Risks of and risk factors for COVID-19 disease in people with diabetes: a cohort study of the total population of Scotland

Women Suffered More Than Men Both During and After the COVID-19 Pandemic-A Cross-Sectional Study Among 29,079 Patients With Type 2 Diabetes

OBJECTIVE

To investigate the gender differences and the disparities between infected and noninfected patients with type 2 diabetes (T2D) regarding patient-reported experiences during the COVID-19 pandemic in Norway.

METHOD

Register study using questionnaires sent electronically to patients with T2D, June 2022. The questionnaire included 82 questions covering COVID-19 disease, symptoms, medications, comorbidities, hospital care, possibility of working from home and information received from health authorities. Clinical and demographic data were collected from the Norwegian diabetes registry for adults.

RESULTS

A total of 29,079 T2D patients participated, of whom 38.1% were women. Patients infected with COVID-19 were younger, had shorter diabetes duration and less comorbidities than noninfected (p < 0.01). Women reported significantly more anxiety, depression and fear of not getting their diabetes medication than men did. Most patients were vaccinated against COVID-19 (98.3%), whereas approximately 60% had received seasonal flu vaccine, and only 27.2% the pneumococcal vaccine. Women described more vaccine adverse effects and long Covid symptoms. Overall, 14% experienced vaccine complications and 27.3% of infected individuals reported long Covid symptoms. 2.4% of the infected patients needed hospital admission. Patients were satisfied with the follow-up of their diabetes, and with information from the government during the pandemic.

CONCLUSION

Female patients were more likely to experience a prolonged Covid course, and higher degree of adverse effects from the COVID-19 vaccine than male patients. Also, long Covid symptoms were significantly more often reported among female patients, while men were more prone to be hospitalised when infected. Hospitalised patients, both men and women, had significantly higher HbA1C than those who were not hospitalised. T2D patients had a surprisingly low pneumococcal vaccination coverage, despite recommendations in national guidelines.

Risk of angioedema and thrombolytic therapy among stroke patients: An analysis of data from the FDA Adverse Event Reporting System database

The angioedema risk may vary among stroke patients receiving different thrombolytic agents. This study aimed to investigate the angioedema risk associated with different thrombolytic agents and to identify associated risk factors. We conducted a large-scale retrospective pharmacovigilance study using the FDA Adverse Event Reporting System (FAERS) database. Stroke patients receiving thrombolytic therapy (i.e., alteplase or tenecteplase) were identified, and the associations with angioedema were explored using disproportionality analysis and time-to-onset analysis. Additionally, we used adapted Bradford Hill criteria to confirm these associations. Risk factors for angioedema were explored using stepwise logistic regression. A total of 17,776 stroke patients were included, with 2973 receiving alteplase and 278 receiving tenecteplase. Disproportionality analysis revealed that angioedema might be associated with alteplase (adjusted ROR [aROR] 5.13 [95 ​% CI, 4.55-5.79]) or tenecteplase (aROR 2.72 [95 ​% CI, 1.98-3.67]). The adapted Bradford Hill criteria suggested a probable causal relationship between alteplase and angioedema, whereas there was insufficient evidence of a probable causal relationship with tenecteplase. Multivariate analysis revealed that ACE-inhibitors use (aROR 9.73 [95 ​% CI, 7.29-12.98]), female sex (aROR 1.38 [95 ​% CI, 1.13-1.67]) and hypertension (aROR 2.11 [95 ​% CI, 1.52-2.92]) were significant risk factors for angioedema among alteplase-treated stroke patients. Our study suggested that alteplase is associated with a greater risk of angioedema among stroke patients, but there is insufficient evidence to support an association between tenecteplase and angioedema. Clinicians should be vigilant for this potentially life-threatening complication, particularly in patients with identified risk factors. It is also prudent to consider tenecteplase as an alternative, if available.

Impact of COVID-19 infection on genitourinary cancer management. SOGUG-COVID-19: A spanish, multicenter, observational study

INTRODUCTION

The COVID-19 pandemic is a great burden worldwide, but its impact on patients with genitourinary cancer (GUC) is poorly characterized. This study aimed to characterize the clinical features and evolution of GUC patients affected by COVID-19 in Spain.

PATIENTS AND METHODS

SOGUG-COVID-19 was an observational ambispective non-interventional study that recruited patients with SARS-CoV-2 infection who had been treated for GUC in 32 Spanish hospitals. Data were collected from patients' medical records in a short period of time, coinciding with the first waves of COVID-19, when the mortality was also higher in the general population.

RESULTS

From November 2020 to April 2021, 408 patients were enrolled in the study. The median age was 70 years, and 357 patients (87.5%) were male. Most frequent Cancer Origin was: prostate (40.7%), urothelial (31.4%) and kidney (22.1%). Most patients (71.3%) were diagnosed at the metastatic stage, and 33.3% had poorly differentiated histology. Anticancer treatment during the infection was reported in 58.3% of patients, and 21.3% had received immunotherapy prior to or concurrent with the infection. The most frequent COVID-19 symptoms were pyrexia (49.0%), cough (38.2%) and dyspnea (31.9%). Median age was higher for patients with pneumonia (p < 0.001), patchy infiltrates (p = 0.005), ICU admission (p < 0.001) and death (p < 0.001). Tumor stage was associated with complications (p = 0.006). The fatality rate was 19.9% and the 6-month COVID-19-specific survival rate was 79.7%.

CONCLUSION

Patients with genitourinary cancers seem exceptionally vulnerable to COVID-19 regardless of tumor type or anticancer therapy. Age and tumor stage were the only identified risk factors for severe COVID-19.

Impact of the COVID-19 Pandemic on Lifestyle Behavior and Clinical Care Pathway Management in Type 2 Diabetes: A Retrospective Cross-Sectional Study

Background and Objectives: In Italy, as in the rest of the world, government restrictions aimed at containing the spread of COVID-19 primarily imposed limitations on social relationships and personal behavior. This situation significantly affected the management of chronic illnesses, including type 2 diabetes (T2D). The objective was to evaluate the perceptions of patients with T2D regarding the quality of care received during the COVID-19 pandemic and the impact on dietary and physical activity behaviors. Materials and Methods: We conducted a retrospective cross-sectional survey. Data were collected from June to July 2023 using the convenience sampling of patients with T2D, and the Patient Assessment of Chronic Illness Care (PACIC) and Medi-Lite questionnaires were administered. Results: During the research period, out of the 130 subjects who met all enrollment criteria, 103 patients were included in this study (79.23%). The results of the administered questionnaires were heterogeneous. The average scores from the PACIC Questionnaire for each question displayed significant variability, indicating a range of experiences in the quality of care. In the Medi-Lite survey, fruit, cereals, and olive oil showed the highest adherence levels, with mean scores ranging from 2.58 (SD ± 1.18) for fruit to 1.89 (SD ± 0.34) for olive oil and 1.97 (SD ± 0.17) for cereals. Patients who reported increased food intake during the lockdown attributed it to having more time to prepare meals. Physical activity levels remained unchanged for 48 patients, decreased for 45 patients, and only 9 patients managed to exercise more during the COVID-19 restrictions. Conclusions: Healthcare systems must prioritize comprehensive care plans for T2D that address not only physical health, but also emotional and social well-being. Post-pandemic, promoting healthier lifestyles and empowering patients to manage their condition is crucial. A multidisciplinary and multidimensional approach could support the care of vulnerable individuals, such as patients with T2D, especially during crises like pandemics or other dramatic events.

Mathematical model for understanding the relationship between diabetes and novel coronavirus

A new model is proposed to explore interactions between diabetes and novel coronavirus. The model accounted for both the omicron variant and variants varying from omicron. The model investigated compartments such as hospitalization, diabetes, co-infection, omicron variant, and quarantine. Additionally, the impact of different vaccination doses is assessed. Sensitivity analysis is carried out to determine disease prevalence and control options, emphasizing the significance of knowing epidemics and their characteristics. The model is validated using actual data from Japan. The parameters are fitted with the help of "Least Square Curve Fitting" method to describe the dynamic behavior of the proposed model. Simulation results and theoretical findings demonstrate the dynamic behavior of novel coronavirus and diabetes mellitus (DM). Biological illustrations that illustrate impact of model parameters are evaluated. Furthermore, effect of vaccine efficacy and vaccination rates for the vaccine's first, second, and booster doses is conducted. The impact of various preventive measures, such as hospitalization rate, quarantine or self-isolation rate, vaccine dose-1, dose-2, and booster dose, is considered for diabetic individuals in contact with symptomatic or asymptomatic COVID-19 infectious people in the proposed model. The findings demonstrate the significance of vaccine doses on people with diabetes and individuals infectious with omicron variant. The proposed work helps with subsequent prevention efforts and the design of a vaccination policy to mitigate the effect of the novel coronavirus.

