Risks of and From SARS-CoV-2 Infection and COVID-19 in People With Diabetes: A Systematic Review of Reviews

Impact of Diabetes on COVID-19 Susceptibility: A Nationwide Propensity Score Matching Study

Prior research has highlighted poor clinical outcomes in coronavirus disease 2019 (COVID-19)-infected patients with diabetes; however, susceptibility to COVID-19 infection in patients with diabetes has not been extensively studied. Participants aged ≥30 years who underwent COVID-19 testing from December 2019 to April 2020 were analyzed using the National Health Insurance Service data in South Korea. In a cohort comprising 29,433 1:1 propensity score-matched participants, COVID-19 positivity was significantly higher in participants with diabetes than in those without diabetes (512 [3.5%] vs. 395 [2.7%], P<0.001). Logistic regression analysis indicated that diabetes significantly increased the risk of COVID-19 test positivity (odds ratio, 1.307; 95% confidence interval, 1.144 to 1.493; P<0.001). Patients with diabetes exhibited heightened COVID-19 infection rates compared to individuals without diabetes, and diabetes increased the susceptibility to COVID-19, reinforcing the need for heightened preventive measures, particularly considering the poor clinical outcomes in this group.

Electronic cigarettes and subsequent use of cigarettes in young people: An evidence and gap map

BACKGROUND AND AIMS

The use of e-cigarettes may influence later smoking uptake in young people. Evidence and gap maps (EGMs) are interactive on-line tools that display the evidence and gaps in a specific area of policy or research. The aim of this study was to map clusters and gaps in evidence exploring the relationship between e-cigarette use or availability and subsequent combustible tobacco use in people aged < 30 years.

METHODS

We conducted an EGM of primary studies and systematic reviews. A framework and an interactive EGM was developed in consultation with an expert advisory group. A systematic search of five databases retrieved 9057 records, from which 134 studies were included. Systematic reviews were appraised using AMSTAR-2, and all included studies were coded into the EGM framework resulting in the interactive web-based EGM. A descriptive analysis of key characteristics of the identified evidence clusters and gaps resulted in this report.

RESULTS

Studies were completed between 2015 and 2023, with the first systematic reviews being published in 2017. Most studies were conducted in western high-income countries, predominantly the United States. Cohort studies were the most frequently used study design. The evidence is clustered on e-cigarette use as an exposure, with an absolute gap identified for evidence looking into the availability of e-cigarettes and subsequent cessation of cigarette smoking. We also found little evidence analysing equity factors, and little exploring characteristics of e-cigarette devices.

CONCLUSIONS

This evidence and gap map (EGM) offers a tool to explore the available evidence regarding the e-cigarette use/availability and later cigarette smoking in people under the age of 30 years at the time of the search. The majority of the 134 reports is from high-income countries, with an uneven geographic distribution. Most of the systematic reviews are of lower quality, suggesting the need for higher-quality reviews. The evidence is clustered around e-cigarette use as an exposure and subsequent frequency/intensity of current combustible tobacco use. Gaps in evidence focusing on e-cigarette availability, as well as on the influence of equity factors may warrant further research. This EGM can support funders and researchers in identifying future research priorities, while guiding practitioners and policymakers to the current evidence base.

Association between Glycosylated Hemoglobin Levels and Vaccine Preventable Diseases: A Systematic Review

People with diabetes are at higher risk of serious complications from many vaccine-preventable diseases (VPDs). Some studies have highlighted the potential impact of glycosylated hemoglobin levels (HbA1c), but no systematic review has synthesized these findings. Of the 823 identified studies, 3 were included, for a total of 705,349 participants. Regarding the incidence of herpes zoster (HZ), one study found that higher HbA1c levels at the baseline (>10.3%) were associated with a significantly higher risk of HZ of 44%, compared to those with a good HbA1c control (6.7%). On the contrary, the second one reported that when compared to the reference group (HbA1c of 5.0-6.4%), participants with a HbA1c less than 5.0% were at higher risk of HZ of 63%, whilst participants with a HBA1c more than 9.5% had a similar risk. Finally, the third study observed that diabetes, defined using a value of HbA1c more than 7.5%, was associated with an increased risk of mortality in men with COVID-19. In conclusion, both high and low HBA1c levels appear to be associated with a higher risk of HZ. Regarding COVID-19, a value of HbA1c more than 7.5% was associated with a higher risk of death in COVID-19, but only in men.

Impact of Diabetes Mellitus On In-Hospital Mortality of COVID-19 Patients in Japan Since COVID-19 Became a Common Infectious Disease

AIM

The number of severe cases of coronavirus disease 2019 (COVID-19) has been decreasing since the emergence of the Omicron variant at the end of 2021. COVID-19 has become a common infectious disease in Japan and was downgraded to a category five infectious disease on May 8, 2023. This study aimed to compare the impact of diabetes mellitus on in-hospital mortality in COVID-19 patients since COVID-19 became a common infectious disease.

PATIENTS AND METHODS

We conducted a retrospective observational study using data from an advanced critical care center in Osaka, Japan. The study included 1,381 patients of COVID-19 admitted to the center between March 1, 2020, and May 7, 2023, before COVID-19 became a category five infectious disease in Japan. Individuals younger than 18 years and pregnant women were excluded. We divided the patients into two groups: pre- and post-Omicron epidemic groups. The primary endpoint of the study was the in-hospital mortality, and the prognostic impact of diabetes mellitus was compared between the groups.

RESULTS

The Kaplan-Meier curve showed a significantly lower rate of in-hospital mortality in the post-Omicron epidemic group than in the pre-Omicron epidemic group. The hazard ratio (HR) was 1.83 (95% CI, 1.36-2.50; p < 0.0001). Patients with diabetes mellitus had higher in-hospital mortality in both the pre- and post-Omicron epidemic groups; their HRs were 1.39 (95% CI, 1.21-1.59; p < 0.0001) and 1.45 (95% CI, 1.15-1.83; p = 0.0012), respectively. Diabetes mellitus had no significant interaction effect on the association between the post-Omicron epidemic and in-hospital mortality (p for interaction = 0.2154).

CONCLUSION

Diabetes mellitus may continue contributing to COVID-19 in-hospital mortality in the future, as the Omicron sub-strain may still be prevalent.

Diabetes and infection: review of the epidemiology, mechanisms and principles of treatment

An association between diabetes and infection has been recognised for many years, with infection being an important cause of death and morbidity in people with diabetes. The COVID-19 pandemic has re-kindled an interest in the complex relationship between diabetes and infection. Some infections occur almost exclusively in people with diabetes, often with high mortality rates without early diagnosis and treatment. However, more commonly, diabetes is a complicating factor in many infections. A reciprocal relationship occurs whereby certain infections and their treatments may also increase the risk of diabetes. People with diabetes have a 1.5- to 4-fold increased risk of infection. The risks are the most pronounced for kidney infection, osteomyelitis and foot infection, but are also increased for pneumonia, influenza, tuberculosis, skin infection and general sepsis. Outcomes from infection are worse in people with diabetes, with the most notable example being a twofold higher rate of death from COVID-19. Hyperglycaemia has deleterious effects on the immune response. Vascular insufficiency and neuropathy, together with altered skin, mucosal and gut microbial colonisation, contribute to the increased risk of infection. Vaccination is important in people with diabetes although the efficacy of certain immunisations may be compromised, particularly in the presence of hyperglycaemia. The principles of treatment largely follow those of the general population with certain notable exceptions.

