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Published in: BMC Medicine 1/2022

Open Access 01-12-2022 | SARS-CoV-2 | Research article

Risk for newly diagnosed diabetes after COVID-19: a systematic review and meta-analysis

Authors: Ting Zhang, Qimin Mei, Zhaocai Zhang, Joseph Harold Walline, Yecheng Liu, Huadong Zhu, Shuyang Zhang

Published in: BMC Medicine | Issue 1/2022

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Abstract

Background

There is growing evidence that patients recovering after a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may have a variety of acute sequelae including newly diagnosed diabetes. However, the risk of diabetes in the post-acute phase is unclear. To solve this question, we aimed to determine if there was any association between status post-coronavirus disease (COVID-19) infection and a new diagnosis of diabetes.

Methods

We performed a systematic review and meta-analysis of cohort studies assessing new-onset diabetes after COVID-19. PubMed, Embase, Web of Science, and Cochrane databases were all searched from inception to June 10, 2022. Three evaluators independently extracted individual study data and assessed the risk of bias. Random-effects models estimated the pooled incidence and relative risk (RR) of diabetes compared to non-COVID-19 after COVID-19.

Results

Nine studies with nearly 40 million participants were included. Overall, the incidence of diabetes after COVID-19 was 15.53 (7.91–25.64) per 1000 person-years, and the relative risk of diabetes after COVID-19 infection was elevated (RR 1.62 [1.45–1.80]). The relative risk of type 1 diabetes was RR=1.48 (1.26–1.75) and type 2 diabetes was RR=1.70 (1.32–2.19), compared to non-COVID-19 patients. At all ages, there was a statistically significant positive association between infection with COVID-19 and the risk of diabetes: <18 years: RR=1.72 (1.19–2.49), ≥18 years: RR=1.63 (1.26–2.11), and >65 years: RR=1.68 (1.22–2.30). The relative risk of diabetes in different gender groups was about 2 (males: RR=2.08 [1.27–3.40]; females: RR=1.99 [1.47–2.80]). The risk of diabetes increased 1.17-fold (1.02–1.34) after COVID-19 infection compared to patients with general upper respiratory tract infections. Patients with severe COVID-19 were at higher risk (RR=1.67 [1.25–2.23]) of diabetes after COVID-19. The risk (RR=1.95 [1.85–2.06]) of diabetes was highest in the first 3 months after COVID-19. These results remained after taking confounding factors into account.

