Clotting Factors in COVID-19: Epidemiological Association and Prognostic Values in Different Clinical Presentations in an Italian Cohort
Abstract
:1. Introduction
2. Materials and Methods
Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- McCloskey, B.; Heymann, D.L. SARS to novel coronavirus: Old lessons and new lessons. Epidemiol. Infect. 2020, 148, e22. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Guan, W.J.; Ni, Z.Y.; Hu, Y.; Liang, W.H.; Ou, C.Q.; He, J.X.; Liu, L.; Shan, H.; Lei, C.L.; China Medical Treatment Expert Group for Covid-19; et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N. Engl. J. Med. 2020, 382, 1708–1720. [Google Scholar] [CrossRef] [PubMed]
- Liu, J.; Zheng, X.; Tong, Q.; Li, W.; Wang, B.; Sutter, K.; Trilling, M.; Lu, M.; Dittmer, U.; Yang, D. Overlapping and discrete aspects of the pathology and pathogenesis of the emerging human pathogenic coronaviruses SARS-CoV, MERS-CoV, and 2019-nCoV. J. Med. Virol. 2020, 92, 491–494. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Onder, G.; Rezza, G.; Brusaferro, S. Case-Fatality Rate and Characteristics of Patients Dying in Relation to COVID-19 in Italy. JAMA 2020. [Google Scholar] [CrossRef] [PubMed]
- Zhou, F.; Yu, T.; Du, R.; Fan, G.; Liu, Y.; Liu, Z.; Xiang, J.; Wang, Y.; Song, B.; Gu, X.; et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study. Lancet 2020, 395, 1054–1062. [Google Scholar] [CrossRef]
- Wang, D.; Yin, Y.; Hu, C.; Liu, X.; Zhang, X.; Zhou, S.; Jian, M.; Xu, H.; Prowle, J.; Hu, B.; et al. Clinical course and outcome of 107 patients infected with the novel coronavirus, SARS-CoV-2, discharged from two hospitals in Wuhan, China. Crit. Care 2020, 24, 188. [Google Scholar] [CrossRef] [PubMed]
- Stief, T.W.; Ijagha, O.; Weiste, B.; Herzum, I.; Renz, H.; Max, M. Analysis of hemostasis alterations in sepsis. Blood Coagul. Fibrinolysis 2007, 18, 179–186. [Google Scholar] [CrossRef] [PubMed]
- Di Micco, B.; Metafora, S.; Colonna, G.; Cartenì, M.; Ragone, R.; Macalello, M.A.; Di Micco, P.; Baroni, A.; Catalanotti, P.; Tufano, M.A. Porins from Salmonella typhimurium accelerate human blood coagulation in vitro by selective stimulation of thrombin activity: Implications in septic shock DIC pathogenesis. J. Endotoxin. Res. 2001, 7, 211–217. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Iba, T.; Levi, M.; Levy, J.H. Sepsis-Induced Coagulopathy and Disseminated Intravascular Coagulation. Semin Thrombhemost 2020, 46, 89–95. [Google Scholar]
- Chang, J.C. Acute Respiratory Distress Syndrome as an Organ Phenotype of Vascular Microthrombotic Disease: Based on Hemostatic Theory and Endothelial Molecular Pathogenesis. Clin. Appl. Thromb. Hemost. 2019, 25, 1–20. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Tang, N.; Li, D.; Wang, X.; Sun, Z. Abnormal coagulation parameters are associated with poor prognosis in patients with novel coronavirus pneumonia. J. Thrombhaemost. 2020, 18. In Press. [Google Scholar] [CrossRef] [Green Version]
- Schutte, T.; Thijs, A.; Smulders, Y.M. Never ignore extremely elevated D-dimer levels: They are specific for serious illness. Neth. J. Med. 2016, 74, 443–448. [Google Scholar] [PubMed]
- Xia, Y.; Zou, L.; Li, D.; Qin, Q.; Hu, H.; Zhou, Y.; Cao, Y. The ability of an improved qSOFA score to predict acute sepsis severity and prognosis among adult patients. Medicine (Baltimore) 2020, 99, e18942. [Google Scholar] [CrossRef]
- Lippi, G.; Plebani, M. Integrated diagnostics: The future of laboratory medicine? Biochem. Med. (Zagreb) 2020, 30, 010501. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zhang, J.; Zhou, L.; Yang, Y.; Peng, W.; Wang, W.; Chen, X. Therapeutic and triage strategies for 2019 novel coronavirus disease in fever clinics. Lancet Respir. Med. 2020, 8, e11–e12. [Google Scholar] [CrossRef] [Green Version]