The prognostic significance of insulin resistance in COVID-19: a review

Objectives

Emerging publications indicate that diabetes predisposes patients with COVID-19 to more severe complications, which is partly attributed to inflammatory condition. In the current review, we reviewed recent published literature to provide evidence on the role of insulin resistance (IR) in diabetes, the association between diabetes and COVID-19 severity and mortality, the impact of COVID-19 infection on incident new-onset diabetes, mechanisms responsible for IR in COVID-19 patients, and the predictive value of different surrogates of IR in COVID-19.

Method

The literature search performs to find out studies that have assessed the association between IR surrogates and morbidity and mortality in patients with COVID-19.

Results

We showed that there is a bulk of evidence in support of the fact that diabetes is a potent risk factor for enhanced morbidity and mortality in COVID-19 patients. COVID-19 patients with diabetes are more prone to remarkable dysglycemia compared to those without diabetes, which is associated with an unfavourable prognosis. Furthermore, SARS-COV2 can make patients predispose to IR and diabetes via activating ISR, affecting RAAS signaling pathway, provoking inflammation, and changing the expression of PPARɣ and SREBP-1. Additionally, higher IR is associated with increased morbidity and mortality in COVID-19 patients and different surrogates of IR can be utilized as a prognostic biomarker for COVID-19 patients.

Conclusion

Different surrogates of IR can be utilized as predictors of COVID-19 complications and death.

Association of Premorbid GLP-1RA and SGLT-2i Prescription Alone and in Combination with COVID-19 Severity

INTRODUCTION

People with type 2 diabetes are at heightened risk for severe outcomes related to COVID-19 infection, including hospitalization, intensive care unit admission, and mortality. This study was designed to examine the impact of premorbid use of glucagon-like peptide-1 receptor agonist (GLP-1RA) monotherapy, sodium-glucose cotransporter-2 inhibitor (SGLT-2i) monotherapy, and concomitant GLP1-RA/SGLT-2i therapy on the severity of outcomes in individuals with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

METHODS

Utilizing observational data from the National COVID Cohort Collaborative through September 2022, we compared outcomes in 78,806 individuals with a prescription of GLP-1RA and SGLT-2i versus a prescription of dipeptidyl peptidase 4 inhibitors (DPP-4i) within 24 months of a positive SARS-CoV-2 PCR test. We also compared concomitant GLP-1RA/SGLT-2i therapy to GLP-1RA and SGLT-2i monotherapy. The primary outcome was 60-day mortality, measured from the positive test date. Secondary outcomes included emergency room (ER) visits, hospitalization, and mechanical ventilation within 14 days. Using a super learner approach and accounting for baseline characteristics, associations were quantified with odds ratios (OR) estimated with targeted maximum likelihood estimation (TMLE).

RESULTS

Use of GLP-1RA (OR 0.64, 95% confidence interval [CI] 0.56-0.72) and SGLT-2i (OR 0.62, 95% CI 0.57-0.68) were associated with lower odds of 60-day mortality compared to DPP-4i use. Additionally, the OR of ER visits and hospitalizations were similarly reduced with GLP1-RA and SGLT-2i use. Concomitant GLP-1RA/SGLT-2i use showed similar odds of 60-day mortality when compared to GLP-1RA or SGLT-2i use alone (OR 0.92, 95% CI 0.81-1.05 and OR 0.88, 95% CI 0.76-1.01, respectively). However, lower OR of all secondary outcomes were associated with concomitant GLP-1RA/SGLT-2i use when compared to SGLT-2i use alone.

CONCLUSION

Among adults who tested positive for SARS-CoV-2, premorbid use of either GLP-1RA or SGLT-2i is associated with lower odds of mortality compared to DPP-4i. Furthermore, concomitant use of GLP-1RA and SGLT-2i is linked to lower odds of other severe COVID-19 outcomes, including ER visits, hospitalizations, and mechanical ventilation, compared to SGLT-2i use alone. Graphical abstract available for this article.

Impact of Pre-existing Type 2 Diabetes Mellitus and Cardiovascular Disease on Healthcare Resource Utilization and Costs in Patients With COVID-19

Background: The economic burden associated with type 2 diabetes mellitus (T2DM) and concurrent cardiovascular disease (CVD) among patients with COVID-19 is unclear. Objective: We compared healthcare resource utilization (HCRU) and costs in patients with COVID-19 and T2DM and CVD (T2DM + CVD), T2DM only, or neither T2DM nor CVD (T2DM/CVD). Methods: A retrospective observational study in COVID-19 patients using data from the Healthcare Integrated Research Database (HIRD®) was conducted. Patients with COVID-19 were identified between March 1, 2020, and May 31, 2021, and followed from first diagnosis or positive lab test to the end of health plan enrollment, end of study period, or death. Patients were assigned one of 3 cohorts: pre-existing T2DM+CVD, T2DM only, or neither T2DM/CVD. Propensity score matching and multivariable analyses were performed to control for differences in baseline characteristics. Study outcomes included all-cause and COVID-19-related HCRU and costs. Results: In all, 321 232 COVID-19 patients were identified (21 651 with T2DM + CVD, 28 184 with T2DM only, and 271 397 with neither T2DM/CVD). After matching, 6967 patients were in each group. Before matching, 46.0% of patients in the T2DM + CVD cohort were hospitalized for any cause, compared with 18.0% in the T2DM-only cohort and 6.3% in the neither T2DM/CVD cohort; the corresponding values after matching were 34.2%, 26.0%, and 21.2%. The proportion of patients with emergency department visits, telehealth visits, or use of skilled nursing facilities was higher in patients with COVID-19 and T2DM + CVD compared with the other cohorts. Average all-cause costs during follow-up were 12   324 , 7882, and $7277 per-patient-per-month after matching for patients with T2DM + CVD, T2DM-only, and neither T2DM/CVD, respectively. COVID-19-related costs contributed to 78%, 75%, and 64% of the overall costs, respectively. The multivariable model showed that per-patient-per-month all-cause costs for T2DM + CVD and T2DM-only were 54% and 21% higher, respectively, than those with neither T2DM/CVD after adjusting for residual confounding. Conclusion: HCRU and costs in patients were incrementally higher with COVID-19 and pre-existing T2DM + CVD compared with those with T2DM-only and neither T2DM/CVD, even after accounting for baseline differences between groups, confirming that pre-existing T2DM + CVD is associated with increased HCRU and costs in COVID-19 patients, highlighting the importance of proactive management.