The possible effect of anti-diabetic agents GLP-1RA and SGLT-2i on the respiratory system function

Type 2 Diabetes (T2D) is a chronic disease with increasing incidence and prevalence and serious chronic complications, especially from cardiovascular system. However, other organs can be affected too. Several studies have associated T2D, especially when poorly controlled, with multiple pulmonary diseases. T2D is a common comorbidity among patients with asthma, Chronic Obstructive Pulmonary Disease (COPD), and Obstructive Sleep Apnea Syndrome (OSAS), and it is related to higher respiratory infection incidence, prevalence and severity. Glucagon-like peptide-1 receptor agonists (GLP-1RA) and Sodium-glucose co-transporter-2 inhibitors (SGLT-2i) are novel antihyperglycaemic agents with established cardiovascular benefits. There are also limited studies indicating their potential benefit in respiratory function. The aim of this article is to review data on the impact of GLP-1RA and SGLT-2i on respiratory function and describe the possible clinical benefits. Key findings indicate that GLP-1RA significantly improve lung function in patients with COPD, evidenced by improvements in spirometry measurements. Additionally, both GLP-1RA and SGLT-2i are associated with a decreased risk of severe and moderate exacerbations in COPD patients and have shown potential in reducing the incidence of respiratory disorders, including asthma and pneumonia. The mechanisms underlying these benefits are not yet fully understood and include multiple effects, such as anti-inflammatory action and oxidative stress reduction.

Trends in diabetic ketoacidosis- and hyperosmolar hyperglycemic state-related mortality during the COVID-19 pandemic in the United States: A population-based study

BACKGROUND

During the pandemic, a notable increase in diabetic ketoacidosis (DKA) and hyperosmolar hyperglycemic state (HHS), conditions that warrant emergent management, was reported. We aimed to investigate the trend of DKA- and HHS-related mortality and excess deaths during the pandemic.

METHODS

Annual age-standardized mortality rates related to DKA and HHS between 2006 and 2021 were estimated using a nationwide database. Forecast analyses based on prepandemic data were conducted to predict the mortality rates during the pandemic. Excess mortality rates were calculated by comparing the observed versus predicted mortality rates. Subgroup analyses of demographic factors were performed.

RESULTS

There were 71 575 DKA-related deaths and 8618 HHS-related deaths documented during 2006-2021. DKA, which showed a steady increase before the pandemic, demonstrated a pronounced excess mortality during the pandemic (36.91% in 2020 and 46.58% in 2021) with an annual percentage change (APC) of 29.4% (95% CI: 16.0%-44.0%). Although HHS incurred a downward trend during 2006-2019, the excess deaths in 2020 (40.60%) and 2021 (56.64%) were profound. Pediatric decedents exhibited the highest excess mortality. More than half of the excess deaths due to DKA were coronavirus disease 2019 (COVID-19) related (51.3% in 2020 and 63.4% in 2021), whereas only less than a quarter of excess deaths due to HHS were COVID-19 related. A widened racial/ethnic disparity was observed, and females exhibited higher excess mortality than males.

CONCLUSIONS

The DKA- and HHS-related excess mortality during the pandemic and relevant disparities emphasize the urgent need for targeted strategies to mitigate the escalated risk in these populations during public health crises.

Impact of COVID-19 and Non-COVID-19 Hospitalized Pneumonia on Longer-Term Cardiovascular Mortality in People With Type 2 Diabetes: A Nationwide Prospective Cohort Study From Scotland

OBJECTIVE

In this study we examine whether hospitalized coronavirus disease 2019 (COVID-19) pneumonia increases long-term cardiovascular mortality more than other hospitalized pneumonias in people with type 2 diabetes and aim to quantify the relative cardiovascular disease (CVD) mortality risks associated with COVID-19 versus non-COVID-19 pneumonia.

RESEARCH DESIGN AND METHODS

With use of the SCI-Diabetes register, two cohorts were identified: individuals with type 2 diabetes in 2016 and at the 2020 pandemic onset. Hospital and death records were linked for determination of pneumonia exposure and CVD deaths. Poisson regression estimated rate ratios (RRs) for CVD death associated with both pneumonia types, with adjustment for confounders. Median follow-up durations were 1,461 days (2016 cohort) and 700 days (2020 cohort).

RESULTS

The adjusted RR for CVD death following non-COVID-19 pneumonia was 5.51 (95% CI 5.31-5.71) prepandemic and 7.3 (6.86-7.76) during the pandemic. For COVID-19 pneumonia, the RR was 9.13 (8.55-9.75). Beyond 30 days post pneumonia, the RRs converged, to 4.24 (3.90-4.60) for non-COVID-19 and 3.35 (3.00-3.74) for COVID-19 pneumonia, consistent even with exclusion of prior CVD cases.

CONCLUSIONS

Hospitalized pneumonia, irrespective of causal agent, marks an increased risk for CVD death immediately and over the long-term. COVID-19 pneumonia poses a higher CVD death risk than other pneumonias in the short-term, but this distinction diminishes over time. These insights underscore the need for including pneumonia in CVD risk assessments, with particular attention to the acute impact of COVID-19 pneumonia.

Impacts of COVID-19 pandemic prevention measures to the palliative care in Taiwan

Background

Prevention measures for palliative care and the provision of discharge planning services for inpatients in Taiwan before and during the COVID-19 pandemic had not been investigated. This study was aimed to investigate the factors associated with heightened palliative care needs and increased mortality rates.

Methods

This research adopts a retrospective case-control study design. The investigation encompasses patients admitted before the pandemic (from January 1, 2019, to May 31, 2019) and during the COVID-19 pandemic (from January 1, 2020, to May 31, 2020). The case group consisted of 231 end-of-life inpatients during the pandemic, control group was composed of the pool of inpatients with pre-pandemic and matched with cases by sex and age in a 1:1 ratio.

Results

The results showed that the prevalence of respiratory failure symptoms (p = 0.004), residing in long-term care facilities (p = 0.017), palliative care needs assessment scores (p = 0.010), as well as the provision of guidance for nasogastric tube feeding (p = 0.002), steam inhalation (p = 0.003), turning and positioning (p < 0.001), percussion (p < 0.001), passive range of motion (p < 0.001), and blood pressure measurement (p < 0.001). Furthermore, the assessment of the necessity for assistive devices, including hospital beds, also exhibited statistically significant variations (p < 0.001). Further investigation of the factors associated with high palliative care needs and the risk of mortality for both the case and control groups. Risk factors for high palliative care needs encompassed assessments of daily activities of living, the presence of pressure ulcers, and the receipt of guidance for ambulation. Risk factors for mortality encompassed age, a diagnosis of cancer, palliative care needs assessment scores, and the provision of guidance for disease awareness.

Conclusion

This research highlights the heightened risk of COVID-19 infection among end-of-life inpatients during the COVID-19 pandemic. The findings of this study may advance care planning to alleviate avoidable suffering. To meet the needs of inpatients during pandemic, healthcare professionals should undergo comprehensive palliative care training and receive policy support.

COVID-19 Vaccine Acceptance, Hesitancy, and Uptake in People with Diabetes in Australia

Background: This study explored vaccination hesitancy, diabetes-specific COVID-19 vaccination concerns, and whether they predicted vaccination uptake in people with diabetes. Methods: Quantitative, cross-sectional, and predictive approaches were used. An online survey was conducted with people with diabetes attending four Australian health services, using convenience sampling (n = 842). The survey data collected included clinico-demographic characteristics, COVID-19 vaccine hesitancy, and attitudes around COVID-19 vaccine confidence and complacency. Clinico-demographic characteristics that predicted vaccination status, vaccine hesitancy, and vaccine-related attitudes were identified using regression analyses. Results: Most participants received at least one COVID-19 vaccine dose. Younger age and type 1 diabetes were associated with lower vaccination status, and they were partially mediated through higher vaccine hesitancy. Younger age and English as a dominant language were associated with higher negative attitudes towards speed of vaccine development. Conclusions: Despite an overall high vaccination rate, general and diabetes-specific COVID-19 vaccine concerns are a barrier to uptake for some people with diabetes, particularly in those who are younger or have type 1 diabetes. A detailed understanding of concerns for particular subgroups can help tailor information to increase vaccine acceptance, particularly in the context of requiring booster doses.

Indirect effects of the COVID-19 pandemic on diagnosing, monitoring, and prescribing in people with diabetes and strategies for diabetes service recovery internationally

The COVID-19 pandemic has caused major disruptions in clinical services for people with chronic long-term conditions. In this narrative review, we assess the indirect impacts of the COVID-19 pandemic on diabetes services globally and the resulting adverse effects on rates of diagnosing, monitoring, and prescribing in people with type 2 diabetes. We summarise potential practical approaches that could address these issues and improve clinical services and outcomes for people living with diabetes during the recovery phase of the pandemic.

Influence of simultaneous comorbidities on COVID-associated acute respiratory distress syndrome mortality in people with diabetes

Objectives

This study analyzed the influence of 23 comorbidities on COVID-associated acute distress respiratory syndrome (CARDS) mortality in people with a history of diabetes mellitus.

Methods

An observational, analytical, cross sectional study was utilized to investigate data from 6723 health services in Brazil, comprising 5433 people with diabetes. Adjusted logistic regression models for demographic factors such as age, sex, and race were used to analyze the association between CARDS mortality and comorbidities.

Results

Persons with two (p < 0.001), three (p < 0.001), four (p < 0.001), and five (p < 0.001) simultaneous comorbidities had a higher chance of dying. We identified that diabetes patients who had concomitant metabolic diseases (p = 0.019), neurological disorders (p < 0.001), or were smokers (p < 0.001) had a higher predicted mortality risk based on CADRS.

Conclusion

The number of comorbidities plays a determining role in CARDS mortality in people with diabetes, especially those who suffer from smoking and neurological diseases simultaneously.

