer (Instrumentation Laboratory, IL, USA) following manufacturer’s recommended procedures. The test items include PT, APTT, FIB, TT, and D-dimer. The Graphpad Prism 5.0 was used for statistical data analysis. The independent sample t-tests were used to compare the differences between the mild and severe groups. The receiver operating curve (ROC) and the area under the curve(AUC) were calculated to compare each parameter. A P-value of <0.05 was considered statistically significant.

Results

In this retrospective study, we analyzed and compared the coagulation function of COVID-19 mild (n = 58) and severe(n = 30) patients. As shown in Table 1, there was no statistical difference in APTT, Fibrinogen (Fib) between the 2 groups. However, PT, TT, D-dimer were significantly higher in the severe group (P < 0.05, Figure 1).
Table 1.

Coagulation Parameters of COVID-19 Patients Between Mild and Severe Groups.

ParametersMild groupSevere group P value
PT(S)11.34 ± 1.3513.98 ± 2.97<0.001
APTT(S)30.39 ± 4.2932.34 ± 7.180.112
Fib(g/L)4.56 ± 1.534.25 ± 1.280.46
TT(S)16.04 ± 1.7617.33 ± 3.000.015
D-dimer(ng/mL)575.53 ± 845.853258.36 ± 3639.270.014

Abbreviations: PT, prothrombin time APTT, activated partial thromboplastin time; Fib, fibrinogen; TT, thrombin time; S, seconds.

Figure 1.

The coagulation parameters between mild and severe groups. TT(A), D-dimer(B), PT(C), APTT(D), Fib(E) between mild patients group and severe papients group, P < 0.05 as a statistic difference.

Coagulation Parameters of COVID-19 Patients Between Mild and Severe Groups. Abbreviations: PT, prothrombin time APTT, activated partial thromboplastin time; Fib, fibrinogen; TT, thrombin time; S, seconds. The coagulation parameters between mild and severe groups. TT(A), D-dimer(B), PT(C), APTT(D), Fib(E) between mild patients group and severe papients group, P < 0.05 as a statistic difference. Then we further analyzed PT, TT, D-dimer, and the receiver operation characteristic curve (ROC) and AUC were calculated for these 3 parameters. As shown in Figure 2, the highest AUC is D-dimer (0.91), and the AUC of PT and TT were 0.80 and 0.61 respectively. As shown in Table 2, D-dimer has a better predicting value for severe patients, with the sensitivity and specificity of 84.4% and 88.8%, respectively. In addition, the positive predictive value (PPV) and negative predictive value (NPV) is higher than the value of TT and PT.
Figure 2.

The receiver operation curve of hematological parameters for predicting the severity of COVID-19 patients. ROC analysis of PT, TT, D-dimer for discriminating 30 severe COVID-19 cases from 58 mild cases.

Table 2.

The Predictive Value of PT, TT and D-Dimer in Mild and Severe COVID-19 Patients.

groupAUCpCut off valueSensitivity (%)Specificity (%)Positive predicitive value(%)Negative predicitive value(%)
PT(S) 0.804<0.00113.355092.98076.8
TT(S) 0.613<0.0119.8539.196.481.870.5
D-dimer 0.910<0.0182184.288.288.988.2

Abbreviations: PT, prothrombin time; TT, thrombin time; S, seconds.

The receiver operation curve of hematological parameters for predicting the severity of COVID-19 patients. ROC analysis of PT, TT, D-dimer for discriminating 30 severe COVID-19 cases from 58 mild cases. The Predictive Value of PT, TT and D-Dimer in Mild and Severe COVID-19 Patients. Abbreviations: PT, prothrombin time; TT, thrombin time; S, seconds.

