Diabetes mellitus and new coronavirus infection: a look into the past; conclusions on prevention and treatment tactics for the future

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In December 2019; there was an outbreak of a new coronavirus infection (NCI) COVID-19 in China; which then developed into a pandemic. Almost immediately after the advent of NCI; it became apparent that the presence of chronic diseases; such as diabetes mellitus (DM); plays a key role in the outcome of the disease for infected patients. Based on the results of numerous studies; we concluded that the risks of complications and death in NCI with the presence of diabetes increase significantly. Scientists have shown that; a persona-lized approach; which consists of selecting an optimal treatment regimen for diabetes during the period of NCI; creating the necessary conditions for the prevention of NCI; and developing a strategy for general vaccination of the population is required for the successful management of patients in this cohort.

Objective: to determine an effective strategy for the treatment and prevention of NCI in comorbid patients based on an analysis of domestic and foreign studies.

Methods. In the process of searching for information; articles that were published over the last 4 years (2019–2023) were studied. A review of more than 90 scientific papers including systematic reviews; meta-analyses; and articles was conducted.

Conclusion. NCI is a serious infectious disease; which; in the presence of comorbid conditions such as diabetes; occurs with an increased risk of mortality and severity of the patient’s condition. To reduce the consequences of the pandemic and effectively prevent new outbreaks; the development of new treatment algorithms and their implementation in clinical practice; early routine monitoring and determination of subsequent vaccination tactics are required.

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作者简介

Liana Aramisova

Kabardino-Balkarian State University n.a. Kh.M. Berbekov

编辑信件的主要联系方式.
Email: iaramisova@gmail.com
ORCID iD: 0000-0001-8105-4235
SPIN 代码: 8233-5939