Effects of different treatments for type 2 diabetes mellitus on mortality of coronavirus disease from 2019 to 2021 in China: a multi-institutional retrospective study

The coronavirus disease (COVID-19) pandemic has continued for 5 years. Sporadic cases continue to occur in different locations. Type 2 diabetes mellitus (T2DM) is associated with a high risk of a poor prognosis in patients with COVID-19. Successful control of blood glucose levels can effectively decrease the risks of severe infections and mortality. However, the effects of different treatments were reported differently and even adversely. This retrospective study included 4,922 patients who have been diagnosed as COVID-19 and T2DM from 138 Hubei hospitals. The clinical characteristics and outcomes were compared and calculated their risk for death using multivariate Cox regression and Kaplan-Meier curves. After adjustment of age, sex, comorbidities, and in-hospital medications, metformin and alpha-glucosidase inhibitor (AGI) use performed lower all-cause mortality (adjusted hazard ratio [HR], 0.41; 95% confidence interval [CI]: 0.24-0.71; p = 0.001 for metformin; 0.53, 0.35-0.80, p = 0.002 for AGIs), while insulin use was associated with increased all-cause mortality (adjusted HR, 2.07, 95% CI, 1.61-2.67, p < 0.001). After propensity score-matched (PSM) analysis, adjusted HRs for insulin, metformin, and AGIs associated with all-cause mortality were 1.32 (95% CI, 1.03-1.81; p = 0.012), 0.48 (95% CI, 0.23-0.83, p = 0.014), and 0.59 (95% CI, 0.35-0.98, p = 0.05). Therefore, metformin and AGIs might be more suitable for patients with COVID-19 and T2DM while insulin might be used with caution.

Impact of a Public Health Emergency on Behavior, Stress, Anxiety and Glycemic Control in Patients With Pancreas or Islet Transplantation for Type 1 Diabetes

A public health emergency such as the COVID-19 pandemic has behavioral, mental and physical implications in patients with type 1 diabetes (T1D). To what extent the presence of a transplant further increases this burden is not known. Therefore, we compared T1D patients with an islet or pancreas transplant (β-cell Tx; n = 51) to control T1D patients (n = 272). Fear of coronavirus infection was higher in those with β-cell Tx than without (Visual Analogue Scale 5.0 (3.0-7.0) vs. 3.0 (2.0-5.0), p = 0.004) and social isolation behavior was more stringent (45.8% vs. 14.0% reported not leaving the house, p < 0.001). A previous β-cell Tx was the most important predictor of at-home isolation. Glycemic control worsened in patients with β-cell Tx, but improved in control patients (ΔHbA1c +1.67 ± 8.74 vs. -1.72 ± 6.15 mmol/mol, p = 0.006; ΔTime-In-Range during continuous glucose monitoring -4.5% (-6.0%-1.5%) vs. +3.0% (-2.0%-6.0%), p = 0.038). Fewer patients with β-cell Tx reported easier glycemic control during lockdown (10.4% vs. 22.6%, p = 0.015). All T1D patients, regardless of transplantation status, experienced stress (33.4%), anxiety (27.9%), decreased physical activity (42.0%), weight gain (40.5%), and increased insulin requirements (29.7%). In conclusion, T1D patients with β-cell Tx are increasingly affected by a viral pandemic lockdown with higher fear of infection, more stringent social isolation behavior and deterioration of glycemic control. This trial has been registered in the clinicaltrials.gov registry under identifying number NCT05977205 (URL: https://clinicaltrials.gov/study/NCT05977205).

Is Metformin Use Associated with a More Favorable COVID-19 Course in People with Diabetes?

Background: Diabetes Mellitus (DM) has been associated with a higher Coronavirus disease-19 (COVID-19) mortality, both in hospitalized patients and in the general population. A possible beneficial effect of metformin on the prognosis of COVID-19 has been reported in some observational studies, whereas other studies disagree. Methods: To investigate the possible effect of metformin on COVID-19 in-hospital mortality, we performed a retrospective study that included all SARS-CoV-2-positive patients with DM who were admitted to two Italian hospitals. In order to adjust for possible confounders accounting for the observed reduction of mortality in metformin users, we adopted the COVID-19 Mortality Risk Score (COVID-19 MRS) as a covariate. Results: Out of the 524 included patients, 33.4% died. A binomial logistic regression showed that metformin use was associated with a significant reduction in case fatality (OR 0.67 [0.45-0.98], p = 0.039), with no significant effect on the need for ventilation (OR 0.75 [0.5-1.11], p = 0.146). After adjusting for COVID-19 MRS, metformin did not retain a significant association with in-hospital mortality [OR 0.795 (0.495-1.277), p = 0.342]. Conclusions: A beneficial effect of metformin on COVID-19 was not proven after adjusting for confounding factors. The use of validated tools to stratify the risk for COVID-19 severe disease and death, such as COVID-19 MRS, may be useful to better explore the potential association of medications and comorbidities with COVID-19 prognosis.

Viral Epitope Scanning Reveals Correlation between Seasonal HCoVs and SARS-CoV-2 Antibody Responses among Cancer and Non-Cancer Patients

Seasonal coronaviruses (HCoVs) are known to contribute to cross-reactive antibody (Ab) responses against SARS-CoV-2. While these responses are predictable due to the high homology between SARS-CoV-2 and other CoVs, the impact of these responses on susceptibility to SARS-CoV-2 infection in cancer patients is unclear. To investigate the influence of prior HCoV infection on anti-SARS-CoV-2 Ab responses among COVID-19 asymptomatic individuals with cancer and controls without cancers, we utilized the VirScan technology in which phage immunoprecipitation and sequencing (PhIP-seq) of longitudinal plasma samples was performed to investigate high-resolution (i.e., epitope level) humoral CoV responses. Despite testing positive for anti-SARS-CoV-2 Ab in the plasma, a majority of the participants were asymptomatic for COVID-19 with no prior history of COVID-19 diagnosis. Although the magnitudes of the anti-SARS-CoV-2 Ab responses were lower in individuals with Kaposi sarcoma (KS) compared to non-KS cancer individuals and those without cancer, the HCoV Ab repertoire was similar between individuals with and without cancer independent of age, sex, HIV status, and chemotherapy. The magnitudes of the anti-spike HCoV responses showed a strong positive association with those of the anti-SARS-CoV-2 spike in cancer patients, and only a weak association in non-cancer patients, suggesting that prior infection with HCoVs might play a role in limiting SARS-CoV-2 infection and COVID-19 disease severity.

A Critical Review on the Long-Term COVID-19 Impacts on Patients With Diabetes

BACKGROUND

The world is currently grappling with the potentially life-threatening coronavirus disease 2019 (COVID-19), marking it as the most severe health crisis in the modern era. COVID-19 has led to a pandemic, with the World Health Organization (WHO) predicting that individuals with diabetes are at a higher risk of contracting the virus compared to the general population. This review aims to provide a practical summary of the long-term impacts of COVID-19 on patients with diabetes. Specifically, it focuses on the effects of SARS-CoV-2 on different types of diabetic patients, the associated mortality rate, the underlying mechanisms, related complications, and the role of vitamin D and zinc in therapeutic and preventive approaches.

METHODS

Relevant literature was identified through searches on PubMed, Web of Science, and Science Direct in English, up to April 2023.

RESULTS

COVID-19 can lead to distressing symptoms and pose a significant challenge for individuals living with diabetes. Older individuals and those with pre-existing conditions such as diabetes, coronary illness, and asthma are more susceptible to COVID-19 infection. Managing COVID-19 in individuals with diabetes presents challenges, as it not only complicates the fight against the infection but also potentially prolongs the recovery time. Moreover, the virus may thrive in individuals with high blood glucose levels. Various therapeutic approaches, including antidiabetic drugs, are available to help prevent COVID-19 in diabetic patients.

CONCLUSIONS

Diabetes increases the morbidity and mortality risk for patients with COVID-19. Efforts are globally underway to explore therapeutic interventions aimed at reducing the impact of diabetes on COVID-19.

Long-Term Outcomes of COVID-19 in Hospitalized Type 2 Diabetes Mellitus Patients

With the onset of the coronavirus pandemic, it has become clear that patients with diabetes are at risk for more severe and fatal COVID-19. Type 2 diabetes mellitus (T2D) is a major risk factor for adverse COVID-19 outcomes. The goal of study was to assess the characteristics and outcomes of hospitalized patients with COVID-19 with or without T2D in the hospital and at 10-month follow-up (FU).

METHODS

A total of 2486 hospitalized patients in the first wave of COVID-19 were analyzed according to the absence/presence of T2D, with 2082 (84.1%) patients in the control COVID-19 group and 381 (15.5%) in the T2D group. Twenty-three patients had other types of diabetes and were therefore excluded from the study. In-hospital mortality and cardiovascular endpoints (myocardial infarction, stroke, cardiovascular deaths and hospitalizations and composite endpoints) at the 10-month follow-up were analyzed. To remove bias in patients' characteristics disproportion, Propensity Score Matching (PSM) was used for hospital and follow-up endpoints.

RESULTS

Hospital mortality was considerably greater in T2D than in the control COVID-19 group (13.89% vs. 4.89%, p < 0.0001), and the difference remained after PSM (p < 0.0001). Higher glucose-level T2D patients had a higher mortality rate (p = 0.018). The most significant predictors of hospital death in T2D patients were a high CRP, glucose, neutrophils count, and Charlson Comorbidity Index. The follow-up of patients over 10 months showed a non-significant increase for all endpoints in the T2D group (p > 0.05), and significant increase in stroke (p < 0.042). After the PSM, the difference decreased in stroke (p = 0.090), but became significant in cardiovascular hospitalizations (p = 0.023).

CONCLUSION

In T2D patients with COVID-19, an increase in hospital mortality, stroke and cardiovascular hospitalizations rates in the follow-up was observed.