Conclusions

After COVID-19, patients of all ages and genders had an elevated incidence and relative risk for a new diagnosis of diabetes. Particular attention should be paid during the first 3 months of follow-up after COVID-19 for new-onset diabetes.
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Literature
1.
go back to reference Drake TM, Riad AM, Fairfield CJ, Egan C, Knight SR, Pius R, et al. Characterisation of in-hospital complications associated with COVID-19 using the ISARIC WHO Clinical Characterisation Protocol UK: a prospective, multicentre cohort study. Lancet. 2021;398:223–37.CrossRefPubMedPubMedCentral Drake TM, Riad AM, Fairfield CJ, Egan C, Knight SR, Pius R, et al. Characterisation of in-hospital complications associated with COVID-19 using the ISARIC WHO Clinical Characterisation Protocol UK: a prospective, multicentre cohort study. Lancet. 2021;398:223–37.CrossRefPubMedPubMedCentral
2.
go back to reference Thomas SJ, Moreira ED, Kitchin N, Absalon J, Gurtman A, Lockhart S, et al. Safety and efficacy of the BNT162b2 mRNA Covid-19 vaccine through 6 months. N Engl J Med. 2021;385:1761–73.CrossRefPubMed Thomas SJ, Moreira ED, Kitchin N, Absalon J, Gurtman A, Lockhart S, et al. Safety and efficacy of the BNT162b2 mRNA Covid-19 vaccine through 6 months. N Engl J Med. 2021;385:1761–73.CrossRefPubMed
3.
go back to reference Voysey M, Clemens SAC, Madhi SA, Weckx LY, Folegatti PM, Aley PK, et al. Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK. Lancet. 2021;397:99–111.CrossRefPubMedPubMedCentral Voysey M, Clemens SAC, Madhi SA, Weckx LY, Folegatti PM, Aley PK, et al. Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK. Lancet. 2021;397:99–111.CrossRefPubMedPubMedCentral
5.
go back to reference Rahmati M, Shamsi MM, Khoramipour K, Malakoutinia F, Woo W, Park S, et al. Baseline physical activity is associated with reduced mortality and disease outcomes in COVID-19: a systematic review and meta-analysis. Rev Med Virol. 2022;32:e2349.CrossRefPubMedPubMedCentral Rahmati M, Shamsi MM, Khoramipour K, Malakoutinia F, Woo W, Park S, et al. Baseline physical activity is associated with reduced mortality and disease outcomes in COVID-19: a systematic review and meta-analysis. Rev Med Virol. 2022;32:e2349.CrossRefPubMedPubMedCentral
6.
go back to reference Huang I, Lim MA, Pranata R. Diabetes mellitus is associated with increased mortality and severity of disease in COVID-19 pneumonia - a systematic review, meta-analysis, and meta-regression. Diabetes Metab Syndr. 2020;14:395–403.CrossRefPubMedPubMedCentral Huang I, Lim MA, Pranata R. Diabetes mellitus is associated with increased mortality and severity of disease in COVID-19 pneumonia - a systematic review, meta-analysis, and meta-regression. Diabetes Metab Syndr. 2020;14:395–403.CrossRefPubMedPubMedCentral
7.
go back to reference Kumar A, Arora A, Sharma P, Anikhindi SA, Bansal N, Singla V, et al. Is diabetes mellitus associated with mortality and severity of COVID-19? A meta-analysis. Diabetes Metab Syndr. 2020;14:535–45.CrossRefPubMedPubMedCentral Kumar A, Arora A, Sharma P, Anikhindi SA, Bansal N, Singla V, et al. Is diabetes mellitus associated with mortality and severity of COVID-19? A meta-analysis. Diabetes Metab Syndr. 2020;14:535–45.CrossRefPubMedPubMedCentral
8.
go back to reference Guo L, Shi Z, Zhang Y, Wang C, Do Vale Moreira NC, Zuo H, et al. Comorbid diabetes and the risk of disease severity or death among 8807 COVID-19 patients in China: a meta-analysis. Diabetes Res Clin Pract. 2020;166:108346.CrossRefPubMedPubMedCentral Guo L, Shi Z, Zhang Y, Wang C, Do Vale Moreira NC, Zuo H, et al. Comorbid diabetes and the risk of disease severity or death among 8807 COVID-19 patients in China: a meta-analysis. Diabetes Res Clin Pract. 2020;166:108346.CrossRefPubMedPubMedCentral
9.
go back to reference Rubino F, Amiel SA, Zimmet P, Alberti G, Bornstein S, Eckel RH, et al. New-onset diabetes in Covid-19. N Engl J Med. 2020;383:789–90.CrossRefPubMed Rubino F, Amiel SA, Zimmet P, Alberti G, Bornstein S, Eckel RH, et al. New-onset diabetes in Covid-19. N Engl J Med. 2020;383:789–90.CrossRefPubMed
