Association of COVID-19 with Diabetes: A Systematic Review and Meta-Analysis

doi:10.21203/rs.3.rs-1848430/v1

Emerging evidence suggests that long COVID-19 may lead to a wide range of post-acute sequelae outcomes, including new onset of diabetes. The aim of this meta-analysis was to estimate the incidence of newly diagnosed diabetes in survivors of coronavirus disease-2019 (COVID-19). Multiple electronic databases (MEDLINE, Scopus, Cochrane Central Register of Controlled Trials and the World Health Organization Global Literature on Coronavirus Disease) and clinical trial registries were searched to June 25, 2022, for studies reporting the association of COVID-19 and diabetes. Two investigators independently assessed studies for inclusion. Risk of bias was assessed using the Newcastle-Ottawa Scale. We estimated the effect of COVID-19 on incident diabetes by random-effects meta-analyses using the generic inverse variance method.

We identified 5 eligible studies consisting of 1,130,773 COVID-19 patients and 16,630,187 controls. Median age was 43 years (interquartile range, 1QR: 20–55), and 34.8 % were female. COVID-19 was associated with a 74% higher risk of incident diabetes (risk ratio, 1.74; 95% CI: 1.37; 2.21). The average risk of bias assessment was 7.5. In this systematic review and meta-analysis, COVID-19 was associated with higher risk for developing new onset diabetes among survivors. Active monitoring of glucose dysregulation after recovery from severe acute respiratory syndrome coronavirus 2 (SARSCoV-2) infection is warranted.

COVID-19

diabetes

meta-analysis

The severe acute respiratory syndrome coronavirus 2 (SARSCoV2), the causative strain of coronavirus disease 2019 (COVID-19) was first detected in early December 2019 in Wuhan, China. As of June 6, 2022, more than 520 million COVID-19 cases and 6·3 million deaths were reported globally.¹

Post-COVID or long COVID-19 conditions are a wide range of new, returning, or ongoing health problems that individuals experience after first being infected with the virus that causes COVID-19.² Emerging evidence suggests that long COVID-19 may lead to a wide range of post-acute sequelae outcomes, including new onset of diabetes.^3–8 The exact mechanisms for newly diagnosed of diabetes in individuals with COVID-19 are not well understood, but it is likely that complex interrelated processes are involved, including previous stress hyperglycemia, steroid-induced hyperglycemia, and direct or indirect effects of SARS-CoV-2 on the β-cell of pancreatic islets.^4,6,7

A previous study with more than 180,000 veterans found that patients who survived COVID-19 were 40% more likely to develop diabetes than those who were never diagnosed with COVID-19.⁹ Moreover, another study found that up to 14% of people hospitalized for COVID-19 were diagnosed with diabetes later.¹⁰ However, to date, there is no studies that have systematically explored the association of COVID-19 with new onset diabetes. A previous systematic review and meta-analysis was limited to only a proportion of newly diagnosed diabetes after COVID-19 with no comparison groups.¹⁰ We aim to fill this critical gap in our knowledge by conducting a systematic review and meta-analysis to examine the association of COVID-19 with diabetes.

Results were reported following Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) 2020.¹¹ This study was deemed exempt by the Penn State Institutional Review Board.

Data Sources and Searches

Multiple electronic databases (MEDLINE, Scopus, Cochrane Central Register of Controlled Trials and the World Health Organization Global Literature on Coronavirus Disease) and clinical trial registries were searched to June 25, 2022, for studies reporting the association of COVID-19 and diabetes without language restriction. Clinical trial registries and conference proceedings were also searched. The following Medical Subject Headings and keyword search terms were used; [“diabetes” OR type 2 diabetes OR type 1 diabetes] AND [“SARS-CoV-2” OR “COVID-19” OR “severe acute respiratory syndrome coronavirus-2” OR “coronavirus disease 2019”.]