The impact of type 2 diabetes and glycaemic control on mortality and clinical outcomes in hospitalized patients with COVID-19 in the capital region of Denmark

AIM

To explore the impact of type 2 diabetes (T2D), glycaemic control and use of glucose-lowering medication on clinical outcomes in hospitalized patients with COVID-19.

MATERIALS AND METHODS

For all patients admitted to a hospital in the Capital Region of Denmark (1 March 2020 to 1 December 2021) with confirmed COVID-19, we extracted data on mortality, admission to intensive care unit (ICU), demographics, comorbidities, medication use and laboratory tests from the electronic health record system. We compared patients with T2D to patients without diabetes using Cox proportional hazards models adjusted for available confounding variables. Outcomes were 30-day mortality and admission to an ICU. For patients with T2D, we also analysed the association of baseline haemoglobin A1c (HbA1c) levels and use of specific glucose-lowering medications with the outcomes.

RESULTS

In total, 4430 patients were analysed, 1236 with T2D and 2194 without diabetes. The overall 30-day mortality was 19% (n = 850) and 10% (n = 421) were admitted to an ICU. Crude analyses showed that patients with T2D both had increased mortality [hazard ratio (HR) 1.37; 95% CI 1.19-1.58] and increased risk of ICU admission (HR 1.28; 95% CI 1.04-1.57). When adjusted for available confounders, this discrepancy was attenuated for both mortality (adjusted HR 1.13; 95% CI 0.95-1.33) and risk of ICU admission (adjusted HR 1.01; 95% CI 0.79-1.29). Neither baseline haemoglobin A1c nor specific glucose-lowering medication use were significantly associated with the outcomes.

CONCLUSION

Among those hospitalized for COVID-19, patients with T2D did not have a higher risk of death and ICU admission, when adjusting for confounders.

4. Comprehensive Medical Evaluation and Assessment of Comorbidities: Standards of Care in Diabetes-2024

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

COVID-19 Vaccination Prior to SARS-CoV-2 Infection Reduced Risk of Subsequent Diabetes Mellitus: A Real-World Investigation Using U.S. Electronic Health Records

OBJECTIVE

Previous studies have indicated a bidirectional correlation between diabetes and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, no investigation has comprehensively explored the potential of coronavirus disease 2019 (COVID-19) vaccination to reduce the risk of new-onset diabetes in infected individuals.

RESEARCH DESIGN AND METHODS

In the first of 2 cohorts, we compared the risk of new-onset diabetes between individuals infected with SARS-CoV-2 and noninfected individuals (N = 1,562,606) using the TriNetX database to validate findings in prior literature. For the second cohort, we identified 83,829 vaccinated and 83,829 unvaccinated COVID-19 survivors from the same period. Diabetes, antihyperglycemic drug use, and a composite of both were defined as outcomes. We conducted Cox proportional hazard regression analysis for the estimation of hazard ratios (HRs) and 95% CIs. Kaplan-Meier analysis was conducted to calculate the incidence of new-onset diabetes. Subgroup analyses based on age (18-44, 45-64, ≥65 years), sex (female, male), race (White, Black or African American, Asian), and BMI categories (<19.9, 20-29, 30-39, ≥40), sensitivities analyses, and a dose-response analysis were conducted to validate the findings.

RESULTS

The initial cohort of patients infected with SARS-CoV-2 had a 65% increased risk (HR 1.65; 95% CI 1.62-1.68) of developing new-onset diabetes relative to noninfected individuals. In the second cohort, we observed that vaccinated patients had a 21% lower risk of developing new-onset diabetes in comparison with unvaccinated COVID-19 survivors (HR 0.79; 95% CI 0.73-0.86). Subgroup analyses by sex, age, race, and BMI yielded similar results. These findings were consistent in sensitivity analyses and cross-validation with an independent data set from TriNetX.

CONCLUSIONS

In conclusion, this study validates a 65% higher risk of new-onset diabetes in SARS-CoV-2-infected individuals compared to noninfected counterparts. Furthermore, COVID-19 survivors who received COVID-19 vaccinations experienced a reduced risk of new-onset diabetes, with a dose-dependent effect. Notably, the protective impact of COVID-19 vaccination is more pronounced among the Black/African American population than other ethnic groups. These findings emphasize the imperative of widespread vaccination to mitigate diabetes risk and the need for tailored strategies for diverse demographic groups to ensure equitable protection.

Diabetes related phenotypes and their influence on outcomes of patients with corona virus disease 2019 (COVID-19)

INTRODUCTION

Diabetes mellitus (DM) is associated with severe forms of COVID-19 but little is known about the diabetes-related phenotype considering pre-admission, on-admission and data covering the entire hospitalization period.

METHODS

We analyzed COVID-19 inpatients (n = 3327) aged 61.2(48.2-71.4) years attended from March to September 2020 in a public hospital.

RESULTS

DM group (n = 1218) differed from Non-DM group (n = 2109) by higher age, body mass index (BMI), systolic blood pressure and lower O2 saturation on admission. Gender, ethnicity and COVID-19-related symptoms were similar. Glucose and several markers of inflammation, tissue injury and organ dysfunction were higher among patients with diabetes: troponin, lactate dehydrogenase, creatine phosphokinase (CPK), C-reactive protein (CRP), lactate, brain natriuretic peptide, urea, creatinine, sodium, potassium but lower albumin levels. Hospital (12 × 11 days) and intensive care unit permanence (10 × 9 days) were similar but DM group needed more vasoactive, anticoagulant and anti-platelet drugs, oxygen therapy, endotracheal intubation and dialysis. Lethality was higher in patients with diabetes (39.3% × 30.7%) and increased with glucose levels and age, in male sex and with BMI < 30 kg/m2 in both groups (obesity paradox). It was lower with previous treatment with ACEi/BRA in both groups. Ethnicity and education level did not result in different outcomes between groups. Higher frequency of comorbidities (hypertension, cardiovascular/renal disease, stroke), of inflammatory (higher leucocyte number, RCP, LDH, troponin) and renal markers (urea, creatinine, potassium levels and lower sodium, magnesium) differentiated lethality risk between patients with and without diabetes.

CONCLUSIONS

Comorbidities, inflammatory markers and renal disfunction but not Covid-19-related symptoms, obesity, ethnicity and education level differentiated lethality risk between patients with and without diabetes.

Mechanisms and clinical relevance of the bidirectional relationship of viral infections with metabolic diseases

Viruses have been present during all evolutionary steps on earth and have had a major effect on human history. Viral infections are still among the leading causes of death. Another public health concern is the increase of non-communicable metabolic diseases in the last four decades. In this Review, we revisit the scientific evidence supporting the presence of a strong bidirectional feedback loop between several viral infections and metabolic diseases. We discuss how viruses might lead to the development or progression of metabolic diseases and conversely, how metabolic diseases might increase the severity of a viral infection. Furthermore, we discuss the clinical relevance of the current evidence on the relationship between viral infections and metabolic disease and the present and future challenges that should be addressed by the scientific community and health authorities.