Reasons for Hospitalization Among Australians With Type 1 or Type 2 Diabetes and COVID-19

OBJECTIVE

Our aim in this study was to determine the reasons for hospitalization in Australian people with diabetes who contract COVID-19.

METHODS

All COVID-19 cases reported to the Victorian Department of Health and linked hospitalization data were assessed. We determined reasons for acute (0 to 30 days) and postacute (31 to 365 days) hospitalization among those with type 1 or type 2 diabetes and COVID-19, compared to those with COVID-19 and no diabetes, and to admissions before the COVID-19 pandemic.

RESULTS

A total of 13,302 Australians with type 1 or type 2 diabetes were hospitalized in the state of Victoria in the 12 months after COVID-19 diagnosis. Respiratory diseases accounted for 40% of acute admissions among those with diabetes. Viral pneumonia was the leading cause of acute hospitalization among those with diabetes and constituted a larger proportion of admissions in those with compared to those without diabetes (adjusted prevalence ratio 1.87, 95% confidence interval 1.76 to 1.99). The distribution of postacute hospitalizations among those with diabetes aligned with that of people with diabetes before the COVID-19 pandemic.

CONCLUSIONS

Respiratory diseases are the leading cause of acute hospitalization in those with type 1 or type 2 diabetes and COVID-19. The reasons for postacute hospitalization resemble those in people with diabetes and no COVID-19. We reinforce the importance of community management of people with diabetes in the ongoing pandemic.

Mortality-related risk factors of inpatients with diabetes and COVID-19: A multicenter retrospective study in Belgium

BACKGROUND AND AIMS

We describe mortality-related risk factors of inpatients with diabetes and coronavirus disease 2019 (COVID-19) in Belgium.

METHODS

We conducted a multicenter retrospective study from March to May, 2020, in 8 Belgian centers. Data on admission of patients with diabetes and COVID-19 were collected. Survivors were compared to non-survivors to identify prognostic risk factors for in-hospital death using multivariate analysis in both the total population and in the subgroup of patients admitted in the intensive care unit (ICU).

RESULTS

The study included 375 patients. The mortality rate was 26.4% (99/375) in the total population and 40% (27/67) in the ICU. Multivariate analysis identified older age (HR 1.05 [CI 1.03-1.07], P<0.0001) and male gender (HR 2.01 [1.31-3.07], P=0.0013) as main independent risk factors for in-hospital death in the total population. Metformin (HR 0.51 [0.34-0.78], P=0.0018) and renin-angiotensin-aldosterone system blockers (HR 0.56 [0.36-0.86], P=0.0088) use before admission were independent protective factors. In the ICU, chronic kidney disease (CKD) was identified as an independent risk factor for death (HR 4.96 [2.14-11.5], P<0.001).

CONCLUSION

In-hospital mortality due to the first wave of COVID-19 pandemic in Belgium was high in patients with diabetes. We found that advanced age and male gender were independent risk factors for in-hospital death. We also showed that metformin use before admission was associated with a significant reduction of COVID-19-related in-hospital mortality. Finally, we showed that CKD is a COVID-19-related mortality risk factor in patients with diabetes admitted in the ICU.

Risk factor associations for severe COVID-19, influenza and pneumonia in people with diabetes to inform future pandemic preparations: UK population-based cohort study

OBJECTIVE

This study aimed to compare clinical and sociodemographic risk factors for severe COVID-19, influenza and pneumonia, in people with diabetes.

DESIGN

Population-based cohort study.

SETTING

UK primary care records (Clinical Practice Research Datalink) linked to mortality and hospital records.

PARTICIPANTS

Individuals with type 1 and type 2 diabetes (COVID-19 cohort: n=43 033 type 1 diabetes and n=584 854 type 2 diabetes, influenza and pneumonia cohort: n=42 488 type 1 diabetes and n=585 289 type 2 diabetes).

PRIMARY AND SECONDARY OUTCOME MEASURES

COVID-19 hospitalisation from 1 February 2020 to 31 October 2020 (pre-COVID-19 vaccination roll-out), and influenza and pneumonia hospitalisation from 1 September 2016 to 31 May 2019 (pre-COVID-19 pandemic). Secondary outcomes were COVID-19 and pneumonia mortality. Associations between clinical and sociodemographic risk factors and each outcome were assessed using multivariable Cox proportional hazards models. In people with type 2 diabetes, we explored modifying effects of glycated haemoglobin (HbA1c) and body mass index (BMI) by age, sex and ethnicity.

RESULTS

In type 2 diabetes, poor glycaemic control and severe obesity were consistently associated with increased risk of hospitalisation for COVID-19, influenza and pneumonia. The highest HbA1c and BMI-associated relative risks were observed in people aged under 70 years. Sociodemographic-associated risk differed markedly by respiratory infection, particularly for ethnicity. Compared with people of white ethnicity, black and south Asian groups had a greater risk of COVID-19 hospitalisation, but a lesser risk of pneumonia hospitalisation. Risk factor associations for type 1 diabetes and for type 2 diabetes mortality were broadly consistent with the primary analysis.

CONCLUSIONS

Clinical risk factors of high HbA1c and severe obesity are consistently associated with severe outcomes from COVID-19, influenza and pneumonia, especially in younger people. In contrast, associations with sociodemographic risk factors differed by type of respiratory infection. This emphasises that risk stratification should be specific to individual respiratory infections.

Comparative Analysis of COVID-19 Outcomes in Type 1 and Type 2 Diabetes: A Three-Year Retrospective Study

Background and Objectives: This comprehensive retrospective study assesses COVID-19 outcomes in type 1 (T1D) and type 2 diabetes (T2D) patients across three years, focusing on how these outcomes varied with the evolving pandemic and changes in diabetes management. The study aims to determine if COVID-19 outcomes, including severity, intensive care unit (ICU) admission rates, duration of hospitalization, and mortality, are significantly different between these diabetes subtypes. Materials and Methods: The study analyzed data from patients admitted to the Victor Babes Hospital for Infectious Diseases and Pulmonology with confirmed COVID-19 and pre-existing diabetes, from the years 2020, 2021, and 2022. Results: Among 486 patients (200 without diabetes, 62 with T1D, 224 with T2D), T2D patients showed notably higher severity, with 33.5% experiencing severe cases, compared to 25.8% in T1D. Mortality rates were 11.6% in T2D and 8.1% in T1D. T2D patients had longer hospital stays (11.6 ± 7.0 days) compared to T1D (9.1 ± 5.8 days) and were more likely to require ICU admission (OR: 2.24) and mechanical ventilation (OR: 2.46). Hyperglycemia at admission was significantly higher in the diabetes groups, particularly in T2D (178.3 ± 34.7 mg/dL) compared to T1D (164.8 ± 39.6 mg/dL). Conclusions: The study reveals a discernible difference in COVID-19 outcomes between T1D and T2D, with T2D patients having longer hospital admissions, mechanical ventilation necessities, and mortality risks.

Utilizing machine learning for survival analysis to identify risk factors for COVID-19 intensive care unit admission: A retrospective cohort study from the United Arab Emirates

BACKGROUND

The current situation of the unprecedented COVID-19 pandemic leverages Artificial Intelligence (AI) as an innovative tool for addressing the evolving clinical challenges. An example is utilizing Machine Learning (ML) models-a subfield of AI that take advantage of observational data/Electronic Health Records (EHRs) to support clinical decision-making for COVID-19 cases. This study aimed to evaluate the clinical characteristics and risk factors for COVID-19 patients in the United Arab Emirates utilizing EHRs and ML for survival analysis models.

METHODS

We tested various ML models for survival analysis in this work we trained those models using a different subset of features extracted by several feature selection methods. Finally, the best model was evaluated and interpreted using goodness-of-fit based on calibration curves,Partial Dependence Plots and concordance index.

RESULTS

The risk of severe disease increases with elevated levels of C-reactive protein, ferritin, lactate dehydrogenase, Modified Early Warning Score, respiratory rate and troponin. The risk also increases with hypokalemia, oxygen desaturation and lower estimated glomerular filtration rate and hypocalcemia and lymphopenia.

CONCLUSION

Analyzing clinical data using AI models can provide vital information for clinician to measure the risk of morbidity and mortality of COVID-19 patients. Further validation is crucial to implement the model in real clinical settings.

The Functional Roles of MDSCs in Severe COVID-19 Pathogenesis

Severe COVID-19 is a major cause of morbidity and mortality worldwide, especially among those with co-morbidities, the elderly, and the immunocompromised. However, the molecular determinants critical for severe COVID-19 progression remain to be fully elucidated. Meta-analyses of transcriptomic RNAseq and single-cell sequencing datasets comparing severe and mild COVID-19 patients have demonstrated that the early expansion of myeloid-derived suppressor cells (MDSCs) could be a key feature of severe COVID-19 progression. Besides serving as potential early prognostic biomarkers for severe COVID-19 progression, several studies have also indicated the functional roles of MDSCs in severe COVID-19 pathogenesis and possibly even long COVID. Given the potential links between MDSCs and severe COVID-19, we examine the existing literature summarizing the characteristics of MDSCs, provide evidence of MDSCs in facilitating severe COVID-19 pathogenesis, and discuss the potential therapeutic avenues that can be explored to reduce the risk and burden of severe COVID-19. We also provide a web app where users can visualize the temporal changes in specific genes or MDSC-related gene sets during severe COVID-19 progression and disease resolution, based on our previous study.