2nd-year postgraduate student, Department of Faculty Therapy, Medical Academy

俄罗斯联邦, Nalchik

I. Zhurtova

Kabardino-Balkarian State University n.a. Kh.M. Berbekov

Email: liaramisova@gmail.com
ORCID iD: 0000-0003-0668-1073

Department of Faculty Therapy, Medical Academy

俄罗斯联邦, Nalchik

A. Gubachikova

Kabardino-Balkarian State University n.a. Kh.M. Berbekov

Email: liaramisova@gmail.com
ORCID iD: 0000-0002-0017-011X

Department of Faculty Therapy, Medical Academy

俄罗斯联邦, Nalchik

参考

  1. World Health Organization Dashboard covid19; Diabetes. Date accessed: July 26; 2023.
  2. Poorolajal J. The global pandemics are getting more frequent and severe. J Res Health Sci. 2021;21(1):e00502. doi: 10.34172/jrhs.2021.40.
  3. IDF Diabetes Atlas 10th edition 2021.
  4. Mantovani A.; Byrne C.D.; Zheng M.H. Diabetes as a risk factor for greater COVID-19 severity and in-hospital death: A meta-analysis of observational studies. Nutr Metab Cardiovasc. Dis. 2020;30:1236–48. doi: 10.1016/j.numecd.2020.05.014.
  5. Hartmann-Boyce J.; Morris E.; Goyder C.; et al. Diabetes and COVID-19: risks; management; and learnings from other national disasters. Diab Care. 2020;43(8):1695–703. Doi: 10.2337 /dc20-1192.
  6. Steenblock C.; Schwarz P.E.H.; Ludwig B.; et al. COVID-19 and metabolic disease: mechanisms and clinical management. Lancet. Diab Endocrinol. 2021;9(11):786–98. doi: 10.1016/S2213-858.
  7. Qahtani A.A. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2): emergence; history; basic and clinical aspects. Saudi J Biol Sci. 2020;27:2531–38. doi: 10.1016/j.sjbs.2020.04.033.
  8. You J.H.; Lee S.A.; Chun S.Y.; et al. Clinical outcomes of COVID-19 patients with type 2 diabetes: a population-based study in Korea. Endocrinol Metabol. 2020;35(4):901–8. Doi: 10.3803 /EnM.2020.787.
  9. Izzi-Engbeaya C.; Distaso W.; Amin A.; et al. Adverse outcomes in COVID-19 and diabetes: a retrospective cohort study from three London teaching hospitals. BMJ. Open Diab Res Care. 2021;9(1). doi: 10.1136/bmjdrc-2020-001858.
  10. Holman N.; Knighton P.; Kar P.; et al. Risk factors for COVID-19-related mortality in people with type 1 and type 2 diabetes in England: a population-based cohort study. Lancet. Diab Endocrinol. 2020;8(10):823–33. Doi: 10.1016 /S2213-8587 (20)30271-0.
  11. Varikasuvu S.R.; Dutt N.; Thangappazham B.; Varshney S. Diabetes and COVID-19: a pooled analysis related to disease severity and mortality. Prim Care Diabetes. 2021;15(1):24–7. doi: 10.1016/j.pcd.2020.08.015.
  12. Hussain S.; Baxi H.; Chand Jamali M.; et al. Burden of diabetes mellitus and its impact on COVID-19 patients: a meta-analysis of real-world evidence. Diab Metab Syndr. 2020;14(6):1595–602. doi: 10.1016/j.dsx.2020.08.014.
  13. Lukito A.A.; Pranata R.; Henrina J.; et al. The effect of metformin consumption on mortality in hospitalized COVID-19 patients: a systematic review and meta-analysis. Diab Metab Syndr. 202014(6):2177–83. doi: 10.1016/j.dsx.2020.11.006.
  14. Nassar M.; Abosheaishaa H.; Singh A.K.; et al. Noninsulin-based antihyperglycemic medications in patients with diabetes and COVID-19: A systematic review and meta-analysis. J Diab. 2023;15(2):86–96. doi: 10.1111/1753-0407.13359.
  15. Neal B.; Perkovic V.; Mahaffey K.W.; et al. Canagliflozin and cardiovascular and renal events in type 2 diabetes. N Engl J Med. 2017;377 (7):644–57. doi: 10.1056/NEJMc1712572.
  16. Usman M.S.; Siddiqi T.J.; Anker S.D.; et al. Effect of SGLT2 Inhibitors on Cardiovascular Outcomes Across Various Patient Populations. J Am Coll Cardiol. 2023;81(25):2377–87. doi: 10.1016/j.jacc.2023.04.034.
  17. Kosiborod M.N.; Esterline R.; Furtado R.H.M.; et al. Dapagliflozin in patients with cardiometabolic risk factors hospitalised with COVID-19 (DARE-19): a randomised; double-blind; placebo-controlled; phase 3 trial. Lancet. Diab Endocrinol. 2021;9(9):586–94. doi: 10.1016/S2213-8587 (21)00180-7.
  18. Han T.; Ma S.; Sun C.; et al. Association between anti-diabetic agents and clinical outcomes of COVID-19 in patients with diabetes: a systematic review and meta-analysis. Arch Med Res. 2022;53(2):186–95. doi: 10.1016/j.arcmed.2021.08.002.