Impact of SARS-CoV-2 Infection on Disease Trajectory in Youth with T1D: An EHR-Based Cohort Study from the RECOVER Program

Background

Postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC) is associated with worsening diabetes trajectory. It is unknown whether PASC in children with type 1 diabetes (T1D) manifests as worsening diabetes trajectory.

Objective

To explore the association between SARS-CoV-2 infection (COVID-19) and T1D-related healthcare utilization (for diabetic ketoacidosis (DKA) or severe hypoglycemia (SH)) or hemoglobin (Hb) A1c trajectory. Methods: We included children <21 years with T1D and ≥1 HbA1c prior to cohort entry, which was defined as COVID-19 (positive diagnostic test or diagnosis code for COVID-19, multisystem inflammatory syndrome in children, or PASC) or a randomly selected negative test for those who were negative throughout the study period (Broad Cohort). A subset with ≥1 HbA1c value from 28 to 275 days after cohort entry (Narrow Cohort) was included in the trajectory analysis. Propensity score-based matched cohort design followed by weighted Cox regression was used to evaluate the association of COVID-19 with healthcare utilization ≥28 days after cohort entry. Generalized estimating equation (GEE) models were used to measure change in HbA1c in the Narrow Cohort.

Results

From March 01, 2020 to June 22, 2022, 2,404 and 1,221 youth met entry criteria for the Broad and Narrow Cohorts, respectively. The hazard ratio for utilization was (HR 1.45 (95% CI: 0.97, 2.16)). In the Narrow Cohort, the rate of change (slope) of HbA1c increased 91-180 days after cohort entry for those with COVID-19 (0.138 vs. -0.002, p = 0.172). Beyond 180 days, greater declines in HbA1c were observed in the positive cohort (-0.104 vs. 0.008 per month, p = 0.024).

Conclusion

While a trend toward worse outcomes following COVID-19 in T1D patients was observed, these findings were not statistically significant. Continued clinical monitoring of youth with T1D following COVID-19 is warranted.

Diabetes associates with mortality in critically ill patients with SARS-CoV-2 pneumonia: No diabetes paradox in COVID-19

Background

Diabetes mellitus (DM) is not associated with increased mortality in critically ill patients, a phenomenon known as the "diabetes paradox". However, DM is a risk factor for increased mortality in patients with COVID-19. This study aims to investigate the association of DM and stress-induced hyperglycemia at intensive care unit (ICU) with mortality in this population.

Methods

This is a retrospective study. Electronic medical records from patients admitted from March 2020 to September 2020 were reviewed. Primary outcome was mortality. Secondary outcomes were ICU and hospital mortality and stay, and need for mechanical ventilation and renal replacement therapy.

Results

187 patients were included. Overall mortality was 43.2%, higher in patients with DM (55.7% vs. 34%; p = 0.007), even after adjustment for age, hypertension, and disease severity. When patients were separated into groups, named normoglycemia (without DM and glycemia ≤140 mg/dL), stress-induced hyperglycemia (without DM and glycemia >140 mg/dL), and DM (previous diagnosis or HbA1c ≥ 6.5%), the mortality rate was 25.8%, 37.3%, and 55.7%, respectively (p = 0.021). Mortality was higher in patients with higher glycemic variability. No statistical difference related to secondary outcomes was observed.

Conclusions

DM, hyperglycemia, and glycemic variability associated with increased mortality in critically ill patients with severe COVID-19, but did not increase the rates of other clinical outcomes. More than stress-induced hyperglycemia, DM was associated with mortality.

Identifying hub genes and common biological pathways between COVID-19 and benign prostatic hyperplasia by machine learning algorithms

Background

COVID-19, a serious respiratory disease that has the potential to affect numerous organs, is a serious threat to the health of people around the world. The objective of this article is to investigate the potential biological targets and mechanisms by which SARS-CoV-2 affects benign prostatic hyperplasia (BPH) and related symptoms.

Methods

We downloaded the COVID-19 datasets (GSE157103 and GSE166253) and the BPH datasets (GSE7307 and GSE132714) from the Gene Expression Omnibus (GEO) database. In GSE157103 and GSE7307, differentially expressed genes (DEGs) were found using the "Limma" package, and the intersection was utilized to obtain common DEGs. Further analyses followed, including those using Protein-Protein Interaction (PPI), Gene Ontology (GO) function enrichment analysis, and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Potential hub genes were screened using three machine learning methods, and they were later verified using GSE132714 and GSE166253. The CIBERSORT analysis and the identification of transcription factors, miRNAs, and drugs as candidates were among the subsequent analyses.

Results

We identified 97 common DEGs from GSE157103 and GSE7307. According to the GO and KEGG analyses, the primary gene enrichment pathways were immune-related pathways. Machine learning methods were used to identify five hub genes (BIRC5, DNAJC4, DTL, LILRB2, and NDC80). They had good diagnostic properties in the training sets and were validated in the validation sets. According to CIBERSORT analysis, hub genes were closely related to CD4 memory activated of T cells, T cells regulatory and NK cells activated. The top 10 drug candidates (lucanthone, phytoestrogens, etoposide, dasatinib, piroxicam, pyrvinium, rapamycin, niclosamide, genistein, and testosterone) will also be evaluated by the P value, which is expected to be helpful for the treatment of COVID-19-infected patients with BPH.

Conclusion

Our findings reveal common signaling pathways, possible biological targets, and promising small molecule drugs for BPH and COVID-19. This is crucial to understand the potential common pathogenic and susceptibility pathways between them.

Association Between Diabetes Severity and Risks of COVID-19 Infection and Outcomes

BACKGROUND

Little is known about whether diabetes increases the risk of COVID-19 infection and whether measures of diabetes severity are related to COVID-19 outcomes.

OBJECTIVE

Investigate diabetes severity measures as potential risk factors for COVID-19 infection and COVID-19 outcomes.

DESIGN, PARTICIPANTS, MEASURES

In integrated healthcare systems in Colorado, Oregon, and Washington, we identified a cohort of adults on February 29, 2020 (n = 1,086,918) and conducted follow-up through February 28, 2021. Electronic health data and death certificates were used to identify markers of diabetes severity, covariates, and outcomes. Outcomes were COVID-19 infection (positive nucleic acid antigen test, COVID-19 hospitalization, or COVID-19 death) and severe COVID-19 (invasive mechanical ventilation or COVID-19 death). Individuals with diabetes (n = 142,340) and categories of diabetes severity measures were compared with a referent group with no diabetes (n = 944,578), adjusting for demographic variables, neighborhood deprivation index, body mass index, and comorbidities.

