Diabetes is a risk factor for the progression and prognosis of COVID‐19
Open accessAbstract
Backgound: To figure out whether diabetes is a risk factor influencing the progression and prognosis of 2019 novel coronavirus disease (COVID‐19). Methods: A total of 174 consecutive patients confirmed with COVID‐19 were studied. Demographic data, medical history, symptoms and signs, laboratory findings, chest computed tomography (CT) as well the treatment measures were collected and analysed. Results: We found that COVID‐19 patients without other comorbidities but with diabetes (n = 24) were at higher risk of severe pneumonia, release of tissue injury‐related enzymes, excessive uncontrolled inflammation responses and hypercoagulable state associated with dysregulation of glucose metabolism. Furthermore, serum levels of inflammation‐related biomarkers such as IL‐6, C‐reactive protein, serum ferritin and coagulation index, D‐dimer, were significantly higher (P < .01) in diabetic patients compared with those without, suggesting that patients with diabetes are more susceptible to an inflammatory storm eventually leading to rapid deterioration of COVID‐19. Conclusions: Our data support the notion that diabetes should be considered as a risk factor for a rapid progression and bad prognosis of COVID‐19. More intensive attention should be paid to patients with diabetes, in case of rapid deterioration.
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Aging, obesity and inflammation-related diseases such as diabetes and cardiovascular diseases are risk factors for the severity of COVID-19.
“Of note, aging, obesity and inflammation-related diseases such as diabetes and cardiovascular diseases have been shown to be risk factors for the severity of COVID-19 (293, 371–373).”
From IL-6 in inflammation, autoimmunity and cancer (2021) · cites this paper as [372]
The Abstract Results and Discussion report that patients with diabetes had more severe COVID-19 pneumonia and a poorer prognosis. The Discussion links diabetes and obesity to inflammation, and the Results note cardiovascular disease among patients with diabetes, but the paper does not establish aging, obesity, or cardiovascular disease individually as risk factors for COVID-19 severity. Page numbers are not provided in our copy. (LLM, conf=0.88)
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Cites
Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation
Wrapp, D., Wang, N., Corbett, K. S., Goldsmith, J. A., Hsieh, C.-L., Abiona, O., Graham, B. S., & McLellan, J. S. (2020) · Science · doi:10.1126/science.abb2507 · Cited by 8,897 · see citing works
A crucial role of angiotensin converting enzyme 2 (ACE2) in SARS coronavirus–induced lung injury
Kuba, K., Imai, Y., Rao, S., Gao, H., Guo, F., Guan, B., Huan, Y., Yang, P., Zhang, Y., Deng, W., et al. (2005) · Nature Medicine · doi:10.1038/nm1267 · Cited by 3,445 · see citing works
Role of the ACE2/angiotensin 1-7 axis of the renin-angiotensin system in heart failure
Patel, V. B., Zhong, J.-C., Grant, M. B., & Oudit, G. Y. (2016) · Circulation Research · doi:10.1161/circresaha.116.307708 · Cited by 833 · see citing works
Flagged first, then by citations
Research works printed but not linked: 18
- [1]Chen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020; 395(10223): 507‐ 513. 32007143 PMC7135076