SARS-CoV-2 vaccination in children and adolescents with and without type 1 diabetes mellitus

Adults with Diabetes Mellitus (DM) have increased risk of severe clinical presentation during COVID-19 infection, while children and adolescents with type 1 diabetes (T1D) have the same mild clinical course as their healthy peers, especially those with optimal glycemic control. The present review focuses on the necessity of COVID-19 vaccination among children and adolescents with T1D, and also in their non-diabetic peers. The efficacy and safety of COVID-19 vaccines are also discussed, as well as their various side-effects, ranging from common mild to very rare and serious ones. Furthermore, the results of COVID-19 vaccination of adolescents with and without T1D are reported, as well as the efficacy and concerns about childhood vaccination. It is concluded that patients with DM of all age groups should maintain optimal diabetic control in order to avoid glycemic deterioration during COVID-19 infection. Furthermore, despite the very rare and serious complications of COVID-19 vaccines, vaccination against COVID-19 is recommended for children and adolescents with T1D to prevent glycemic deterioration and rare but serious complications of COVID-19 infection.

Assessing the importance of demographic risk factors across two waves of SARS-CoV-2 using fine-scale case data

For the long term control of an infectious disease such as COVID-19, it is crucial to identify the most likely individuals to become infected and the role that differences in demographic characteristics play in the observed patterns of infection. As high-volume surveillance winds down, testing data from earlier periods are invaluable for studying risk factors for infection in detail. Observed changes in time during these periods may then inform how stable the pattern will be in the long term. To this end we analyse the distribution of cases of COVID-19 across Scotland in 2021, where the location (census areas of order 500-1,000 residents) and reporting date of cases are known. We consider over 450,000 individually recorded cases, in two infection waves triggered by different lineages: B.1.1.529 ("Omicron") and B.1.617.2 ("Delta"). We use random forests, informed by measures of geography, demography, testing and vaccination. We show that the distributions are only adequately explained when considering multiple explanatory variables, implying that case heterogeneity arose from a combination of individual behaviour, immunity, and testing frequency. Despite differences in virus lineage, time of year, and interventions in place, we find the risk factors remained broadly consistent between the two waves. Many of the observed smaller differences could be reasonably explained by changes in control measures.

Anti-SARS-CoV-2 antibody levels predict outcome in COVID-19 patients with type 2 diabetes: a prospective cohort study

Patients with type 2 diabetes (T2D) constitute one of the most vulnerable subgroups in COVID-19. Despite high vaccination rates, a correlate of protection to advise vaccination strategies for novel SARS-CoV-2 variants of concern and lower mortality in this high-risk group is still missing. It is further unclear what antibody levels provide protection and whether pre-existing organ damage affects this threshold. To address these gaps, we conducted a prospective multicenter cohort study on 1152 patients with COVID-19 from five hospitals. Patients were classified by diabetes and vaccination status. Anti-SARS-CoV-2-spike-antibodies, creatinine and NTproBNP were measured on hospital admission. Pre-specified endpoints were all-cause in-hospital-mortality, ICU admission, endotracheal intubation, and oxygen administration. Propensity score matching was applied to increase comparability. We observed significantly lower anti-SARS-CoV-2-spike-antibodies in diabetic non-survivors compared to survivors (mean, 95% CI 351BAU/ml, 106-595 vs. 1123, 968-1279, p < 0.001). Mortality risk increased two-fold with each standard deviation-decrease of antibody levels (aHR 1.988, 95% CI 1.229-3.215, p = 0.005). T2D patients requiring oxygen administration, endotracheal intubation and ICU admission had significantly lower antibody levels than those who did not (p < 0.001, p = 0.046, p = 0.011). While T2D patients had significantly worse outcomes than non-diabetic patients, the differences were less pronounced compared to propensity-score-matched non-diabetic patients. Anti-SARS-CoV-2 spike antibodies on hospital admission are inversely associated with oxygen administration, endotracheal intubation, intensive care and in-hospital mortality in diabetic COVID-19 patients. Pre-existing comorbidities may have a greater impact on outcome than diabetes status alone.

SARS-CoV-2 external structures interacting with nanospheres using docking and molecular dynamics

Coronavirus is caused by the SARS-CoV-2 virus has shown rapid proliferation and scarcity of treatments with proven effectiveness. In this way, we simulated the hospitalization of carbon nanospheres, with external active sites of the SARS-CoV-2 virus (M-Pro, S-Gly and E-Pro), which can be adsorbed or inactivated when interacting with the nanospheres. The computational procedures performed in this work were developed with the SwissDock server for molecular docking and the GROMACS software for molecular dynamics, making it possible to extract relevant data on affinity energy, distance between molecules, free Gibbs energy and mean square deviation of atomic positions, surface area accessible to solvents. Molecular docking indicates that all ligands have an affinity for the receptor's active sites. The nanospheres interact favorably with all proteins, showing promising results, especially C60, which presented the best affinity energy and RMSD values ​​for all protein macromolecules investigated. The C60 with E-Pro exhibited the highest affinity energy of -9.361 kcal/mol, demonstrating stability in both molecular docking and molecular dynamics simulations. Our RMSD calculations indicated that the nanospheres remained predominantly stable, fluctuating within a range of 2 to 3 Å. Additionally, the analysis of other structures yielded promising results that hold potential for application in other proteases.Communicated by Ramaswamy H. Sarma.

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.

Factors contributing to poor COVID-19 outcomes in diabetic patients: Findings from a single-center cohort study

Diabetes Mellitus (DM) is a frequent comorbidity in patients infected with the SARS-CoV-2 virus. The risk of developing severe or critical COVID-19 and higher mortality was observed to be increased in diabetic patients hospitalized due to COVID-19. In this study we aimed to find out the impact of clinical characteristics, comorbidities, laboratory results, and complications on the outcomes of diabetic patients hospitalized due to COVID-19. This article is a retrospective cohort study that include diabetic patients hospitalized with COVID-19 infection. A definition of diabetes was based on the past history of diabetes or if the HbA1c was 6.5% or higher. Demographics, clinical characteristics, comorbidities, laboratory results, and complications were extracted from the electronic medical records. The mortality rate increased with increasing age (from 5.56% in younger patients to 46% in the elderly) and with severity (from 25.71% in moderate cases to 43.77% in critical cases). We found that a critical severity on admission (OR: 5.26, 95% CI: 1.28-21.66, p = 0.0214), a history of stroke (OR: 8.37, 95% CI: 2.2-31.88, p = 0.0018), and low calcium levels on admission (OR: 2.23, 95% CI: 1.01-4.91, p = 0.0475) were significant risk factors predicting higher COVID-19 mortality in diabetic patients. The findings of this study suggest that reduced calcium levels could potentially indicate higher mortality due to COVID-19 in patients with DM. Furthermore, careful monitoring of diabetic patients hospitalized due to COVID-19 infection, especially those with critical disease severity or those with a history of stroke, may improve their outcome and lessen mortality.

Clinical characteristics and acute complication of COVID-19 patients with diabetes: a multicenter, retrospective study in Southern China

Aims

This study aims to describe the clinical characteristics, laboratory data and complications of hospitalized COVID-19 patients with type 2 diabetes mellitus (T2DM) since epidemic prevention and control optimization was adjusted in December 2022 in China.

Methods

This retrospective multicenter study included 298 patients with confirmed type 2 diabetes mellitus with or without COVID-19. We collected data from the first wave of the pandemic in The Fifth Affiliated Hospital of Guangzhou Medical University, Loudi Central Hospital and The First People's Hospital of Xiangtan from December 1, 2022 to February 1, 2023. We extracted baseline data, clinical symptoms, acute complications, laboratory findings, treatment and outcome data of each patient from electronic medical records.

Results

For among 298 hospitalized patients with type 2 diabetes, 136 (45.6%) were COVID-19 uninfected, and 162 (54.4%) were COVID-19 infected. We found that the incidence of cough, fatigue, fever, muscle soreness, sore throat, shortness of breath, hyposmia, hypogeusia and polyphagia (all p<0.01) were significantly higher in the exposure group. They showed higher levels of ketone (p=0.04), creatinine (p<0.01), blood potassium (p=0.01) and more diabetic ketoacidosis (p<0.01). Patients with COVID-19 less use of metformin (p<0.01), thiazolidinediones (p<0.01) and SGLT2 (p<0.01) compared with patients without COVID-19.

Conclusion

COVID-19 patients with diabetes showed more severe respiratory and constitutional symptoms and an increased proportion of hyposmia and hypogeusia. Moreover, COVID-19 patients with diabetes have a higher incidence of acute complications, are more prone to worsening renal function, and are more cautious about the use of antidiabetic drugs.

Risk phenotypes of diabetes and association with COVID-19 severity and death: an update of a living systematic review and meta-analysis

AIMS/HYPOTHESIS

To provide a systematic overview of the current body of evidence on high-risk phenotypes of diabetes associated with COVID-19 severity and death.

METHODS

This is the first update of our recently published living systematic review and meta-analysis. Observational studies investigating phenotypes in individuals with diabetes and confirmed SARS-CoV-2 infection with regard to COVID-19-related death and severity were included. The literature search was conducted from inception up to 14 February 2022 in PubMed, Epistemonikos, Web of Science and the COVID-19 Research Database and updated using PubMed alert to 1 December 2022. A random-effects meta-analysis was used to calculate summary relative risks (SRRs) with 95% CIs. The risk of bias was evaluated using the Quality in Prognosis Studies (QUIPS) tool and the certainty of evidence using the GRADE approach.