RESULTS

Of 30,935 patients with COVID-19 infection, 996 met the criteria for severe COVID-19. Type 1 (odds ratio [OR] 1.41, 95% CI 1.27-1.57) and type 2 diabetes (OR 1.27, 95% CI 1.23-1.31) were associated with increased risk of COVID-19 infection. Insulin treatment was associated with greater COVID-19 infection risk (OR 1.43, 95% CI 1.34-1.52) than treatment with non-insulin drugs (OR 1.26, 95% 1.20-1.33) or no treatment (OR 1.24; 1.18-1.29). The relationship between glycemic control and COVID-19 infection risk was dose-dependent: from an OR of 1.21 (95% CI 1.15-1.26) for hemoglobin A1c (HbA1c) < 7% to an OR of 1.62 (95% CI 1.51-1.75) for HbA1c ≥ 9%. Risk factors for severe COVID-19 were type 1 diabetes (OR 2.87; 95% CI 1.99-4.15), type 2 diabetes (OR 1.80; 95% CI 1.55-2.09), insulin treatment (OR 2.65; 95% CI 2.13-3.28), and HbA1c ≥ 9% (OR 2.61; 95% CI 1.94-3.52).

CONCLUSIONS

Diabetes and greater diabetes severity were associated with increased risks of COVID-19 infection and worse COVID-19 outcomes.

Glycemic Gap Predicts Mortality in a Large Multicenter Cohort Hospitalized With COVID-19

CONTEXT

Diabetes or hyperglycemia at admission are established risk factors for adverse outcomes during hospitalization for COVID-19, but the impact of prior glycemic control is not clear.

OBJECTIVE

We aimed to examine the associations between admission variables, including glycemic gap, and adverse clinical outcomes in patients hospitalized with COVID-19 infection.

METHODS

We examined the relationship between clinical predictors, including acute and chronic glycemia, and clinical outcomes, including intensive care unit (ICU) admission, mechanical ventilation (MV), and mortality among 1786 individuals with diabetes or hyperglycemia (glucose > 10 mmol/L twice in 24 hours) who were admitted from March 2020 through February 2021 with COVID-19 infection at 5 university hospitals in the eastern United States.

RESULTS

The cohort was 51.3% male, 53.3% White, 18.8% Black, 29.0% Hispanic, with age = 65.6 ± 14.4 years, BMI = 31.5 ± 7.9 kg/m2, glucose = 12.0 ± 7.5 mmol/L [216 ± 135 mg/dL], and HbA1c = 8.07% ± 2.25%. During hospitalization, 38.9% were admitted to the ICU, 22.9% received MV, and 10.6% died. Age (P < 0.001) and admission glucose (P = 0.014) but not HbA1c were associated with increased risk of mortality. Glycemic gap, defined as admission glucose minus estimated average glucose based on HbA1c, was a stronger predictor of mortality than either admission glucose or HbA1c alone (OR = 1.040 [95% CI: 1.019, 1.061] per mmol/L, P < 0.001). In an adjusted multivariable model, glycemic gap, age, BMI, and diabetic ketoacidosis on admission were associated with increased mortality, while higher estimated glomerular filtration rate (eGFR) and use of any diabetes medication were associated with lower mortality (P < 0.001).

CONCLUSION

Relative hyperglycemia, as measured by the admission glycemic gap, is an important marker of mortality risk in COVID-19.

Multimorbidity and SARS-CoV-2-Related Outcomes: Analysis of a Cohort of Italian Patients

BACKGROUND

Since the outbreak of the COVID-19 pandemic, identifying the main risk factors has been imperative to properly manage the public health challenges that the pandemic exposes, such as organizing effective vaccination campaigns. In addition to gender and age, multimorbidity seems to be 1 of the predisposing factors coming out of many studies investigating the possible causes of increased susceptibility to SARS-CoV-2 infection and adverse outcomes. However, only a few studies conducted have used large samples.

OBJECTIVE

The objective is to evaluate the association between multimorbidity, the probability to be tested, susceptibility, and the severity of SARS-CoV-2 infection in the Piedmont population (Northern Italy, about 4 million inhabitants). For this purpose, we considered 5 main outcomes: access to the swab, positivity to SARS-CoV-2, hospitalization, intensive care unit (ICU) admission, and death within 30 days from the first positive swab.

METHODS

Data were obtained from different Piedmont health administrative databases. Subjects aged from 45 to 74 years and infections diagnosed from February to May 2020 were considered. Multimorbidity was defined both with the Charlson Comorbidity Index (CCI) and by identifying patients with previous comorbidities, such as diabetes and oncological, cardiovascular, and respiratory diseases. Multivariable logistic regression models (adjusted for age and month of infection and stratified by gender) were performed for each outcome. Analyses were also conducted by separating 2 age groups (45-59 and 60-74 years).

RESULTS

Of 1,918,549 subjects, 85,348 (4.4%) performed at least 1 swab, of whom 12,793 (14.9%) tested positive for SARS-CoV-2. Of these 12,793 subjects, 4644 (36.3%) were hospitalized, 1508 (11.8%) were admitted to the ICU, and 749 (5.9%) died within 30 days from the first positive swab. Individuals with a higher CCI had a higher probability of being swabbed but a lower probability of testing positive. We observed the same results when analyzing subjects with previous oncological and cardiovascular diseases. Moreover, especially in the youngest group, we identified a greater risk of being hospitalized and dying. Among comorbidities considered in the study, respiratory diseases seemed to be the most likely to increase the risk of having a positive swab and worse disease outcomes.

CONCLUSIONS

Our study shows that patients with multimorbidity, although swabbed more frequently, are less likely to get infected with SARS-CoV-2, probably due to greater attention on protective methods. Moreover, a history of respiratory diseases is a risk factor for a worse prognosis of COVID-19. Nonetheless, whatever comorbidities affect the patients, a strong dose-response effect was observed between an increased CCI score and COVID-19 hospitalization, ICU admission, and death. These results are important in terms of public health because they help in identifying a group of subjects who are more prone to worse SARS-CoV-2 outcomes. This information is important for promoting targeted prevention and developing policies for the prioritization of public health interventions.

Diabetes and the COVID-19 pandemic

Almost immediately after the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus emerged, it was evident that people with chronic diseases, including diabetes, were disproportionately affected, with an increased risk of hospitalisation and mortality. Over the ensuing 2 years, the indirect effects of the pandemic on healthcare delivery in the short term have become prominent, along with the lingering effects of the virus in those directly infected. In the wake of the pandemic and without any evidence from high quality studies, a number of national and international consensus recommendations were published, which were subsequently rapidly updated based on observational studies. There have been unprecedented disruptions from both direct and indirect impacts of coronavirus disease-2019 (COVID-19) in people with diabetes. In this review, we summarise the impact of acute COVID-19 in people with diabetes, discuss how the presentation and epidemiology during the pandemic, including presentation of diabetic ketoacidosis and new-onset diabetes, has changed, and we consider the wider impact of the pandemic on patients and healthcare service delivery, including some of the areas of uncertainty. Finally, we make recommendations on prioritising patients as we move into the recovery phase and also how we protect people with diabetes for the future, as COVID-19 is likely to become endemic.