10.
go back to reference Sathish T, Tapp RJ, Cooper ME, Zimmet P. Potential metabolic and inflammatory pathways between COVID-19 and new-onset diabetes. Diabetes Metab. 2021;47:101204.CrossRefPubMed Sathish T, Tapp RJ, Cooper ME, Zimmet P. Potential metabolic and inflammatory pathways between COVID-19 and new-onset diabetes. Diabetes Metab. 2021;47:101204.CrossRefPubMed
12.
go back to reference Rey-Reñones C, Martinez-Torres S, Martín-Luján FM, Pericas C, Redondo A, Vilaplana-Carnerero C, et al. Type 2 diabetes mellitus and COVID-19: a narrative review. Biomedicines. 2022;10:2089.CrossRefPubMedPubMedCentral Rey-Reñones C, Martinez-Torres S, Martín-Luján FM, Pericas C, Redondo A, Vilaplana-Carnerero C, et al. Type 2 diabetes mellitus and COVID-19: a narrative review. Biomedicines. 2022;10:2089.CrossRefPubMedPubMedCentral
14.
go back to reference Rahmati M, Keshvari M, Mirnasuri S, Yon DK, Lee SW, Il Shin J, et al. The global impact of COVID-19 pandemic on the incidence of pediatric new-onset type 1 diabetes and ketoacidosis: a systematic review and meta-analysis. J Med Virol. 2022;94:5112–27.CrossRefPubMedPubMedCentral Rahmati M, Keshvari M, Mirnasuri S, Yon DK, Lee SW, Il Shin J, et al. The global impact of COVID-19 pandemic on the incidence of pediatric new-onset type 1 diabetes and ketoacidosis: a systematic review and meta-analysis. J Med Virol. 2022;94:5112–27.CrossRefPubMedPubMedCentral
16.
go back to reference Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000;283:2008–12.CrossRefPubMed Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000;283:2008–12.CrossRefPubMed
19.
go back to reference Freeman MF, Tukey JW. Transformations related to the angular and the square root. Ann Math Stat. 1950;21:607–11.CrossRef Freeman MF, Tukey JW. Transformations related to the angular and the square root. Ann Math Stat. 1950;21:607–11.CrossRef
20.
23.
go back to reference Kossmeier M, Tran US, Voracek M. Power-enhanced funnel plots for meta-analysis: the sunset funnel plot; 2019. Kossmeier M, Tran US, Voracek M. Power-enhanced funnel plots for meta-analysis: the sunset funnel plot; 2019.
24.
go back to reference Mathur MB, VanderWeele TJ. Sensitivity analysis for unmeasured confounding in meta-analyses. J Am Stat Assoc. 2020;115:163–72.CrossRefPubMed Mathur MB, VanderWeele TJ. Sensitivity analysis for unmeasured confounding in meta-analyses. J Am Stat Assoc. 2020;115:163–72.CrossRefPubMed
25.
go back to reference Mathur MB, VanderWeele TJ. Methods to address confounding and other biases in meta-analyses: review and recommendations. Annu Rev Public Health. 2022;43:19–35.CrossRefPubMed Mathur MB, VanderWeele TJ. Methods to address confounding and other biases in meta-analyses: review and recommendations. Annu Rev Public Health. 2022;43:19–35.CrossRefPubMed
26.
go back to reference Haneuse S, VanderWeele TJ, Arterburn D. Using the E-value to assess the potential effect of unmeasured confounding in observational studies. JAMA. 2019;321:602–3.CrossRefPubMed Haneuse S, VanderWeele TJ, Arterburn D. Using the E-value to assess the potential effect of unmeasured confounding in observational studies. JAMA. 2019;321:602–3.CrossRefPubMed
28.
go back to reference Team R. R: a language and environment for statistical computing. undefined. 2014. Team R. R: a language and environment for statistical computing. undefined. 2014.
29.
go back to reference Barrett CE. Risk for newly diagnosed diabetes 30 days after SARS-CoV-2 infection among persons aged 18 years — United States, March 1, 2020–June 28, 2021. MMWR Morb Mortal Wkly Rep. 2022;71. Barrett CE. Risk for newly diagnosed diabetes 30 days after SARS-CoV-2 infection among persons aged 18 years — United States, March 1, 2020–June 28, 2021. MMWR Morb Mortal Wkly Rep. 2022;71.
30.