Study selection

Studies were selected according to Participant (P) Exposure (E) Comparator [C], Outcome (O) Study type (S) [PECOS] criteria:¹²

Participants: Persons of all ages and sex included in studies that investigated incident diabetes in survivors of COVID-19.

Exposure: COVID-19.

Comparison: Non-COVID-19 group.

Outcome of interest: Diabetes.

Study type: Randomized clinical trials (RCT) and observational studies.

Pairs of independent investigators (YZ and DMB) screened the titles and abstracts of all citations. Studies included by either reviewer were retrieved for full-text screening. Independent investigators (YZ and DMB) screened the full-text version of eligible studies. Disagreements in the included papers were resolved by discussion and if necessary, a third investigator (PS) was consulted.

Data Extraction and Quality Assessment

A standardized data extraction form was developed, and two investigators (YZ and DMB) worked independently to extract study details. The following information was extracted: authors name, year of study publication, country, study design, study-level descriptive statistics (mean (SD)/ median (IQR) age in years, proportion (%) female), sample size, number with diabetes, number with COVID-19, outcome assessment, follow-up time, number of controls, risk ratio and 95% confidence interval. Risk of bias was evaluated using Newcastle- Ottawa Scale for observational studies ¹³. Studies with fewer than 5 stars were considered low quality; 5 to 7 stars, moderate quality; and more than 7 stars, high quality.

Data Synthesis and Analysis

Study-level demographics were summarized with descriptive statistics. The primary outcome was incident diabetes in survivors of COVID-19. For studies without measures of associations, a generalized linear mixed model was used to calculate the RR using the number of events and the sample size of each study group.¹⁴ One study Barret et al. (2022) used two different national databases and reported separate results. Therefore, in this circumstance, we separated the effect estimated from Barret et al. study into two studies as one with IQVIA database and the second one with HealthVerity.³

The pooled RR estimate for diabetes risk from each study was weighted by the inverse of its variance (inter-study plus intra-study variances). DerSimonian and Laird (DL) random-effects method was used to estimate the pooled inter-study variance (heterogeneity).¹⁵ Heterogeneity between studies was evaluated with the indicator expressed as percent low (25%), moderate (50%), and high (75%).¹⁶ Due to small number of studies (n<10), we did not pursue subgroup analyses. Publication bias was quantitatively evaluated with Egger’s linear regression and Begg’s rank test^17,18 and qualitatively with funnel plots. Two-sided P < .05 was deemed statistically significant. All statistical analyses were performed with R software version 3.6.2 (R Foundation for Statistical Computing, Vienna, Austria) using Meta and Metafor R packages.

Identified studies

Figure 1 summarizes study selection process. A total of 853 studies were screened. The exclusion process yielded 5 studies^3,5,9,19,20 conducted in 2 countries. Barret et al (2022) was reported in this meta-analysis as two independent studies.³ The baseline characteristics of the studies included in the systematic review are presented in Table 1. Included studies consisted of patients 1,130,773 COVID-19 patients, with median age of 62 years (1QR: 59 – 67), and 34.8 % were female. The average study quality was 7.5 (range 5-9).

Association of COVID-19 and incident diabetes

Of the 6 studies that characterized the risk of incident diabetes among survivors of COVID-19, the pooled point estimates 1.74 (95% CI: 1.37; 2.21, Figure 2), implying a 74% higher risk of diabetes. The between-study variation was high (I²= 96, p<0.0001).

Publication bias and Study heterogeneity

Visual inspection of a funnel plot of the included studies (Figure 3) indicated a slight asymmetry indicative of mild publication bias. Egger’s test (p=0.35) and Begg's test (p=0.19) for publication bias were non-significant, although the number of included studies is small. To balance the funnel plots and adjust for potential publication bias, we conducted Duval and Tweedie's trim and fill test to balance ²¹. The results indicated that if publication bias existed, 2 additional studies will be needed to eliminate bias and the overall effect of COVID-19 on incident diabetes changed from 1.74 (95% CI: 1.37; 2.21) to 1.50 (1.21; 1.89, Figure 4). To identify outlier and influential studies, we further performed influence sensitivity analyses by excluding and replacing one study at a time from the meta-analysis and calculated the RR for the remaining studies ²². No substantial change from any of the pooled RR was observed when other studies were removed in turn, indicating that no individual study had a considerable influence on the pooled estimate. The plots for the analysis estimates are provided in Figure 5.