The Impact of the COVID-19 Pandemic on Ethnic Minority Groups With Diabetes

Major ethnic disparities in diabetes care, especially for intermediate outcomes and diabetes complications, were evident prior to the coronavirus disease 2019 (COVID-19) pandemic. Diabetes is a risk factor for severe COVID-19, and the combination of these ethnic disparities in diabetes care and outcomes may have contributed to the inequity in COVID-19 outcomes for people with diabetes. Overall, ethnic minority populations have suffered disproportionate rates of COVID-19 hospitalization and mortality. Results from the limited number of studies of COVID-19 in ethnic minority populations with diabetes are mixed, but there is some suggestion that rates of hospitalization and mortality are higher than those of White populations. Reasons for the higher incidence and severity of COVID-19-related outcomes in minority ethnic groups are complex and have been shown to be due to differences in comorbid conditions (e.g., diabetes), exposure risk (e.g., overcrowded living conditions or essential worker jobs), and access to treatment (e.g., health insurance status and access to tertiary care medical centers), which all relate to long-standing structural inequities that vary by ethnicity. While guidelines and approaches for diabetes self-management and outpatient and inpatient care during the pandemic have been published, few have recommended addressing wider structural issues. As we now plan for the recovery and improved surveillance and risk factor management, it is imperative that primary and specialist care services urgently address the disproportionate impact the pandemic has had on ethnic minority groups. This should include a focus on the larger structural barriers in society that put ethnic minorities with diabetes at potentially greater risk for poor COVID-19 outcomes.

4. Comprehensive Medical Evaluation and Assessment of Comorbidities: Standards of Care in Diabetes-2023

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Association of Obesity and Diabetes with SARS-Cov-2 Infection and Symptoms in the COVID-19 Community Research Partnership

OBJECTIVE

Obesity and diabetes are established risk factors for severe SARS-CoV-2 outcomes, but less is known about their impact on susceptibility to COVID-19 infection and general symptom severity. We hypothesized that those with obesity or diabetes would be more likely to self-report a positive SARS-CoV-2 test, and among those with a positive test, have greater symptom severity and duration.

METHODS

Among 44,430 COVID-19 Community Research Partnership participants, we evaluated the association of self-reported and electronic health record obesity and diabetes with a self-reported positive COVID-19 test at any time. Among the 2,663 participants with a self-reported positive COVID-19 test during the study, we evaluated the association of obesity and diabetes with self-report of symptom severity, duration, and hospitalization. Logistic regression models were adjusted for age, sex, race/ethnicity, socioeconomic status, and healthcare worker status.

RESULTS

We found a positive graded association between Body Mass Index (BMI) category and positive COVID-19 test (Overweight OR = 1.14 [1.05-1.25]; Obesity I OR = 1.29 [1.17-2.42]; Obesity II OR = 1.34 [1.19-1.50]; Obesity III OR = 1.53 [1.35-1.73]), and a similar but weaker association with COVID-19 symptoms and severity among those with a positive test. Diabetes was associated with COVID-19 infection but not symptoms after adjustment, with some evidence of an interaction between obesity and diabetes.

CONCLUSIONS

While the limitations of this health system convenience sample include generalizability and selection around test-seeking, the strong graded association of BMI and diabetes with self-reported COVID-19 infection suggests that obesity and diabetes may play a role in risk for symptomatic SARS-CoV-2 beyond co-occurrence with socioeconomic factors.

Incidence Trends of New-Onset Diabetes in Children and Adolescents Before and During the COVID-19 Pandemic: Findings From Florida

This study examined the incidence trends of new-onset type 1 and type 2 diabetes in children and adolescents in Florida before and during the coronavirus disease 2019 (COVID-19) pandemic. In this observational descriptive cohort study, we used a validated computable phenotype to identify incident diabetes cases among individuals <18 years of age in the OneFlorida+ network of the national Patient-Centered Clinical Research Network between January 2017 and June 2021. We conducted an interrupted time series analysis based on the autoregressive integrated moving average model to compare changes in age-adjusted incidence rates of type 1 and type 2 diabetes before and after March 2020, when COVID-19 was declared a national health emergency in the U.S. The age-adjusted incidence rates of both type 1 and type 2 diabetes increased post-COVID-19 for children and adolescents. These results highlight the need for longitudinal cohort studies to examine how the pandemic might influence subsequent diabetes onset in young individuals.

The published trend of studies on COVID-19 and dietary supplements: Bibliometric analysis

BACKGROUND

There are no guidelines on dietary supplements for the prevention or treatment of COVID-19. Therefore, we would like to analyze and discuss the above confusion through the bibliometric analysis.

METHODS

On 3 September 2022, we conducted a search of all relevant literature retrieved from the WOS core collection database from 2019 to 2022. CiteSpace software is used to build the visual co-occurrence network.

RESULTS

In the study of "COVID-19 and Dietary Supplements", the total of 170 authors published 855 articles in 451 journals. Several distinct core author groups were formed by Wang, Grant, Singh, Zhu, and other authors with numerous publications. The majority of the publications came from the Shahid Beheshti University of Medical Sciences. The United States of America had the highest number of publications. By analyzing keyword clusters, we found that the research focus was dietary supplements (vitamin D, vitamin K, vitamin C), mechanisms (ferritin, specialized pro-resolving mediators (SPMs), oxidative stress), research methods (clinical trials), and the prevention and treatment strategies (lockdown) of COVID-19.

CONCLUSIONS

vitamin D is the mainstream dietary supplement for COVID-19. There are still numerous controversies that deserve further discussion. Such as whether the use of vitamin D or TCM offers benefits, and whether the addition of dietary supplements during the lockdown measures can help prevent COVID-19 infection.

MUC22, HLA-A, and HLA-DOB variants and COVID-19 in resilient super-agers from Brazil

Background

Although aging correlates with a worse prognosis for Covid-19, super elderly still unvaccinated individuals presenting mild or no symptoms have been reported worldwide. Most of the reported genetic variants responsible for increased disease susceptibility are associated with immune response, involving type I IFN immunity and modulation; HLA cluster genes; inflammasome activation; genes of interleukins; and chemokines receptors. On the other hand, little is known about the resistance mechanisms against SARS-CoV-2 infection. Here, we addressed polymorphisms in the MHC region associated with Covid-19 outcome in super elderly resilient patients as compared to younger patients with a severe outcome.

Methods

SARS-CoV-2 infection was confirmed by RT-PCR test. Aiming to identify candidate genes associated with host resistance, we investigated 87 individuals older than 90 years who recovered from Covid-19 with mild symptoms or who remained asymptomatic following positive test for SARS-CoV-2 as compared to 55 individuals younger than 60 years who had a severe disease or died due to Covid-19, as well as to the general elderly population from the same city. Whole-exome sequencing and an in-depth analysis of the MHC region was performed. All samples were collected in early 2020 and before the local vaccination programs started.

Results

We found that the resilient super elderly group displayed a higher frequency of some missense variants in the MUC22 gene (a member of the mucins' family) as one of the strongest signals in the MHC region as compared to the severe Covid-19 group and the general elderly control population. For example, the missense variant rs62399430 at MUC22 is two times more frequent among the resilient super elderly (p = 0.00002, OR = 2.24).

