The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Hematological findings and complications of COVID‐19
Open accessAbstract
COVID‐19 is a systemic infection with a significant impact on the hematopoietic system and hemostasis. Lymphopenia may be considered as a cardinal laboratory finding, with prognostic potential. Neutrophil/lymphocyte ratio and peak platelet/lymphocyte ratio may also have prognostic value in determining severe cases. During the disease course, longitudinal evaluation of lymphocyte count dynamics and inflammatory indices, including LDH, CRP and IL‐6 may help to identify cases with dismal prognosis and prompt intervention in order to improve outcomes. Biomarkers, such high serum procalcitonin and ferritin have also emerged as poor prognostic factors. Furthermore, blood hypercoagulability is common among hospitalized COVID‐19 patients. Elevated D‐Dimer levels are consistently reported, whereas their gradual increase during disease course is particularly associated with disease worsening. Other coagulation abnormalities such as PT and aPTT prolongation, fibrin degradation products increase, with severe thrombocytopenia lead to life‐threatening disseminated intravascular coagulation (DIC), which necessitates continuous vigilance and prompt intervention. So, COVID‐19 infected patients, whether hospitalized or ambulatory, are at high risk for venous thromboembolism, and an early and prolonged pharmacological thromboprophylaxis with low molecular weight heparin is highly recommended. Last but not least, the need for assuring blood donations during the pandemic is also highlighted.
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Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30183-5 · Cited by 48,884
Clinical characteristics of coronavirus disease 2019 in China
Guan, W.-J., Ni, Z.-Y., Hu, Y., Liang, W.-H., Ou, C.-Q., He, J.-X., Liu, L., Shan, H., Lei, C.-L., Hui, D. S. C., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2002032 · Cited by 30,246
A novel coronavirus from patients with pneumonia in China, 2019
Zhu, N., Zhang, D., Wang, W., Li, X., Yang, B., Song, J., Zhao, X., Huang, B., Shi, W., Lu, R., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001017 · Cited by 28,244
Zhou, F., Yu, T., Du, R., Fan, G., Liu, Y., Liu, Z., Xiang, J., Wang, Y., Song, B., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30566-3 · Cited by 27,263
Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., Qiu, Y., Wang, J., Liu, Y., Wei, Y., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30211-7 · Cited by 21,415
Association of cardiac injury with mortality in hospitalized patients with COVID-19 in Wuhan, China
Shi, S., Qin, M., Shen, B., Cai, Y., Liu, T., Yang, F., Gong, W., Liu, X., Liang, J., Zhao, Q., et al. (2020) · JAMA Cardiology · doi:10.1001/jamacardio.2020.0950 · Cited by 4,349
High expression of ACE2 receptor of 2019-nCoV on the epithelial cells of oral mucosa
Xu, H., Zhong, L., Deng, J., Peng, J., Dan, H., Zeng, X., Li, T., & Chen, Q. (2020) · International Journal of Oral Science · doi:10.1038/s41368-020-0074-x · Cited by 2,838
Characteristics and outcomes of 21 critically ill patients with COVID-19 in Washington State
Arentz, M., Yim, E., Klaff, L., Lokhandwala, S., Riedo, F. X., Chong, M., & Lee, M. (2020) · JAMA · doi:10.1001/jama.2020.4326 · Cited by 2,259
Deng, Y., Liu, W., Liu, K., Fang, Y.-Y., Shang, J., Zhou, L., Wang, K., Leng, F., Wei, S., Chen, L., et al. (2020) · Chinese Medical Journal · doi:10.1097/cm9.0000000000000824 · Cited by 657
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Gupta, A., Madhavan, M. V., Sehgal, K., Nair, N., Mahajan, S., Sehrawat, T. S., Bikdeli, B., Ahluwalia, N., Ausiello, J. C., Wan, E. Y., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0968-3 · Cited by 3,185
Immunology of COVID-19: Current State of the Science
Vabret, N., Britton, G. J., Gruber, C., Hegde, S., Kim, J., Kuksin, M., Levantovsky, R., Malle, L., Moreira, A., Park, M. D., et al. (2020) · Immunity · doi:10.1016/j.immuni.2020.05.002 · Cited by 1,623
Why does COVID-19 disproportionately affect older people?
Mueller, A. L., McNamara, M. S., & Sinclair, D. A. (2020) · Aging · doi:10.18632/aging.103344 · Cited by 1,128
The hypercoagulable state in COVID-19: Incidence, pathophysiology, and management
Abou-Ismail, M. Y., Diamond, A., Kapoor, S., Arafah, Y., & Nayak, L. (2020) · Thrombosis Research · doi:10.1016/j.thromres.2020.06.029 · Cited by 694
Pretorius, E., Vlok, M., Venter, C., Bezuidenhout, J. A., Laubscher, G. J., Steenkamp, J., & Kell, D. B. (2021) · Cardiovascular Diabetology · doi:10.1186/s12933-021-01359-7 · Cited by 518
Metadata
- Authors
- Terpos, E., Ntanasis‐Stathopoulos, I., Elalamy, I., Kastritis, E., Sergentanis, T. N., Politou, M., Psaltopoulou, T., Gerotziafas, G., & Dimopoulos, M. A.
- Venue
- American Journal of Hematology
- Publisher
- Wiley
- Published
- 2020-05-23
- Volume
- 95
- Issue
- 7
- Pages
- 834-847
- ISSN
- 0361-8609 (ISSN-L)
- 1096-8652
- OpenAlex
- W3016126001
- Cited by
- 1,673
- References
- 9
- FWCI
- 44.60
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Terpos, E., Ntanasis‐Stathopoulos, I., Elalamy, I., Kastritis, E., Sergentanis, T. N., Politou, M., Psaltopoulou, T., Gerotziafas, G., & Dimopoulos, M. A. (2020). Hematological findings and complications of COVID‐19. American Journal of Hematology. https://doi.org/10.1002/ajh.25829
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