  19. Hariyanto T.I.; Kurniawan A. Dipeptidyl peptidase 4 (DPP4) inhibitor and outcome from coronavirus disease 2019 (COVID-19) in diabetic patients: a systematic review; meta-analysis; and meta-regression. J Diab Metab Disord. 2021;20(1):543–50. doi: 10.1007/s40200-021-00777-4.
  20. Yang Y.; Cai Z.; Zhang J. Insulin Treatment May Increase Adverse Outcomes in Patients With COVID-19 and Diabetes: A Systematic Review and Meta-Analysis. Front. Endocrinol. (Lausanne). 2021;12:696087. doi: 10.3389/fendo.2021.696087.
  21. Hariyanto T.I.; Intan D.; Hananto J.E.; et al. Pre-admission glucagon-like peptide-1 receptor agonist (GLP-1RA) and mortality from coronavirus disease 2019 (Covid-19): a systematic review; meta-analysis; and meta-regression. Diab Res Clin Pract. 2021;179:109031. doi: 10.1016/j.diabres.2021.109031.
  22. Khunti K.; Knighton P.; Zaccardi F.; et al. Prescription of glucose-lowering therapies and risk of COVID-19 mortality in people with type 2 diabetes: a nationwide observational study in England. Lancet. Diab Endocrinol. 2021;9(5):293–303. doi: 10.1016/S2213-8587(21)00050-4.
  23. Miller J.L; Tada M.; Goto M.; et al. Prediction models for severe manifestations and mortality due to COVID-19: A systematic review. Acad Emerg Med Care. 2022;29(2):206–16. doi: 10.1111/acem.14447.
  24. Hippisley-Cox J.; Coupland C.A.; Mehta N.; et al. Risk prediction of covid-19 related death and hospital admission in adults after covid-19 vaccination: national prospective cohort study. BMJ. 2021;374:n2244. doi: 10.1136/bmj.n2244.
  25. Wang Y.; Duan L.; Li M.; et al. COVID-19 Vaccine Hesitancy and Associated Factors among Diabetes Patients: A Cross-Sectional Survey in Changzhi; Shanxi; China. Vaccines (Basel). 2022;10(1):129. doi: 10.3390/vaccines10010129.
  26. Kaine G.; Wright V.; Greenhalgh S. Predicting willingness to be vaccinated for Covid-19: Evidence from New Zealand. PLoS One. 2022;17(4) e0266485. doi: 10.1371/journal.pone.0266485.
  27. Guaraldi F.; Montalti M.; Di Valerio Z.; et al. Rate and Predictors of Hesitancy toward SARS-CoV-2 Vaccine among Type 2 Diabetic Patients: Results from an Italian Survey. Vaccines (Basel). 2021;9(5):460. doi: 10.3390/vaccines9050460.
  28. Patwary M.M.; Alam M.A.; Bardhan M.; et al. COVID-19 Vaccine Acceptance among Lowand Lower-Middle-Income Countries: A Rapid Systematic Review and Meta-Analysis. Vaccines (Basel). 2022;10(3):427. doi: 10.3390/vaccines10030427.
  29. Ekpor E.; Akyirem S. Global acceptance of COVID-19 vaccine among persons with diabetes: A systematic review and meta-analysis. Diab Res Clin Pract. 2023;201:110731. doi: 10.1016/j.diabres.2023.110731.
  30. Alsaleh F.M.; Elzain M.; Alsairafi Z.K.; Naser A.Y. Perceived Knowledge; Attitude; and Practices (KAP) and Fear toward COVID-19 among Patients with Diabetes Attending Primary Healthcare Centers in Kuwait. Int J Environ Res Public Health. 2023;20(3):2369. doi: 10.3390/ijerph20032369.
  31. Nguyen K.H.; Srivastav A.; Razzaghi H.; et al. COVID-19 Vaccination Intent; Perceptions; and Reasons for Not Vaccinating Among Groups Prioritized for Early Vaccination – United States; September and December 2020. MMWR. Morb Mortal Wkly Rep. 2021;70(6):217–22. doi: 10.15585/mmwr.mm7006e3.
  32. Norhayati M.N.; Che Yusof R.; Azman Y.M. Systematic Review and Meta-Analysis of COVID-19 Vaccination Acceptance. Front Med. (Lausanne) 2022;8. doi: 10.3389/fmed.2021. 783982.
  33. Wang Q.; Hu S.; Du F.; et al. Mapping global acceptance and uptake of COVID-19 vaccination: A systematic review and meta-analysis. Commun Med (Lond) 2022;2:113. doi: 10.1038/s43856-022-00177-6.
  34. Prabani K.I.P.; Weerasekara I.; Damayanthi H.D.W.T. COVID-19 vaccine acceptance and hesitancy among patients with cancer: a systematic review and meta-analysis. Public Health. 2022; 212:66–75.
  35. Zhao Y.; Du J.; Li Z.; et al. It Is Time to Improve the Acceptance of COVID-19 Vaccines Among People with Chronic Diseases: A Systematic Review and Meta-analysis 2023 Jan 19. J Med Virol. 2023;10.1002/jmv.28509.

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