Discussion

Since the outbreak of COVID-19 in Wuhan, this disease has been spreading all over the world and the WHO declares a pandemic which causes a Public Health Emergency of International Concern. SARS-CoV-2 was identified as the pathogen of the COVID-19 and the virus uses angiotensin-converting enzyme2(ACE2) as one of the receptors to enter into susceptible cells.[12] Belonging to the β-coronavirus genus, SARS-CoV-2 has a 85% homology with bat SARS-like coronavirus.[12] Once infected, the disease progression and outcome of the patients vary. Although most patients infected by SARS-CoV-2 present with mild or even no symptoms, some will develop into severe cases leading to breath failure and death if not managed properly. Therefore, identification of the biomarkers that can be used to predict disease progression is of particular importance. D-dimer molecules are generated through the degradation of cross-linked fibrin during fibrinolysis.[13] The analysis of D-dimer is critical for the modern triage and diagnosis of disseminated intravascular coagulation (DIC).[14] In this retrospective study, we aim to identify possible biomarkers to differentiate the severe patients from the mild ones so that clinicians may make a quick response and provide a more suitable therapeutic scheme for severe patients. We analyzed the coagulation function of the mild and severe groups, and we found that PT, TT and D-dimer showed a higher level in the severe group, while no statistic difference in APTT and Fib in 2 groups (Table 1 and Figure 1). In the severe group, PT, TT and D-dimer were statistically higher when compared with those of mild group (P value was <0.001,<0.05,0.014 respectively). We further chose TT, PT and D-dimer for ROC test (Figure 2). We found that D-dimer has a larger area (0.91) than TT (0.613) and PT(0.804) (Table 2). Although PT and TT both have higher specificity(92.9% and 96.4%), their sensitivity (50% and 39.1%) were much lower than D-dimer. D-dimer has better sensitivity of 84.2% and specificity of 88.9% in predicting the severe COVID-19 cases. Furthermore, the optimum cut off value of D-dimer was 821ng/mL. COVID-19 patients with the D-dimer higher than 821ng/mL may develop into severe cases that need more carefully monitored. However, there were only 88 cases, with 58 mild and 30 severe patients, respectively. Considering the relatively small patient population in this analysis, more clinical cases are needed to confirm our conclusion. Furthermore, we did not analyze the prognosis of the enrolled cases, and follow-up study is in progress. In summary, our retrospective analysis of 50 mild and 38 severe COVID-19 patients indicated that the coagulation function between the mild and the severe patients are different, and D-dimer higher than 821ng/mL is a useful biomarker to predict the patient is likely to develop into severe case with a sensitivity of 84.2% and specificity of 88.9%.
  14 in total

1.  [Clinical characteristics of 30 medical workers infected with new coronavirus pneumonia].

Authors:  M Liu; P He; H G Liu; X J Wang; F J Li; S Chen; J Lin; P Chen; J H Liu; C H Li
Journal:  Zhonghua Jie He He Hu Xi Za Zhi       Date:  2020-02-17

2.  Anticoagulant treatment is associated with decreased mortality in severe coronavirus disease 2019 patients with coagulopathy.

Authors:  Ning Tang; Huan Bai; Xing Chen; Jiale Gong; Dengju Li; Ziyong Sun
Journal:  J Thromb Haemost       Date:  2020-04-27       Impact factor: 5.824

3.  Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding.

Authors:  Roujian Lu; Xiang Zhao; Juan Li; Peihua Niu; Bo Yang; Honglong Wu; Wenling Wang; Hao Song; Baoying Huang; Na Zhu; Yuhai Bi; Xuejun Ma; Faxian Zhan; Liang Wang; Tao Hu; Hong Zhou; Zhenhong Hu; Weimin Zhou; Li Zhao; Jing Chen; Yao Meng; Ji Wang; Yang Lin; Jianying Yuan; Zhihao Xie; Jinmin Ma; William J Liu; Dayan Wang; Wenbo Xu; Edward C Holmes; George F Gao; Guizhen Wu; Weijun Chen; Weifeng Shi; Wenjie Tan
Journal:  Lancet       Date:  2020-01-30       Impact factor: 79.321

4.  Coronavirus Disease 2019 (COVID-19): Emerging and Future Challenges for Dental and Oral Medicine.

Authors:  L Meng; F Hua; Z Bian
Journal:  J Dent Res       Date:  2020-03-12       Impact factor: 6.116

Review 5.  What dentists need to know about COVID-19.

Authors:  Maryam Baghizadeh Fini
Journal:  Oral Oncol       Date:  2020-04-28       Impact factor: 5.337

6.  Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study.