Patients’ Characteristics | COVID-19 Group N: 67 | Control Group N: 67 | p |
---|---|---|---|
Males, n (%) | 47 (70%) | 35 (52%) | 0.09 |
Age <40 yy, n (%) | 2 (3%) | 3 (4%) | 0.67 |
Age 40–60 yy, n (%) | 19 (28%) | 15 (22%) | 0.74 |
Age >60 yy, n (%) | 46 (68%) | 49 (73%) | 0.09 |
Cardiovascular diseases, n (%) | 28 (41%) | 25 (37%) | 0.99 |
Concomitant Antiplatelets Drugs, n (%) | 22 (32%) | 30 (44%) | 0.06 |
Concomitant Anticoagulants Drugs, n (%) | 6 (9%) | 10 (14%) | 0.12 |
Asymptomatic Pneumonia, n (%) | 2 (3%) | 0 (0%) | 0.24 |
Abnormal PT sec, n (%) | 16 (23%) | 7 (10%) | 0.09 |
Abnormal aPTT, n (%) | 2 (3%) | 1 (2%) | 0.73 |
D-dimer>500–700 mcg/dL, n (%) | 54 (80%) | 40 (59%) | 0.09 |
Fibrinogen >400 mg/dL, n (%) | 58 (86%) | 39 (58%) | 0.005 |
Parameter | COVID-19 Group | Control Group | FPTest p-Value | FKTest p-Value |
---|---|---|---|---|
PT seconds | 11(10.0–13.0) | 11(10.0–13.5) | 0.39 | 0.23 |
aPTT | 0.96(0.85–1.07) | 0.98(0.88–1.06) | 0.16 | 0.08 |
PLT(mmcube) | 360(244–413.5) | 323(272–371) | 0.28 | 0.13 |
CRP(mg/dL) | 13.46(5.63–25.83) | 11.00(6.00–25.00) | 0.38 | 0.88 |
Fibrinogen (mg/dL) | 622(448–796) | 455(352.5–588.5) | 0.0000064 | 0.71 |
D-dimer (mcg/dL) | 556(327–859) | 500(260 -650) | 0.10 | 0.15 |
Patients’ Characteristics | COVID-19 with SARS N: 24 | COVID-19 without SARS N: 43 | p |
---|---|---|---|
Males, n (%) | 15 (60%) | 30 (69%) | 0.73 |
Age <40 yy, n (%) | (0%) | 2 (4%) | 0.41 |
Age 40–60 yy, n (%) | 11 (45%) | 19 (44%) | 0.99 |
Age >60 yy, n (%) | 13 (54%) | 24 (54%) | 0.99 |
Cardiovascular diseases, n (%) | 14 (58%) | 14 (32%) | 0.07 |
Concomitant Antiplatelets Drugs, n (%) | 8 (33%) | 14 (32%) | 0.99 |
Concomitant Anticoagulants Drugs, n (%) | 1 (4%) | 2 (4%) | 0.99 |
Abnormal PT, n (sec.) | 8 33%) | 9 (20%) | 0.03 |
Abnormal aPTT, n (%) | 0 (0%) | 2 (4%) | 0.73 |
D-dimer >500–700 mcg/dL, n (%) | 21 (91%) | 33 (76%) | 0.41 |
Fibrinogen >400 mg/dL, n (%) | 22 (92%) | 35 (81%) | 0.81 |
Parameter | COVID-19 with SARS | COVID-19 without SARS | FP-Test p-Value | FK-Test p-Value |
---|---|---|---|---|
PT seconds | 1.17(1.10–1.27) | 1.15(1.10–1.22) | 0.56 | 0.45 |
aPTT | 0.92(0.81–1.12) | 0.89(0.80–1.04) | 0.14 | 0.62 |
PLT(mmcube) | 320(210–595) | 346(191–605) | 0.32 | 0.15 |
CRP(mg/dL) | 62(31–95) | 55(28–93) | 0.46 | 0.96 |
Fibrinogen (mg/dL) | 747(600.0–834.0) | 567(472.5–644.50) | 0.0003 | 0.48 |
D-dimer (mcg/dL) | 633(484–2324) | 500(281.75–740.50) | 0.075 | 0.21 |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Di Micco, P.; Russo, V.; Carannante, N.; Imparato, M.; Rodolfi, S.; Cardillo, G.; Lodigiani, C. Clotting Factors in COVID-19: Epidemiological Association and Prognostic Values in Different Clinical Presentations in an Italian Cohort. J. Clin. Med. 2020, 9, 1371. https://doi.org/10.3390/jcm9051371
Di Micco P, Russo V, Carannante N, Imparato M, Rodolfi S, Cardillo G, Lodigiani C. Clotting Factors in COVID-19: Epidemiological Association and Prognostic Values in Different Clinical Presentations in an Italian Cohort. Journal of Clinical Medicine. 2020; 9(5):1371. https://doi.org/10.3390/jcm9051371
Chicago/Turabian StyleDi Micco, Pierpaolo, Vincenzo Russo, Novella Carannante, Michele Imparato, Stefano Rodolfi, Giuseppe Cardillo, and Corrado Lodigiani. 2020. "Clotting Factors in COVID-19: Epidemiological Association and Prognostic Values in Different Clinical Presentations in an Italian Cohort" Journal of Clinical Medicine 9, no. 5: 1371. https://doi.org/10.3390/jcm9051371