- [5]Tipnis SR, Hooper NM, Hyde R, Karran E, Christie G, Turner AJ. A human homolog of angiotensin‐converting enzyme. Cloning and functional expression as a captopril‐insensitive carboxypeptidase. J Biol Chem. 2000; 275(43): 33238‐ 33243. 10924499
- [6]Knapp S. Diabetes and infection: is there a link?—a mini‐review. Gerontology. 2013; 59(2): 99‐ 104. 23182884
- [7]Shah BR, Hux JE. Quantifying the risk of infectious diseases for people with diabetes. Diabetes Care. 2003; 26(2): 510‐ 513. 12547890
- [8]Muller LM, Gorter KJ, Hak E, et al. Increased risk of common infections in patients with type 1 and type 2 diabetes mellitus. Clin Infect Dis. 2005; 41(3): 281‐ 288. 16007521
- [9]Joshi N, Caputo GM, Weitekamp MR, Karchmer AW. Infections in patients with diabetes mellitus. N Engl J Med. 1999; 341(25): 1906‐ 1912. 10601511
- [10]Hodgson K, Morris J, Bridson T, Govan B, Rush C, Ketheesan N. Immunological mechanisms contributing to the double burden of diabetes and intracellular bacterial infections. Immunology. 2015; 144(2): 171‐ 185. 25262977 PMC4298412
- [11]Yang JK, Feng Y, Yuan MY, et al. Plasma glucose levels and diabetes are independent predictors for mortality and morbidity in patients with SARS. Diabetic Med. 2006; 23(6): 623‐ 628. 16759303
- [12]Wang D, Hu B, Hu C, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus‐infected pneumonia in Wuhan, China. JAMA. 2020; 323: 1061. 32031570 PMC7042881
- [13]W‐j G, Liang W‐h, Zhao Y, et al. Comorbidity and its impact on 1,590 patients with COVID‐19 in China: a Nationwide analysis. medRxiv. 2020. PMC7098485 32217650
- [14]Guzman‐Flores JM, Lopez‐Briones S. Cells of innate and adaptive immunity in type 2 diabetes and obesity. Gaceta Medica de Mexico. 2012; 148(4): 381‐ 389. 22976756
- [15]Shu CJ, Benoist C, Mathis D. The immune system's involvement in obesity‐driven type 2 diabetes. Semin Immunol. 2012; 24(6): 436‐ 442. 23333525 PMC3582811
- [16]Meshkani R, Vakili S. Tissue resident macrophages: Key players in the pathogenesis of type 2 diabetes and its complications. Clin Chim Acta. 2016; 462: 77‐ 89. 27570063
- [17]Jaeckel E, Manns M, Von Herrath M. Viruses and diabetes. Ann N Y Acad Sci. 2002; 958: 7‐ 25. 12021080
- [18]Jali MV, Shankar PS. Transient diabetes following chicken pox. J Assoc Physicians India. 1990; 38(9): 663‐ 664. 2266090
- [19]Yang JK, Lin SS, Ji XJ, Guo LM. Binding of SARS coronavirus to its receptor damages islets and causes acute diabetes. Acta Diabetol. 2010; 47(3): 193‐ 199. 19333547 PMC7088164
- [20]Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020; 395(10223): 497‐ 506. 31986264 PMC7159299
- [21]Tanaka T, Narazaki M, Kishimoto T. Immunotherapeutic implications of IL‐6 blockade for cytokine storm. Immunotherapy. 2016; 8(8): 959‐ 970. 27381687
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Sorted by citations
Impact of COVID-19 pandemic on mental health in the general population: a systematic review
Xiong, J., Lipsitz, O., Nasri, F., Lui, L. M. W., Gill, H., Phan, L., Chen-Li, D., Iacobucci, M., Ho, R., Majeed, A., et al. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.08.001 · Cited by 5,204 · see citing works
IL-6 in inflammation, autoimmunity and cancer
Hirano, T. (2021) · International Immunology · doi:10.1093/intimm/dxaa078 · Cited by 1,453 · see citing works
Mao, R., Qiu, Y., He, J.-S., Tan, J.-Y., Li, X.-H., Liang, J., Shen, J., Zhu, L.-R., Chen, Y., Iacucci, M., et al. (2020) · The Lancet Gastroenterology & Hepatology · doi:10.1016/s2468-1253(20)30126-6 · Cited by 1,056 · see citing works