RESULTS

A total of 169 articles (147 new studies) based on approximately 900,000 individuals were included. We conducted 177 meta-analyses (83 on COVID-19-related death and 94 on COVID-19 severity). Certainty of evidence was strengthened for associations between male sex, older age, blood glucose level at admission, chronic insulin use, chronic metformin use (inversely) and pre-existing comorbidities (CVD, chronic kidney disease, chronic obstructive pulmonary disease) and COVID-19-related death. New evidence with moderate to high certainty emerged for the association between obesity (SRR [95% CI] 1.18 [1.04, 1.34], n=21 studies), HbA1c (53-75 mmol/mol [7-9%]: 1.18 [1.06, 1.32], n=8), chronic glucagon-like peptide-1 receptor agonist use (0.83 [0.71, 0.97], n=9), pre-existing heart failure (1.33 [1.21, 1.47], n=14), pre-existing liver disease (1.40 [1.17, 1.67], n=6), the Charlson index (per 1 unit increase: 1.33 [1.13, 1.57], n=2), high levels of C-reactive protein (per 5 mg/l increase: 1.07 [1.02, 1.12], n=10), aspartate aminotransferase level (per 5 U/l increase: 1.28 [1.06, 1.54], n=5), eGFR (per 10 ml/min per 1.73 m2 increase: 0.80 [0.71, 0.90], n=6), lactate dehydrogenase level (per 10 U/l increase: 1.03 [1.01, 1.04], n=7) and lymphocyte count (per 1×109/l increase: 0.59 [0.40, 0.86], n=6) and COVID-19-related death. Similar associations were observed between risk phenotypes of diabetes and severity of COVID-19, with some new evidence on existing COVID-19  vaccination status (0.32 [0.26, 0.38], n=3), pre-existing hypertension (1.23 [1.14, 1.33], n=49), neuropathy and cancer, and high IL-6 levels. A limitation of this study is that the included studies are observational in nature and residual or unmeasured confounding cannot be ruled out.

CONCLUSIONS/INTERPRETATION

Individuals with a more severe course of diabetes and pre-existing comorbidities had a poorer prognosis of COVID-19 than individuals with a milder course of the disease.

REGISTRATION

PROSPERO registration no. CRD42020193692.

PREVIOUS VERSION

This is a living systematic review and meta-analysis. The previous version can be found at https://link.springer.com/article/10.1007/s00125-021-05458-8 FUNDING: The German Diabetes Center (DDZ) is funded by the German Federal Ministry of Health and the Ministry of Culture and Science of the State North Rhine-Westphalia. This study was supported in part by a grant from the German Federal Ministry of Education and Research to the German Center for Diabetes Research (DZD).

Circulating ACE2 level and zinc/albumin ratio as potential biomarkers for a precision medicine approach to COVID-19

Highly mutable influenza is successfully countered based on individual susceptibility and similar precision-like medicine approach should be effective against SARS-COV-2. Among predictive markers to bring precision medicine to COVID-19, circulating ACE2 has potential features being upregulated in both severe COVID-19 and predisposing comorbidities. Spike SARS-CoVs were shown to induce ADAM17-mediated shedding of enzymatic active ACE2, thus accounting for its increased activity that has also been suggested to induce positive feedback loops leading to COVID-19-like manifestations. For this reason, pre-existing ACE2 activity and inhibition of ACE2/ADAM17 zinc-metalloproteases through zinc chelating agents have been proposed to predict COVID-19 outcome before infection and to protect from COVID-19, respectively. Since most diagnostic laboratories are not equipped for enzymatic activity determination, other potential predictive markers of disease progression exploitable by diagnostic laboratories were explored. Concentrations of circulating albumin, zinc, ACE2 protein and its activity were investigated in healthy, diabetic (COVID-19-susceptible) and SARS-CoV-2-negative COVID-19 individuals. ACE2 both protein levels and activity significantly increased in COVID-19 and diabetic patients. Abnormal high levels of ACE2 characterised a subgroup (16-19%) of diabetics, while COVID-19 patients were characterised by significantly higher zinc/albumin ratios, pointing to a relative increase of albumin-unbound zinc species, such as free zinc ones. Data on circulating ACE2 levels are in line with the hypothesis that they can drive susceptibility to COVID-19 and elevated zinc/albumin ratios support the therapeutic use of zinc chelating inhibitors of ACE2/ADAM17 zinc-metalloproteases in a targeted therapy for COVID-19.

Diabetes Mellitus and Its Association with Adverse In-Hospital Outcomes in Patients with COVID-19-A Nationwide Study

BACKGROUND

Diabetes mellitus (DM) represents a relevant risk factor regarding morbidity and mortality worldwide. However, only limited data exist regarding the impact of DM on the clinical outcome of patients with COVID-19 infection.

METHODS

All hospitalized patients with confirmed COVID-19-infection (ICD-code U07.1) during the year 2020 in Germany were included in the present study. Patients were stratified regarding the co-prevalence of DM (ICD-codes E10-E14), and the impact of DM on in-hospital case fatality and in-hospital adverse events was analyzed.

RESULTS

Overall, 176,137 hospitalizations with confirmed COVID-19 infection were documented; of these, 45,232 (25.7%) patients had an additional diagnosis of DM. Diabetic patients with COVID-19 were more often of male sex and 7 years older (median 76.0 (IQR: 66.0-83.0) vs. 69.0 (52.0-81.0) years, p < 0.001). COVID-19 patients with DM demonstrated an aggravated comorbidity profile, as reflected by a higher Charlson comorbidity index (6.0 (IQR: 4.0-8.0) vs. 3.0 (1.0-5.0), p < 0.001). Risk for pneumonia (OR 1.38 (95% CI: 1.35-1.41), p < 0.001), acute respiratory distress syndrome (OR 1.53 (95% CI: 1.47-1.60), p < 0.001), and need for intensive care (21.3% vs. 13.3%, p < 0.001) were increased in DM patients. DM was an independent risk factor for acute kidney failure (OR 1.49 (95% CI: 1.44-1.53), p < 0.001), dialysis (OR 1.56 (95% CI: 1.47-1.66), p < 0.001), mechanical ventilation (OR: 1.49 (95% CI: 1.43-1.56), p < 0.001), extracorporeal membrane oxygenation (OR 1.44 (95% CI: 1.27-1.62), p < 0.001), major adverse cardiac and cerebrovascular events (OR: 1.24 (95% CI: 1.20-1.27), p < 0.001), and in-hospital mortality (OR: 1.26 (95% CI: 1.22-1.30), p < 0.001).

CONCLUSIONS

In patients with COVID-19-infection, DM is a relevant risk factor for adverse events, including mortality. The vulnerable patient group of diabetics with COVID-19 requires intense medical care and monitoring during hospitalization.

Molecular Mechanisms Responsible for Diabetogenic Effects of COVID-19 Infection-Induction of Autoimmune Dysregulation and Metabolic Disturbances

The COVID-19 pandemic has revealed a significant association between SARS-CoV-2 infection and diabetes, whereby individuals with diabetes are more susceptible to severe disease and higher mortality rates. Interestingly, recent findings suggest a reciprocal relationship between COVID-19 and diabetes, wherein COVID-19 may contribute to developing new-onset diabetes and worsen existing metabolic abnormalities. This narrative review aims to shed light on the intricate molecular mechanisms underlying the diabetogenic effects of COVID-19. Specifically, the review explores the potential role of various factors, including direct damage to β-cells, insulin resistance triggered by systemic inflammation, and disturbances in hormonal regulation, aiming to enhance our understanding of the COVID-19 impact on the development and progression of diabetes. By analysing these mechanisms, the aim is to enhance our understanding of the impact of COVID-19 on the development and progression of diabetes. The binding of SARS-CoV-2 to angiotensin-converting enzyme 2 (ACE2) receptors, which are present in key metabolic organs and tissues, may interfere with glucometabolic pathways, leading to hyperglycaemia, and potentially contribute to the development of new disease mechanisms. The virus's impact on β-cells through direct invasion or systemic inflammation may induce insulin resistance and disrupt glucose homeostasis. Furthermore, glucocorticoids, commonly used to treat COVID-19, may exacerbate hyperglycaemia and insulin resistance, potentially contributing to new-onset diabetes. The long-term effects of COVID-19 on glucose metabolism are still unknown, necessitating further research into the possibility of developing a novel type of diabetes. This article provides a comprehensive overview of the current understanding of the interaction between COVID-19 and diabetes, highlighting potential areas for future research and therapeutic interventions.

Assessment of the Immune Response in Patients with Insulin Resistance, Obesity, and Diabetes to COVID-19 Vaccination

The SARS-CoV-19 pandemic overwhelmed multiple healthcare systems across the world. Patients with underlying medical conditions such as obesity or diabetes were particularly vulnerable, had more severe symptoms, and were more frequently hospitalized. To date, there have been many studies on the severity of SARS-CoV-2 in patients with metabolic disorders, but data on the efficiency of vaccines against COVID-19 are still limited. This paper aims to provide a comprehensive overview of the effectiveness of COVID-19 vaccines in individuals with diabetes, insulin resistance, and obesity. A comparison is made between the immune response after vaccination in patients with and without metabolic comorbidities. Additionally, an attempt is made to highlight the mechanisms of immune stimulation affected by SARS-CoV-2 vaccines and how metabolic comorbidities modulate these mechanisms. The focus is on the most common COVID-19 vaccines, which include mRNA vaccines such as Pfizer-BioNTech and Moderna, as well as viral vector vaccines such as AstraZeneca and Johnson & Johnson. Furthermore, an effort is made to clarify how the functional differences between these vaccines may impact the response in individuals with metabolic disorders, drawing from available experimental data. This review summarizes the current knowledge regarding the post-vaccination response to COVID-19 in the context of metabolic comorbidities such as diabetes, insulin resistance, and obesity.