Conclusion

Since the pro-inflammatory basal state in the elderly may enhance the susceptibility to severe Covid-19, we hypothesized that MUC22 might play an important protective role against severe Covid-19, by reducing overactive immune responses in the senior population.

Considerations for management of patients with diabetes mellitus and acute COVID-19

Diabetes mellitus (DM) is an independent risk factor for admission to intensive care unit and death in patients with coronavirus disease 2019 (COVID-19). On the other hand, medications used in the management of COVID-19 are potentially associated with increases in blood glucose levels and a higher incidence of infections. Accordingly, care of patients with DM and acute COVID-19 requires careful consideration of both diseases. Hyperglycemia and hypoglycemia are associated with adverse outcomes and therefore frequent measurement of blood glucose levels and a basal-bolus insulin regimen are required in most patients. Regarding the management of COVID-19, dexamethasone increases blood glucose levels and might also increase the risk for infections. On the other hand, limited data suggest that antiviral and immunomodulatory agents used in COVID-19 are not strongly associated with higher incidence of infections in this population. As knowledge evolves in this field, optimization of the management of both DM and COVID-19 will hopefully improve the outcome of these patients.

SARS-CoV-2 coinfections with variant genomic lineages identified by multiplex fragment analysis

Immunocompromised patients can experience prolonged SARS-CoV-2 infections in the setting of a lack of protectivity immunity despite vaccination. As circulating SARS-CoV-2 strains become more heterogeneous, concomitant infection with multiple SARS-CoV-2 variants has become an increasing concern. Immunocompromised patient populations represent potential reservoirs for the emergence of novel SARS-CoV-2 variants through mutagenic change or coinfection followed by recombinatory events. Identification of SARS-CoV-2 coinfections is challenging using traditional next generation sequencing pipelines; however, targeted genotyping approaches can facilitate detection. Here we describe five COVID-19 cases caused by coinfection with different SARS-CoV-2 variants (Delta/Omicron BA.1 and Omicron BA.1/BA.2) as identified by multiplex fragment analysis.

Symptoms and Glycemic Control in Young People With Type 1 Diabetes Following SARS-CoV-2 Infection: An Observational Study

CONTEXT

Data is needed regarding the effect of SARS-CoV-19 infection on young people with established type 1 diabetes. Identifying the disease outcomes, short and long-term sequelae may help to establish an evidence-based prevention and education policy for sick days management and DKA prevention.

OBJECTIVE

This work aims to describe clinical manifestations of SARS-CoV-2 infection in children, adolescents, and young adults with established type 1 diabetes (T1D) and explore the effects of COVID-19 on glycemic control and disease course.

METHODS

An observational study was conducted at 3 pediatric diabetes clinics in Israel between mid-March 2020 and mid-March 2021. Included were young people with established T1D, age younger than 30 years, who tested positive for SARS-CoV-2 (quantitative real-time polymerase chain reaction). Data were collected from medical files, diabetes devices, and COVID-19 questionnaire. Outcome measures were analyzed by the presence/absence of clinical symptoms (symptomatic/asymptomatic) and by age group (pediatric, < 19 years/young adults, 19-30 years).

RESULTS

Of 132 patients, mean age 16.9 ± 5.3years, with COVID-19-confirmed infection, 103 (78%) had related symptoms; the most common were headaches, fatigue, fever, and loss of sense of smell. All had a mild disease course, but 4 required hospitalization and 2 cases were directly related to COVID-19 infection (pleuropneumonia in a patient with immunodeficiency syndrome, 1 case of diabetic ketoacidosis). Logistic regression analysis showed that age (odds ratio [OR] = 1.11; 95% CI, 1.01-1.23; P = .033), elevated glucose levels (OR = 5.23; 95% CI, 1.12-24.41; P = .035), and comorbidities (OR = 8.21; 95% CI, 1.00-67.51; P = .050) were positively associated with symptomatic infection. Persistent symptoms occurred in 16.5% of the cohort over a median of 6.7 months; age (OR = 1.14; 95% CI, 1.01-1.29; P = .030) and elevated glucose levels (OR = 3.42; 95% CI, 1.12-10.40; P = .031) were positively associated with persistent symptoms. Usually, no change was reported in glucose levels (64%) except for a temporary deterioration in glycemic control during the short infection period.

CONCLUSION

Young people with established T1D experience mild COVID-19 infection. Elevated glucose levels during COVID-19 infection and older age were associated with prolonged disease course.

Gene Networks of Hyperglycemia, Diabetic Complications, and Human Proteins Targeted by SARS-CoV-2: What Is the Molecular Basis for Comorbidity?

People with diabetes are more likely to have severe COVID-19 compared to the general population. Moreover, diabetes and COVID-19 demonstrate a certain parallelism in the mechanisms and organ damage. In this work, we applied bioinformatics analysis of associative molecular networks to identify key molecules and pathophysiological processes that determine SARS-CoV-2-induced disorders in patients with diabetes. Using text-mining-based approaches and ANDSystem as a bioinformatics tool, we reconstructed and matched networks related to hyperglycemia, diabetic complications, insulin resistance, and beta cell dysfunction with networks of SARS-CoV-2-targeted proteins. The latter included SARS-CoV-2 entry receptors (ACE2 and DPP4), SARS-CoV-2 entry associated proteases (TMPRSS2, CTSB, and CTSL), and 332 human intracellular proteins interacting with SARS-CoV-2. A number of genes/proteins targeted by SARS-CoV-2 (ACE2, BRD2, COMT, CTSB, CTSL, DNMT1, DPP4, ERP44, F2RL1, GDF15, GPX1, HDAC2, HMOX1, HYOU1, IDE, LOX, NUTF2, PCNT, PLAT, RAB10, RHOA, SCARB1, and SELENOS) were found in the networks of vascular diabetic complications and insulin resistance. According to the Gene Ontology enrichment analysis, the defined molecules are involved in the response to hypoxia, reactive oxygen species metabolism, immune and inflammatory response, regulation of angiogenesis, platelet degranulation, and other processes. The results expand the understanding of the molecular basis of diabetes and COVID-19 comorbidity.

A role for the diabetes nurse educator to telemedically support children with type 1 diabetes on continuous glucose monitoring? The COVID-19 lockdown experience

The role of diabetes nurse educators during the COVID-19 lockdown to telematically provide routine reviews of glycaemic control in children with type 1 diabetes (T1D) using continuous glucose monitoring systems is evaluated. Implementing these routines in the day-to-day clinical practice could reduce in-person clinic visits and improve glucose control.

Effect of diabetes on short-term mortality and incidence of first hospitalizations for cardiovascular events after recovery from SARS-CoV-2 infection

AIM

To evaluate the impact of diabetes and COVID-19 on all-cause-mortality and first hospitalizations for cardiovascular events (CVE): myocardial infarction or stroke, within six months after being tested positive and having recovered from SARS-CoV-2 infection.