Principal findings

In this meta-analysis of 6 cohort studies including over 1 million COVID-19 patients, COVID-19 was associated with a 74% higher risk of diabetes compared to the controls without COVID-19. The risk of bias assessment was low.

Previous studies

Our findings are consistent with the previous meta-analysis that assessed the proportion of COVID-19 survivors with diabetes. A 2021 study by Sathish and colleagues assessed a total of 3711 COVID-19 patients with 492 cases of newly diagnosed diabetes from eight studies.¹⁰ In the random-effects meta-analysis model, the estimated pooled proportion of incident diabetes was 14.4% (95% CI: 5.9-25.8%). They, however, noted a high degree of heterogeneity (I²: 98.6%, p<0.001). The weaknesses of the above study, however, included a lack of a control group and a very small study sample size.

Potential mechanisms

Potential pathophysiological mechanisms of new-onset diabetes among COVID-19 survivors are not fully understood. SARS-CoV-2 binds to angiotensin-converting enzyme 2 and transmembrane serine protease 2 receptors, which are expressed in key metabolic organs and tissues, including pancreatic beta cells, adipose tissue, the small intestine, and the kidneys.^23-25 Furthermore, it has been demonstrated that SARS-CoV-2 infection attenuates pancreatic insulin levels and secretion and induces β cell apoptosis.^26,27 Thus, it is plausible that SARS-CoV-2 may cause pleiotropic alterations of glucose metabolism that could lead to incident diabetes or facilitate a rapid transition from the prediabetes state to full-blown diabetes.

Clinical implications of our findings and recommendations.

Given the extraordinary number of COVID-19 survivors globally, the modest increase in diabetes risk could correspond to a drastic rise in the number of people diagnosed with the disease worldwide. Therefore, active monitoring of glucose dysregulation after recovery from severe acute respiratory syndrome coronavirus 2 (SARSCoV-2) infection is warranted. Additionally, there is a need for studies that determine various social determinants of health associated with new onset diabetes. These factors would be critical to developing effective prevention and management strategies for the disease. Lastly, future research could also focus on employing genomics data to stratify acute COVID-19 patients and predict phenotypes of patients at an increased risk of COVID-19- induced diabetes and uncover novel disease mechanisms. Moreover, into the length and severity of COVID-19 infection and the incidence of new onset Diabetes.

Limitations

Our study has some limitations worth noting. First, a high degree of heterogeneity was observed, which could have been caused by pooling studies from different sociodemographic populations. Nevertheless, a random effects model was invoked to derive plausible estimates. Second, it is also a possibility that some individuals in the control groups might have undetected mild or asymptomatic COVID-19 because they had not been tested. Such non-differential misclassification of the exposure may underestimate the strength of the association of COVID-19 with the onset of diabetes. Lastly, due to the limited number of studies included in the present meta-analysis, we did not explore potentials sources of heterogeneity by conducting subgroup analyses or meta-regressions.

In this systematic review and meta-analysis, COVID-19 was a risk factor for developing new onset diabetes among survivors. Active monitoring of glucose dysregulation after recovery from severe acute respiratory syndrome coronavirus 2 (SARSCoV-2) infection is warranted.

Acknowledgments: None

Disclosure of conflicts of interest

All authors have no conflict of interest to disclose as it relates to this research.

Funding Source: There was no external or internal funding to support this study.