Recent trends and advances in type 1 diabetes therapeutics: A comprehensive review

Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by the destruction of pancreatic β-cells, leading to insulin deficiency. Insulin replacement therapy is the current standard of care for T1D, but it has significant limitations. However, stem cell-based replacement therapy has the potential to restore β-cell function and achieve glycaemic control eradicating the necessity for drugs or injecting insulin externally. While significant progress has been made in preclinical studies, the clinical translation of stem cell therapy for T1D is still in its early stages. In continuation, further research is essentially required to determine the safety and efficacy of stem cell therapies and to develop strategies to prevent immune rejection of stem cell-derived β-cells. The current review highlights the current state of cellular therapies for T1D including, different types of stem cell therapies, gene therapy, immunotherapy, artificial pancreas, and cell encapsulation being investigated, and their potential for clinical translation.

Hyperglycemia Associated With Raynaud Phenomenon and Liver Dysfunction After COVID-19 Vaccination in Type 1 Diabetes Mellitus

Background/Objective

The association of COVID-19 vaccinations and the changes in glycemic control remains debatable. We report a case of a patient with type 1 diabetes mellitus (DM) with previously well-controlled glucose on a hybrid closed-loop insulin pump who developed significant glucose variation, new onset Raynaud phenomenon, and liver dysfunction after the vaccination.

Case Report

A 33-year-old man with type 1 DM since the age of 5 years was on an insulin pump for 17 years. He had a reasonable controlled glucose level with a hemoglobin A1c level of 6.8% (51 mmol/mol). Three days after he received the COVID-19 vaccination, his glucose level started to fluctuate in the range of 46 to 378 mg/dL with 3.5 times higher total daily insulin requirement. The patient developed white-pale cold hands, weight gain, fatigue, and liver dysfunction. Computed tomography of the abdomen revealed mild hepatomegaly, and laboratory workup was negative for hepatitis. One month later, his glucose level became better controlled, and his liver function improved. Continuous glucose monitoring revealed that his glucose profile returned to baseline after 6 weeks.

Discussion

COVID-19 vaccination resulted in significant glucose variation and fluctuations in this patient. It could be explained by the vaccine-induced immune response causing an increase in insulin resistance, such as in adipose tissue and muscle cells. Immune stimulation could have also caused the abnormal liver function and explain his new onset Raynaud phenomenon.

Conclusion

We described, for the first time, the long-term continuous glucose monitoring glucose profile with a hybrid closed-loop system in type 1 DM after COVID-19 vaccination. Clinicians need to keep alert to glycemic excursion and side effects after immunization in type 1 DM.

Causal associations between type 1 diabetes and COVID-19 infection and prognosis: a two-sample Mendelian randomization study

INTRODUCTION

It has been suggested that type 1 diabetes was associated with increased COVID-19 morbidity and mortality. However, their causal relationship is still unclear. Herein, we performed a two-sample Mendelian randomization (MR) to investigate the causal effect of type 1 diabetes on COVID-19 infection and prognosis.

RESEARCH DESIGN AND METHODS

The summary statistics of type 1 diabetes were obtained from two published genome-wide association studies of European population, one as a discovery sample including 15 573 cases and 158 408 controls, and the other data as a replication sample consisting of 5913 cases and 8828 controls. We first performed a two-sample MR analysis to evaluate the causal effect of type 1 diabetes on COVID-19 infection and prognosis. Then, reverse MR analysis was conducted to determine whether reverse causality exists.

RESULTS

MR analysis results showed that the genetically predicted type 1 diabetes was associated with higher risk of severe COVID-19 (OR=1.073, 95% CI: 1.034 to 1.114, p_FDR=1.15×10^-3) and COVID-19 death (OR=1.075, 95% CI: 1.033 to 1.119, p_FDR=1.15×10^-3). Analysis of replication dataset showed similar results, namely a positive association between type 1 diabetes and severe COVID-19 (OR=1.055, 95% CI: 1.029 to 1.081, p_FDR=1.59×10^-4), and a positively correlated association with COVID-19 death (OR=1.053, 95% CI: 1.026 to 1.081, p_FDR=3.50×10^-4). No causal association was observed between type 1 diabetes and COVID-19 positive, hospitalized COVID-19, the time to the end of COVID-19 symptoms in the colchicine treatment group and placebo treatment group. Reverse MR analysis showed no reverse causality.

CONCLUSIONS

Type 1 diabetes had a causal effect on severe COVID-19 and death after COVID-19 infection. Further mechanistic studies are needed to explore the relationship between type 1 diabetes and COVID-19 infection and prognosis.

Prediction of in-hospital mortality rate in COVID-19 patients with diabetes mellitus using machine learning methods

Background

Since its emergence in December 2019, until June 2022, coronavirus 2019 (COVID-19) has impacted populations all around the globe with it having been contracted by ~ 535 M people and leaving ~ 6.31 M dead. This makes identifying and predicating COVID-19 an important healthcare priority.

Method and Material

The dataset used in this study was obtained from Shahid Beheshti University of Medical Sciences in Tehran, and includes the information of 29,817 COVID-19 patients who were hospitalized between October 8, 2019 and March 8, 2021. As diabetes has been shown to be a significant factor for poor outcome, we have focused on COVID-19 patients with diabetes, leaving us with 2824 records.

Results

The data has been analyzed using a decision tree algorithm and several association rules were mined. Said decision tree was also used in order to predict the release status of patients. We have used accuracy (87.07%), sensitivity (88%), and specificity (80%) as assessment metrics for our model.

Conclusion

Initially, this study provided information about the percentages of admitted Covid-19 patients with various underlying disease. It was observed that diabetic patients were the largest population at risk. As such, based on the rules derived from our dataset, we found that age category (51-80), CPR and ICU residency play a pivotal role in the discharge status of diabetic inpatients.

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.

The impact of pre-existing cross-reactive immunity on SARS-CoV-2 infection and vaccine responses

Pre-existing cross-reactive immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins in infection-naive subjects have been described by several studies. In particular, regions of high homology between SARS-CoV-2 and common cold coronaviruses have been highlighted as a likely source of this cross-reactivity. However, the role of such cross-reactive responses in the outcome of SARS-CoV-2 infection and vaccination is currently unclear. Here, we review evidence regarding the impact of pre-existing humoral and T cell immune responses to outcomes of SARS-CoV-2 infection and vaccination. Furthermore, we discuss the importance of conserved coronavirus epitopes for the rational design of pan-coronavirus vaccines and consider cross-reactivity of immune responses to ancestral SARS-CoV-2 and SARS-CoV-2 variants, as well as their impact on COVID-19 vaccination.

The Influence of Age, Sex, and Socioeconomic Status on Glycemic Control Among People With Type 1 and Type 2 Diabetes in Canada: Patient-Led Longitudinal Retrospective Cross-sectional Study With Multiple Time Points of Measurement

BACKGROUND

Clinical guidelines for most adults with diabetes recommend maintaining hemoglobin A1c (HbA1c) levels ≤7% (≤53 mmol/mol) to avoid microvascular and macrovascular complications. People with diabetes of different ages, sexes, and socioeconomic statuses may differ in their ease of attaining this goal.

OBJECTIVE

As a team of people with diabetes, researchers, and health professionals, we aimed to explore patterns in HbA1c results among people with type 1 or type 2 diabetes in Canada. Our research question was identified by people living with diabetes.

METHODS

In this patient-led retrospective cross-sectional study with multiple time points of measurement, we used generalized estimating equations to analyze the associations of age, sex, and socioeconomic status with 947,543 HbA1c results collected from 2010 to 2019 among 90,770 people living with type 1 or type 2 diabetes in Canada and housed in the Canadian National Diabetes Repository. People living with diabetes reviewed and interpreted the results.

RESULTS

HbA1c results ≤7.0% represented 30.5% (male people living with type 1 diabetes), 21% (female people living with type 1 diabetes), 55% (male people living with type 2 diabetes) and 59% (female people living with type 2 diabetes) of results in each subcategory. We observed higher HbA1c values during adolescence, and for people living with type 2 diabetes, among people living in lower income areas. Among those with type 1 diabetes, female people tended to have lower HbA1c levels than male people during childbearing years but higher HbA1c levels than male people during menopausal years. Team members living with diabetes confirmed that the patterns we observed reflected their own life courses and suggested that these results be communicated to health professionals and other stakeholders to improve the treatment for people living with diabetes.

CONCLUSIONS

A substantial proportion of people with diabetes in Canada may need additional support to reach or maintain the guideline-recommended glycemic control goals. Blood sugar management goals may be particularly challenging for people going through adolescence or menopause or those living with fewer financial resources. Health professionals should be aware of the challenging nature of glycemic management, and policy makers in Canada should provide more support for people with diabetes to live healthy lives.

Increase in hypoglycaemia and hyperglycaemia in people with diabetes admitted to hospital during COVID-19 pandemic

BACKGROUND

We used detailed information on patients with diabetes admitted to hospital to determine differences in clinical outcomes before and during the COVID-19 pandemic in the UK.

METHODS

The study used electronic patient record data from Imperial College Healthcare NHS Trust. Hospital admission data for patients coded for diabetes was analysed over three time periods: pre-pandemic (31st January 2019-31st January 2020), Wave 1 (1st February 2020-30th June 2020), and Wave 2 (1st September 2020-30th April 2021). We compared clinical outcomes including glycaemia and length of stay.