Authors:  Nanshan Chen; Min Zhou; Xuan Dong; Jieming Qu; Fengyun Gong; Yang Han; Yang Qiu; Jingli Wang; Ying Liu; Yuan Wei; Jia'an Xia; Ting Yu; Xinxin Zhang; Li Zhang
Journal:  Lancet       Date:  2020-01-30       Impact factor: 79.321

7.  Prediction of severe illness due to COVID-19 based on an analysis of initial Fibrinogen to Albumin Ratio and Platelet count.

Authors:  Xiaojie Bi; Zhengxian Su; Haixi Yan; Juping Du; Jing Wang; Linping Chen; Minfei Peng; Shiyong Chen; Bo Shen; Jun Li
Journal:  Platelets       Date:  2020-05-05       Impact factor: 3.862

Review 8.  Coronavirus Disease 2019 (COVID-19) and pregnancy: what obstetricians need to know.

Authors:  Sonja A Rasmussen; John C Smulian; John A Lednicky; Tony S Wen; Denise J Jamieson
Journal:  Am J Obstet Gynecol       Date:  2020-02-24       Impact factor: 8.661

Review 9.  Possible aerosol transmission of COVID-19 and special precautions in dentistry.

Authors:  Zi-Yu Ge; Lu-Ming Yang; Jia-Jia Xia; Xiao-Hui Fu; Yan-Zhen Zhang
Journal:  J Zhejiang Univ Sci B       Date:  2020-03-16       Impact factor: 3.066

10.  A Novel Coronavirus from Patients with Pneumonia in China, 2019.

Authors:  Na Zhu; Dingyu Zhang; Wenling Wang; Xingwang Li; Bo Yang; Jingdong Song; Xiang Zhao; Baoying Huang; Weifeng Shi; Roujian Lu; Peihua Niu; Faxian Zhan; Xuejun Ma; Dayan Wang; Wenbo Xu; Guizhen Wu; George F Gao; Wenjie Tan
Journal:  N Engl J Med       Date:  2020-01-24       Impact factor: 91.245

View more
  5 in total

Review 1.  Diagnostic Accuracy of Liquid Biomarkers in Airway Diseases: Toward Point-of-Care Applications.

Authors:  Vivianne Landry; Patrick Coburn; Karen Kost; Xinyu Liu; Nicole Y K Li-Jessen
Journal:  Front Med (Lausanne)       Date:  2022-06-06

2.  Predictive Value of Blood Coagulation Parameters in Poor Outcomes in COVID-19 Patients: A Retrospective Observational Study in Romania.

Authors:  Cosmin Citu; Bogdan Burlea; Florin Gorun; Andrei Motoc; Oana Maria Gorun; Daniel Malita; Adrian Ratiu; Roxana Margan; Mirela Loredana Grigoras; Felix Bratosin; Ioana Mihaela Citu
Journal:  J Clin Med       Date:  2022-05-17       Impact factor: 4.964

3.  Hemostatic System (Fibrinogen Level, D-Dimer, and FDP) in Severe and Non-Severe Patients With COVID-19: A Systematic Review and Meta-Analysis.

Authors:  Mehrdad Rostami; Zahra Khoshnegah; Hassan Mansouritorghabeh
Journal:  Clin Appl Thromb Hemost       Date:  2021 Jan-Dec       Impact factor: 2.389

4.  An interpretable machine learning model based on a quick pre-screening system enables accurate deterioration risk prediction for COVID-19.

Authors:  Lijing Jia; Zijian Wei; Heng Zhang; Jiaming Wang; Ruiqi Jia; Manhong Zhou; Xueyan Li; Hankun Zhang; Xuedong Chen; Zheyuan Yu; Zhaohong Wang; Xiucheng Li; Tingting Li; Xiangge Liu; Pei Liu; Wei Chen; Jing Li; Kunlun He
Journal:  Sci Rep       Date:  2021-11-30       Impact factor: 4.379

5.  Blood coagulation parameter abnormalities in hospitalized patients with confirmed COVID-19 in Ethiopia.

Authors:  Shambel Araya; Mintesnot Aragaw Mamo; Yakob Gebregziabher Tsegay; Asegdew Atlaw; Aschalew Aytenew; Abebe Hordofa; Abebe Edao Negeso; Moges Wordofa; Tirhas Niguse; Mahlet Cheru; Zemenu Tamir
Journal:  PLoS One       Date:  2021-06-21       Impact factor: 3.240

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.