Authors' contributions: Designed research (project conception, development of overall research plan, and study oversight): PS and DMB. Data extraction: YZ, PS, and DMB. Analyzed data: PS and DMB. Performed statistical analysis: PS. Wrote the first draft of the manuscript: PS and DMB. Review and editing: PS, LW, VMC and DMB. All authors have read and approved the final manuscript.

Data Availability Statement: All data generated for this study are included in this manuscript.

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Table 1. Meta-analysis characteristics of included cohort studies reporting COVID-19 and risk of diabetes

Author (Year)	Sample Size, N	Female, N (%)	Outcome (Diabetes) assessment	Country	Study Design	Mean age (y)	Total Case, N	Follow-up periods	Median follow-up time (D)	Reported effect sizes: HR/RR (95% CI)	Covariates in the fully - adjusted model	Quality Score	COVID-19 patients	Controls
Rathmann et al (2022)	71730 (35865 pairs)	32732 (45.6%)	ICD-10 codes (E11-E14)	Germany	Retrospective cohort study	42.6	364	March 2020 to January 2021	119	IRR: 1.28 (1.05, 1.57)	Sex, age, health insurance, index month for Covid-19 and comorbidity (obesity, hypertension, hyperlipidaemia, myocardial infarction, stroke)	8	35865	35865
Barret et al (2022)	485358	243102 (50.1%)	ICD-10 codes (E08-E13)	US	Retrospective cohort study	12.3	200	March 2020 to February 2021	NA	HR: 2.66 (1.98, 3.56)	Matched on age, sex, and month of encounter	7	80893	404465
Barret et al (2022)	878878	440024 (50.1%)	ICD-10 codes (E08-E13)	US	Retrospective cohort study	12.7	1973	March 2020 to June 2021	NA	HR: 1.31 (1.20, 1.44)	Age, sex, and month of encounter	7	439439	439439
Xie et al (2022)	4299721	485021 (11.3%)	ICD-10 codes (E08.X to E13.X) or a HbA1c measurement of more than 6·4% (46 mmol/mol)	US	Cohort study	60.9	134873	March 2020 to Sept 2021	352	HR: 1.40 (1.36, 1.44)	Age, race, sex, area deprivation index, BMI, smoking status, use of long-term care, number of outpatient and inpatient encounters, and number of HbA1c measurements; comorbidities including cancer, cardiovascular disease, cerebrovascular disease, chronic lung disease, dementia, HIV, hyperlipidaemia, and peripheral artery disease; laboratory test results including estimated glomerular filtration rate (eGFR) and HbA1c; vital signs including systolic and diastolic blood pressure; and medications including the use of steroids	9	181280	4118441
Wander et al (2022)	2777768	376274 (13.5%)	1) two or more abnormal laboratory values from plasma or serum (random glucose ≥200 mg/dL, fasting glucose ≥126 mg/dL, 2-h glucose from an oral glucose tolerance test ≥200 mg/dL) or whole blood (A1C ≥6.5%); or 2) two outpatient or one inpatient ICD-10 codes of E08–E13; or 3) receipt of an initial and one refill prescription of a glucose-lowering medication.	US	Retrospective cohort study	59	9150	March 2020 to March 2021	120	OR for Male: 2.56 (2.32, 2.83) OR for Female: 1.21 (0.88, 1.68)	Age, race, ethnicity, BMI, tobacco use, and facility location.	9	126710	2651058
Daugherty et al (2021)	9247505	4607112 (49.8%)	ICD-10 codes	US	Retrospective cohort study	42.4	1886	January 2020 to October 2020	95	HR: 2.47 (1.14, 5.37)	Propensity score matching with age, sex, socioeconomic status, race, index month, pre-existing comorbidities, total length of stay as an inpatient in the previous year, previous number of visits to a primary care physician, cardiologist, or nephrologist	5	266586	8980919

No competing interests reported.

Association of COVID-19 with Diabetes: A Systematic Review and Meta-Analysis

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Abstract

Figures

Introduction

Methods

Results

Discussion

Conclusions

Declarations

References

Tables

Additional Declarations

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Version 1