RESULTS

We analysed data obtained from 12,878, 4008 and 7189 hospital admissions during the three pre-specified time periods. The incidence of Level 1 and Level 2 hypoglycaemia was significantly higher during Waves 1 and 2 compared to the pre-pandemic period (25 % and 25.1 % vs. 22.9 % for Level 1 and 11.7 % and 11.5 % vs. 10.3 % for Level 2). The incidence of hyperglycaemia was also significantly higher during the two waves. The median hospital length of stay increased significantly (4.1[1.6, 9.8] and 4.0[1.4, 9.4] vs. 3.5[1.2, 9.2] days).

CONCLUSIONS

During the COVID-19 pandemic in the UK, hospital in-patients with diabetes had a greater number of hypoglycaemic/hyperglycaemic episodes and an increased length of stay when compared to the pre-pandemic period. This highlights the necessity for a focus on improved diabetes care during further significant disruptions to healthcare systems and ensuring minimisation of the impact on in-patient diabetes services.

SUMMARY

Diabetes is associated with poorer outcomes from COVID-19. However the glycaemic control of inpatients before and during the COVID-19 pandemic is unknown. We found the incidence of hypoglycaemia and hyperglycaemia was significantly higher during the pandemic highlighting the necessity for a focus on improved diabetes care during further pandemics.

The retrospective study of the metabolic patterns of BCG-vaccination in type-2 diabetic individuals in COVID-19 infection

Background

The cross-protective nature of Bacillus Calmette-Guerin (BCG) vaccine against SARS-CoV-2 virus was previously suggested, however its effect in COVID-19 patients with type 2 diabetes (T2D) and the underlying metabolic pathways has not been addressed. This study aims to investigate the difference in the metabolomic patterns of type 2 diabetic patients with BCG vaccination showing different severity levels of COVID-19 infection.

Methods

Sixty-seven COVID-19 patients were categorized into diabetic and non-diabetic individuals who had been previously vaccinated or not with BCG vaccination. Targeted metabolomics were performed from serum samples from all patients using tandem mass spectrometry. Statistical analysis included multivariate and univariate models.

Results

Data suggested that while BCG vaccination may provide protection for individuals who do not have diabetes, it appears to be linked to more severe COVID-19 symptoms in T2D patients (p = 0.02). Comparing the metabolic signature of BCG vaccinated T2D individuals to non-vaccinated counterparts revealed that amino acid (sarcosine), cholesterol esters (CE 20:0, 20:1, 22:2), carboxylic acid (Aconitic acid) were enriched in BCG vaccinated T2D patients, whereas spermidine, glycosylceramides (Hex3Cer(d18:1_22:0), Hex2Cer(d18:1/22:0), HexCer(d18:1/26:1), Hex2Cer(d18:1/24:0), HexCer(d18:1/22:0) were higher in BCG vaccinated non- T2D patients. Furthermore, data indicated a decrease in sarcosine synthesis from glycine and choline and increase in spermidine synthesis in the BCG vaccinated cohort in T2D and non-T2D groups, respectively.

Conclusion

This pilot study suggests increased severity of COVID-19 in BCG vaccinated T2D patients, which was marked by decreased sarcosine synthesis, perhaps via lower sarcosine-mediated removal of viral antigens.

Development and validation of DNA methylation scores in two European cohorts augment 10-year risk prediction of type 2 diabetes

Type 2 diabetes mellitus (T2D) presents a major health and economic burden that could be alleviated with improved early prediction and intervention. While standard risk factors have shown good predictive performance, we show that the use of blood-based DNA methylation information leads to a significant improvement in the prediction of 10-year T2D incidence risk. Previous studies have been largely constrained by linear assumptions, the use of cytosine-guanine pairs one-at-a-time and binary outcomes. We present a flexible approach (via an R package, MethylPipeR) based on a range of linear and tree-ensemble models that incorporate time-to-event data for prediction. Using the Generation Scotland cohort (training set n_cases = 374, n_controls = 9,461; test set n_cases = 252, n_controls = 4,526) our best-performing model (area under the receiver operating characteristic curve (AUC) = 0.872, area under the precision-recall curve (PRAUC) = 0.302) showed notable improvement in 10-year onset prediction beyond standard risk factors (AUC = 0.839, precision-recall AUC = 0.227). Replication was observed in the German-based KORA study (n = 1,451, n_cases = 142, P = 1.6 × 10^-5).

Glycemic Control in Critically Ill COVID-19 Patients: Systematic Review and Meta-Analysis

Background: Given the mortality risk in COVID-19 patients, it is necessary to estimate the impact of glycemic control on mortality rates among inpatients by designing and implementing evidence-based blood glucose (BG) control methods. There is evidence to suggest that COVID-19 patients with hyperglycemia are at risk of mortality, and glycemic control may improve outcomes. However, the optimal target range of blood glucose levels in critically ill COVID-19 patients remains unclear, and further research is needed to establish the most effective glycemic control strategies in this population. Methods: The investigation was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Data sources were drawn from Google Scholar, ResearchGate, PubMed (MEDLINE), Cochrane Library, and Embase databases. Randomized controlled trials, non-randomized controlled trials, retrospective cohort studies, and observational studies with comparison groups specific to tight glycemic control in COVID-19 patients with and without diabetes. Results: Eleven observational studies (26,953 patients hospitalized for COVID-19) were included. The incidence of death was significantly higher among COVID-19 patients diagnosed with diabetes than those without diabetes (OR = 2.70 [2.11, 3.45] at a 95% confidence interval). Incidences of death (OR of 3.76 (3.00, 4.72) at a 95% confidence interval) and complications (OR of 0.88 [0.76, 1.02] at a 95% confidence interval) were also significantly higher for COVID-19 patients with poor glycemic control. Conclusion: These findings suggest that poor glycemic control in critically ill patients leads to an increased mortality rate, infection rate, mechanical ventilation, and prolonged hospitalization.

Association between Cardiovascular Risk and Coronavirus Disease 2019: Findings from 2021 National Health Interview Survey

PURPOSE

To examine the association between pre-existing cardiovascular disorders and the risk of coronavirus disease 2019 (COVID-19) among community-dwelling adults in the United States (US).

METHODS

We analyzed data from the 2021 National Health Interview Survey (NHIS), encompassing 28,848 nationally representative participants aged ≥18. We examined the association by two age groups, younger adults (aged 18-59) and older adults (aged>60). Weighted analyses were conducted to consider the complex sampling design used in the NHIS.

RESULTS

Our results show that 13.9% of younger and 8.2% of older adults were infected with coronavirus, corresponding to a nationwide estimate of 23,701,358 COVID-19 cases in younger adults and 6,310,206 in older adults in 2021. Subjects who lived in the South region of the US had the highest COVID-19 rate (13.4%), followed by the Midwest (12.6%), West (10.9%), and Northeast (10.4%). Pre-existing cardiovascular risk factors (overweight, obesity, hypertension, and diabetes) were significantly associated with increased risk for COVID-19 infection in younger and older adults. Pre-existing cardiovascular diseases (angina, heart attack, and coronary heart disease) were significantly associated with COVID-19 in older adults but not significantly in younger adults. Significant dose-response relationships existed between the increased number of pre-existing cardiovascular risk factors and COVID-19 infection, with the strongest association in non-Hispanic (NH) Black and Hispanic ethnicities compared to NH White.

CONCLUSION

Pre-existing cardiovascular disorders are significantly associated with the risk of COVID-19 infection. The magnitudes of this risk association are stronger among the minority populations than NH White. Further studies are needed to determine the long-term impact of COVID-19 infection and its relationship to pre-existing cardiovascular disorders.

Insight on Infections in Diabetic Setting

The correlation between diabetes mellitus and infectious diseases is widely recognized. DM patients are characterized by the impaired function of the immune system. This translates into the occurrence of a variety of infections, including urinary tract, skin and surgical site infections, pneumonia, tuberculosis, and, more recently, SARS-CoV-2. Hyperglycemia has been identified as a relevant factor contributing to unfavorable outcomes in hospitalized patients including SARS-CoV-2 patients. Several studies have been performed proving that to maintain the proper and stringent monitoring of glycemia, a balanced diet and physical activity is mandatory to reduce the risk of infections and their associated complications. This review is focused on the mechanisms accounting for the increased susceptibility of DM patients to infections, with particular attention to the impact of newly introduced hypoglycemic drugs in sepsis management.

COVID-19 and diabetes in 2020: a systematic review

Attempts were made to review the literature on diabetic patients who experience complications when they contract COVID-19, and to determine whether ethnicity and other risk factors play an important role in the development of symptoms and their severity, as well as responding to medications. A literature search was performed using five keywords, namely COVID-19, diabetes, ethnicity, medications, and risk factors between January 2019 and December 2020 using electronic databases such as PubMed, Science Direct, Google Scholar, Springer Link, and Scopus. Forty studies were included. The review indicated that diabetes was a significant risk factor for poorer outcomes and increased mortality associated with COVID-19. There were several risk factors for diabetic patients that increased their likelihood of poorer outcomes associated with COVID-19. These included black and Asian ethnicity, male sex with high BMI. In conclusion, patients with diabetes of black or Asian origin with high BMI, male sex, and older age had an increased risk of poorer outcomes associated with COVID-19. This highlights the importance of considering the history of the patient in prioritising care and treatment.