Kell, D. B., Heyden, E. L., & Pretorius, E. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.01221 · Cited by 460 · see citing works
Coronavirus infections and type 2 diabetes-shared pathways with therapeutic implications
Drucker, D. J. (2020) · Endocrine Reviews · doi:10.1210/endrev/bnaa011 · Cited by 399 · see citing works
Chemistry and biology of ferritin
Plays, M., Müller, S., & Rodriguez, R. (2021) · Metallomics · doi:10.1093/mtomcs/mfab021 · Cited by 232 · see citing works
The Role of Nutrition in COVID-19 Susceptibility and Severity of Disease: A Systematic Review
James, P. T., Ali, Z., Armitage, A. E., Bonell, A., Cerami, C., Drakesmith, H., Jobe, M., Jones, K. S., Liew, Z., Moore, S. E., et al. (2021) · The Journal of Nutrition · doi:10.1093/jn/nxab059 · Cited by 147 · see citing works
Khera, A., Baum, S. J., Gluckman, T. J., Gulati, M., Martin, S. S., Michos, E. D., Navar, A. M., Taub, P. R., Toth, P. P., Virani, S. S., et al. (2020) · American Journal of Preventive Cardiology · doi:10.1016/j.ajpc.2020.100009 · Cited by 143 · see citing works
Type 2 diabetes mellitus and COVID-19: a narrative review
Corrao, S., Pinelli, K., Vacca, M., Raspanti, M., & Argano, C. (2021) · Frontiers in Endocrinology · doi:10.3389/fendo.2021.609470 · Cited by 97 · see citing works
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Pita Costa, J., Grobelnik, M., Fuart, F., Stopar, L., Epelde, G., Fischaber, S., Poliwoda, P., Rankin, D., Wallace, J., Black, M., et al. (2020) · IEEE Computational Intelligence Magazine · doi:10.1109/mci.2020.3019898 · Cited by 29 · see citing works
Yin, W., Liu, Y., Hu, H., Sun, J., Liu, Y., & Wang, Z. (2022) · PLOS ONE · doi:10.1371/journal.pone.0275251 · Cited by 27 · see citing works
Rinderknecht, M. D., & Klopfenstein, Y. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00482-9 · Cited by 23 · see citing works
Is a Cloud-Based Platform Useful for Diabetes Management in Colombia? The Tidepool Experience
León-Vargas, F., Martin, C., Garcia-Jaramillo, M., Aldea, A., Leal, Y., Herrero, P., Reyes, A., Henao, D., & Gomez, A. M. (2021) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2021.106205 · Cited by 14 · see citing works
- Authors
- Guo, W., Li, M., Dong, Y., Zhou, H., Zhang, Z., Tian, C., Qin, R., Wang, H., Shen, Y., Du, K., Zhao, L., Fan, H., Luo, S., & Hu, D.
- Affiliations
- Guizhou University (CN)
- Wuhan Union Hospital (CN)
- Corresponding author
- Luo, Shanshan
- Hu, Desheng
- ORCID
- Venue
- Diabetes/Metabolism Research and Reviews
- Publisher
- Wiley
- Published
- 2020-04-07
- Volume
- 36
- Issue
- 7
- Pages
- e3319-e3319
- ISSN
- 1520-7552 (ISSN-L)
- 1520-7560
- PMC
- PMC7228407
- OpenAlex
- W3013283620
- Cited by
- 1,404
- References
- 3
- Citations by year
- 2026: 13 · 2025: 54 · 2024: 111 · 2023: 152 · 2022: 241 · 2021: 406 · 2020: 426 · 2019: 1
- FWCI
- 40.18
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Diabetes/Metabolism Research and Reviews (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (31770983, 81601747, 81974249)
- Topics
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Health Sciences › Medicine › Neurology › Long-Term Effects of COVID-19
- Keywords
- COVID-19 pandemic, diabetes mellitus, risk factors, disease progression, prognosis, severe pneumonia, inflammation, hypercoagulability, D-dimer, interleukin-6, C-reactive protein, serum ferritin, glucose metabolism
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