go back to reference Cohen K, Ren S, Heath K, Dasmariñas MC, Jubilo KG, Guo Y, et al. Risk of persistent and new clinical sequelae among adults aged 65 years and older during the post-acute phase of SARS-CoV-2 infection: retrospective cohort study. BMJ. 2022;376:e068414.CrossRefPubMed Cohen K, Ren S, Heath K, Dasmariñas MC, Jubilo KG, Guo Y, et al. Risk of persistent and new clinical sequelae among adults aged 65 years and older during the post-acute phase of SARS-CoV-2 infection: retrospective cohort study. BMJ. 2022;376:e068414.CrossRefPubMed
32.
go back to reference Birabaharan M, Kaelber DC, Pettus JH, Smith DM. Risk of new-onset type 2 diabetes in 600 055 people after COVID-19: a cohort study. Diabetes Obes Metab. 2022;24:1176–9.CrossRefPubMed Birabaharan M, Kaelber DC, Pettus JH, Smith DM. Risk of new-onset type 2 diabetes in 600 055 people after COVID-19: a cohort study. Diabetes Obes Metab. 2022;24:1176–9.CrossRefPubMed
33.
go back to reference Qeadan F, Tingey B, Egbert J, Pezzolesi MG, Burge MR, Peterson KA, et al. The associations between COVID-19 diagnosis, type 1 diabetes, and the risk of diabetic ketoacidosis: a nationwide cohort from the US using the Cerner Real-World Data. PLoS One. 2022;17:e0266809.CrossRefPubMedPubMedCentral Qeadan F, Tingey B, Egbert J, Pezzolesi MG, Burge MR, Peterson KA, et al. The associations between COVID-19 diagnosis, type 1 diabetes, and the risk of diabetic ketoacidosis: a nationwide cohort from the US using the Cerner Real-World Data. PLoS One. 2022;17:e0266809.CrossRefPubMedPubMedCentral
34.
go back to reference Collaborative, Tazare J, Walker AJ, Tomlinson L, Hickman G, Rentsch CT, et al. Rates of serious clinical outcomes in survivors of hospitalisation with COVID-19 in England: a descriptive cohort study within the OpenSAFELY platform. Wellcome Open Research; 2022. Collaborative, Tazare J, Walker AJ, Tomlinson L, Hickman G, Rentsch CT, et al. Rates of serious clinical outcomes in survivors of hospitalisation with COVID-19 in England: a descriptive cohort study within the OpenSAFELY platform. Wellcome Open Research; 2022.
36.
go back to reference Ayoubkhani D, Khunti K, Nafilyan V, Maddox T, Humberstone B, Diamond I, et al. Post-covid syndrome in individuals admitted to hospital with covid-19: retrospective cohort study. BMJ. 2021;372:n693.CrossRefPubMed Ayoubkhani D, Khunti K, Nafilyan V, Maddox T, Humberstone B, Diamond I, et al. Post-covid syndrome in individuals admitted to hospital with covid-19: retrospective cohort study. BMJ. 2021;372:n693.CrossRefPubMed
38.
go back to reference Yang JK, Feng Y, Yuan MY, Yuan SY, Fu HJ, Wu BY, et al. Plasma glucose levels and diabetes are independent predictors for mortality and morbidity in patients with SARS. Diabet Med. 2006;23:623–8.CrossRefPubMed Yang JK, Feng Y, Yuan MY, Yuan SY, Fu HJ, Wu BY, et al. Plasma glucose levels and diabetes are independent predictors for mortality and morbidity in patients with SARS. Diabet Med. 2006;23:623–8.CrossRefPubMed
39.
go back to reference Yang J-K, Lin S-S, Ji X-J, Guo L-M. Binding of SARS coronavirus to its receptor damages islets and causes acute diabetes. Acta Diabetol. 2010;47:193–9.CrossRefPubMed Yang J-K, Lin S-S, Ji X-J, Guo L-M. Binding of SARS coronavirus to its receptor damages islets and causes acute diabetes. Acta Diabetol. 2010;47:193–9.CrossRefPubMed
40.
go back to reference Apicella M, Campopiano MC, Mantuano M, Mazoni L, Coppelli A, Del Prato S. COVID-19 in people with diabetes: understanding the reasons for worse outcomes. Lancet Diabetes Endocrinol. 2020;8:782–92.CrossRefPubMedPubMedCentral Apicella M, Campopiano MC, Mantuano M, Mazoni L, Coppelli A, Del Prato S. COVID-19 in people with diabetes: understanding the reasons for worse outcomes. Lancet Diabetes Endocrinol. 2020;8:782–92.CrossRefPubMedPubMedCentral
41.
go back to reference Kusmartseva I, Wu W, Syed F, Van Der Heide V, Jorgensen M, Joseph P, et al. Expression of SARS-CoV-2 entry factors in the pancreas of normal organ donors and individuals with COVID-19. Cell Metab. 2020;32:1041–1051.e6.CrossRefPubMedPubMedCentral Kusmartseva I, Wu W, Syed F, Van Der Heide V, Jorgensen M, Joseph P, et al. Expression of SARS-CoV-2 entry factors in the pancreas of normal organ donors and individuals with COVID-19. Cell Metab. 2020;32:1041–1051.e6.CrossRefPubMedPubMedCentral