METHODS

Resident population in Tuscany, Italy of age 45-94 yr without prior hospitalization for CVE, tested positive for SARS-CoV-2 by March 1st, 2020 and afterwards recovering from COVID-19 was compared with age, gender and diabetes matched controls without infection, for incidence rate ratio (IRR) of all-cause-deaths or first CVE at six months follow up.

RESULTS

46,152 subjects of whom 4,597 with diabetes, tested positive and recovered from SARS-CoV-2 were compared with 1:1 age, gender and diabetes matched controls without infection. COVID-19 was associated with higher all-cause-mortality: IRR:1.92(95 %CI:1.63-2.25) while diabetes with increased risk of first CVE hospitalizations: IRR:2.24(2.18-4.25). Co-presence of COVID-19 and diabetes didn't add any additional excess risk. Being women and statins' use significantly reduced death risk.

CONCLUSIONS

After recovery from COVID-19, independently of diabetes, all-cause-mortality risk at six months was twofold increased, while risk of first CVE hospitalization remained unmodified. Diabetes, independently of prior COVID-19, resulted in higher six-months risk of first CVE not of death. Female gender and statins' use reduced both excess risks.

Gestational diabetes is associated with SARS-CoV-2 infection during pregnancy: A case-control study

Aim

Individuals with SARS-CoV-2 infection and (pre-existing) diabetes, including pregnant women, present with more severe morbidity, as compared to non-diabetic subjects. To date, evidence is limited concerning the role of gestational diabetes (GDM) in severity of SARS-CoV-2 infection during pregnancy, or vice versa. The aim of our study was to investigate the prevalence of GDM in a SARS-CoV-2 infected pregnant population and evaluate risk factors for and from severe infection in these patients.

Methods

A case-control study with prospective data collection for the case group and 1:2 matching with historical controls based on parity, BMI and ethnicity was conducted (n = 224). GDM screening was performed at 26 weeks’ gestation. Multivariate binary logistic regression analysis was performed to assess risk factors for GDM and inpatient COVID-19 management.

Results

34.6% of the patients in the case group suffered from GDM, vs. 16.1% in the control group (p = 0.002). 35.7% patients were diagnosed with GDM after, vs. 33.3% before SARS-CoV-2 infection (OR (95%CI) 1.11(0.40–3.08), p = 0.84), with no correlation between time point of infection and GDM diagnosis. SARS-CoV-2 (OR (95%CI) 2.79 (1.42, 5.47), p = 0.003) and BMI (OR (95%CI) 1.12 (1.05, 1.19), p = 0.001) were significant independent risk factors for GDM.

Conclusion

Data suggests that GDM increases the risk of infection in SARS-CoV-2 infected pregnant women. Meanwhile, SARS-CoV-2 during pregnancy might increase the risk of developing GDM.

Vaccination and caution in using protective measures should be recommended to pregnant women, particularly when suffering from GDM.

Mendelian randomization study of obesity and type 2 diabetes in hospitalized COVID-19 patients

BACKGROUND

Both obesity and type 2 diabetes (T2D) are reported to be highly enriched in hospitalized COVID-19 patients. Due to the close correlation between obesity and T2D, it is important to examine whether obesity and T2D are independently related to COVID-19 hospitalization.

OBJECTIVE

To examine the causal effect of obesity and T2D in hospitalized COVID-19 patients using Mendelian randomization (MR).

RESEARCH DESIGN AND METHODS

This two-sample MR analysis applied genetic markers of obesity identified in the genome wide association study (GWAS) by the GIANT Consortium as instrumental variables (IVs) of obesity; and genetic markers of T2D identified by the DIAGRAM Consortium as IVs of T2D. The MR analysis was performed in hospitalized COVID-19 patient by the COVID-19 Host Genetics Initiative using the MR-Base platform.

RESULTS

All 3 classes of obesity (Class 1/2/3) were shown as the causal risk factors of COVID-19 hospitalization; however, T2D doesn't increase the risk of hospitalization or critically ill COVID-19 as an independent factor.

CONCLUSIONS

Obesity, but not T2D, is a primary risk factor of COVID-19 hospitalization.

Interleukin-6 in SARS-CoV-2 induced disease: Interactions and therapeutic applications

Interleukin-6 (IL-6) is a multi-tasking cytokine that represents high activity in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and cancer. High concentration of this pleiotropic cytokine accounts for hyperinflammation and cytokine storm, and is related to multi-organ failure in patients with SARS-CoV-2 induced disease. IL-6 promotes lymphopenia and increases C-reactive protein (CRP) in such cases. However, blockade of IL-6 is not a full-proof of complete response. Hypoxia, hypoxemia, aberrant angiogenesis and chronic inflammation are inter-related events occurring as a response to the SARS-CoV-2 stimulatory effect on high IL-6 activity. Taking both pro- and anti-inflammatory activities will make complex targeting IL-6 in patient with SARS-CoV-2 induced disease. The aim of this review was to discuss about interactions occurring within the body of patients with SARS-CoV-2 induced disease who are representing high IL-6 levels, and to determine whether IL-6 inhibition therapy is effective for such patients or not. We also address the interactions and targeted therapies in cancer patients who also have SARS-CoV-2 induced disease.

Estimating causal effects of genetically predicted type 2 diabetes on COVID-19 in the East Asian population

BACKGROUND

Observational studies suggested that type 2 diabetes mellitus (T2DM) was associated with an increased risk of coronavirus disease 2019 (COVID-19). However, Mendelian randomization (MR) studies in the European population failed to find causal associations, partly because T2DM was pleiotropically associated with body mass index (BMI). We aimed to estimate the causal effects of T2DM on COVID-19 outcomes in the East Asian (EAS) population using a two-sample MR approach.

METHODS

We obtained summary statistics from a genome-wide association study (GWAS) that included 433,540 EAS participants as the exposure dataset for T2DM risk and from COVID-19 Host Genetics Initiative GWAS meta-analyses (round 7) of EAS ancestry as the outcome dataset for COVID-19 susceptibility (4,459 cases and 36,121 controls), hospitalization (2,882 cases and 31,200 controls), and severity (794 cases and 4,862 controls). As the main MR analysis, we performed the inverse variance weighted (IVW) method. Moreover, we conducted a series of sensitivity analyses, including IVW multivariable MR using summary statistics for BMI from a GWAS with 158,284 Japanese individuals as a covariate.

RESULTS

The IVW method showed that the risk of T2DM significantly increased the risk of COVID-19 susceptibility (odds ratio [OR] per log (OR) increase in T2DM, 1.11; 95% confidence interval [CI], 1.02-1.20; P = 0.014) and hospitalization (OR, 1.15; 95% CI, 1.04-1.26; P = 0.005), although the risk of severity was only suggestive. Moreover, IVW multivariable MR analysis indicated that the causal effects of T2DM on COVID-19 outcomes were independent of the effect of BMI.

CONCLUSIONS

Our MR study indicated for the first time that genetically predicted T2DM is a risk factor for SARS-CoV-2 infection and hospitalized COVID-19 independent of obesity in the EAS population.