43.
go back to reference Müller JA, Groß R, Conzelmann C, Krüger J, Merle U, Steinhart J, et al. SARS-CoV-2 infects and replicates in cells of the human endocrine and exocrine pancreas. Nat Metab. 2021;3:149–65.CrossRefPubMed Müller JA, Groß R, Conzelmann C, Krüger J, Merle U, Steinhart J, et al. SARS-CoV-2 infects and replicates in cells of the human endocrine and exocrine pancreas. Nat Metab. 2021;3:149–65.CrossRefPubMed
44.
go back to reference Fabbri A, Marchesini G, Benazzi B, Morelli A, Montesi D, Bini C, et al. Stress hyperglycemia and mortality in subjects with diabetes and sepsis. Crit Care Explor. 2020;2:e0152.CrossRefPubMedPubMedCentral Fabbri A, Marchesini G, Benazzi B, Morelli A, Montesi D, Bini C, et al. Stress hyperglycemia and mortality in subjects with diabetes and sepsis. Crit Care Explor. 2020;2:e0152.CrossRefPubMedPubMedCentral
45.
go back to reference de Carvalho VF, Guedes Cocate P, Gonçalves Pereira L, de Cássia Gonçalves Alfenas R. The role of hyperglycemia in the induction of oxidative stress and inflammatory process. Nutr Hosp. 2012;27:1391–8. de Carvalho VF, Guedes Cocate P, Gonçalves Pereira L, de Cássia Gonçalves Alfenas R. The role of hyperglycemia in the induction of oxidative stress and inflammatory process. Nutr Hosp. 2012;27:1391–8.
46.
go back to reference Dave GS, Kalia K. Hyperglycemia induced oxidative stress in type-1 and type-2 diabetic patients with and without nephropathy. Cell Mol Biol (Noisy-le-grand). 2007;53:68–78. Dave GS, Kalia K. Hyperglycemia induced oxidative stress in type-1 and type-2 diabetic patients with and without nephropathy. Cell Mol Biol (Noisy-le-grand). 2007;53:68–78.
47.
go back to reference Mariatulqabtiah AR, Buttigieg KR. COVID-19 vaccinations for children. Lancet Infect Dis. 2022;S1473-3099(22):00414–5. Mariatulqabtiah AR, Buttigieg KR. COVID-19 vaccinations for children. Lancet Infect Dis. 2022;S1473-3099(22):00414–5.
49.
go back to reference Deeks JJ, Dinnes J, D'Amico R, Sowden AJ, Sakarovitch C, Song F, et al. Evaluating non-randomised intervention studies. Health Technol Assess. 2003;7. Deeks JJ, Dinnes J, D'Amico R, Sowden AJ, Sakarovitch C, Song F, et al. Evaluating non-randomised intervention studies. Health Technol Assess. 2003;7.
50.
go back to reference Van Der Weele TJ, Ding P. Sensitivity analysis in observational research: introducing the E-value. Ann Intern Med. 2017;167:268–74.CrossRef Van Der Weele TJ, Ding P. Sensitivity analysis in observational research: introducing the E-value. Ann Intern Med. 2017;167:268–74.CrossRef
51.
go back to reference Rathmann W, Bongaerts B, Carius H-J, Kruppert S, Kostev K. Basic characteristics and representativeness of the German Disease Analyzer database. Int J Clin Pharmacol Ther. 2018;56:459–66.CrossRefPubMed Rathmann W, Bongaerts B, Carius H-J, Kruppert S, Kostev K. Basic characteristics and representativeness of the German Disease Analyzer database. Int J Clin Pharmacol Ther. 2018;56:459–66.CrossRefPubMed
53.
go back to reference Herbert A, Wijlaars L, Zylbersztejn A, Cromwell D, Hardelid P. Data resource profile: Hospital Episode Statistics Admitted Patient Care (HES APC). Int J Epidemiol. 2017;46:1093–1093i.CrossRefPubMedPubMedCentral Herbert A, Wijlaars L, Zylbersztejn A, Cromwell D, Hardelid P. Data resource profile: Hospital Episode Statistics Admitted Patient Care (HES APC). Int J Epidemiol. 2017;46:1093–1093i.CrossRefPubMedPubMedCentral
Metadata
Title
Risk for newly diagnosed diabetes after COVID-19: a systematic review and meta-analysis
Authors
Ting Zhang
Qimin Mei
Zhaocai Zhang
Joseph Harold Walline
Yecheng Liu
Huadong Zhu
Shuyang Zhang
Publication date
01-12-2022
Publisher
BioMed Central
Published in
BMC Medicine / Issue 1/2022
Electronic ISSN: 1741-7015
DOI
https://doi.org/10.1186/s12916-022-02656-y

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