Plasma glucose levels and diabetes are independent predictors for mortality and morbidity in patients with SARS

Diabetes and Infectious Diseases with a Focus on Melioidosis

Diabetes mellitus (DM) leads to impaired innate and adaptive immune responses. This renders individuals with DM highly susceptible to microbial infections such as COVID-19, tuberculosis and melioidosis. Melioidosis is a tropical disease caused by the bacterial pathogen Burkholderia pseudomallei, where diabetes is consistently reported as the most significant risk factor associated with the disease. Type-2 diabetes is observed in 39% of melioidosis patients where the risk of infection is 13-fold higher than non-diabetic individuals. B. pseudomallei is found in the environment and is an opportunistic pathogen in humans, often exhibiting severe clinical manifestations in immunocompromised patients. The pathophysiology of diabetes significantly affects the host immune responses that play a critical role in fighting the infection, such as leukocyte and neutrophil impairment, macrophage and monocyte inhibition and natural killer cell dysfunction. These defects result in delayed recruitment as well as activation of immune cells to target the invading B. pseudomallei. This provides an advantage for the pathogen to survive and adapt within the immunocompromised diabetic patients. Nevertheless, knowledge gaps on diabetes-infectious disease comorbidity, in particular, melioidosis-diabetes comorbidity, need to be filled to fully understand the dysfunctional host immune responses and adaptation of the pathogen under diabetic conditions to guide therapeutic options.

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.

Long-Term Impairment of Working Ability in Subjects under 60 Years of Age Hospitalised for COVID-19 at 2 Years of Follow-Up: A Cross-Sectional Study

Background: Coronavirus disease 2019 (COVID-19) can lead to persistent and debilitating symptoms referred to as Post-Acute sequelae of SARS-CoV-2 infection (PASC) This broad symptomatology lasts for months after the acute infection and impacts physical and mental health and everyday functioning. In the present study, we aimed to evaluate the prevalence and predictors of long-term impairment of working ability in non-elderly people hospitalised for COVID-19. Methods: This cross-sectional study involved 322 subjects hospitalised for COVID-19 from 1 March 2020 to 31 December 2022 in the University Hospital of Bari, Apulia, Italy, enrolled at the time of their hospital discharge and followed-up at a median of 731 days since hospitalization (IQR 466-884). Subjects reporting comparable working ability and those reporting impaired working ability were compared using the Mann-Whitney test (continuous data) and Fisher's test or Chi-Square test (categorical data). Multivariable analysis of impaired working ability was performed using a logistic regression model. Results: Among the 322 subjects who were interviewed, 184 reported comparable working ability (57.1%) and 134 reported impaired working ability (41.6%) compared to the pre-COVID-19 period. Multivariable analysis identified age at hospital admission (OR 1.02, 95% CI 0.99 to 1.04), female sex (OR 1.90, 95% CI 1.18 to 3.08), diabetes (OR 3.73, 95% CI 1.57 to 9.65), receiving oxygen during hospital stay (OR 1.76, 95% CI 1.01 to 3.06), and severe disease (OR 0.51, 95% CI 0.26 to 1.01) as independent predictors of long-term impaired working ability after being hospitalised for COVID-19. Conclusions: Our findings suggest that PASC promotes conditions that could result in decreased working ability and unemployment. These results highlight the significant impact of this syndrome on public health and the global economy, and the need to develop clinical pathways and guidelines for long-term care with specific focus on working impairment.

Diabetes Mellitus and Pneumococcal Pneumonia

Currently, there are more than 500 million people suffering from diabetes around the world. People aged 65 years or older are the most affected by this disease, and it is estimated that approximately 96% of diabetes cases worldwide are type 2 diabetes. People with diabetes mellitus are at an increased risk of infections such as pneumonia, due to a series of factors that may contribute to immune dysfunction, including hyperglycemia, inhibition of neutrophil chemotaxis, impaired cytokine production, phagocytic cell dysfunction, altered T cell-mediated immune responses and the co-existence of chronic comorbidities. Rates of infection, hospitalization and mortality in diabetic patients are reported to be higher than in the general population. Research into the risk of infectious diseases such as pneumonia in these patients is very important because it will help improve their management and treatment.

Comorbidities and their association with COVID-19 mortality in Mexico between January 2020 and August 2021

By August 17, 2021, 4.3 million people had died globally as a result of SARS-CoV-2 infection. While data collection is ongoing, it is abundantly obvious that this is one of the most significant public health crises in modern history. Consequently, global efforts are being made to attain a greater understanding of this disease and to identify risk factors associated with more severe outcomes. The goal of this study is to identify clinical characteristics and risk factors associated with COVID-19 mortality in Mexico. The dataset used in this study was released by Sistema Nacional de Vigilancia Epidemiologica de Enfermedades Respiratorias (SISVER) de la Secretaría de Salud and contains 2.9 million COVID-19 cases. The effects of risk factors on COVID-19 mortality were estimated using multivariable logistic regression models with generalized estimation equation and Kaplan-Meier curves. Case fatality rates, case hospitalization rates are also reported using the Centers for Disease Control and Prevention (CDC) USA death-to-case ratio method. In general, older males with pre-existing conditions had higher odds of death. Age greater than 40, male sex, hypertension, diabetes, and obesity are associated with higher COVID-19 mortality. End-stage renal disease, chronic obstructive pulmonary disease, and immunosuppression are all linked with COVID-19 patient fatalities. Smoking and Asthma are associated with lower COVID-19 mortality which is consistent with findings from the article published in Nature based on National Health Service (NHS) of UK dataset (17 million cases). Intensive care unit (ICU), patient intubation, and pneumonia diagnosis are shown to substantially increase mortality risk for COVID-19 patients.

Leishmania amazonensis infection regulates oxidate stress in hyperglycemia and diabetes impairing macrophage's function and immune response

Leishmaniasis is a group of infectious diseases caused by protozoa of the Leishmania genus and its immunopathogenesis results from an unbalanced immune response during the infection. Diabetes is a chronic disease resulting from dysfunction of the body's production of insulin or the ability to use it properly, leading to hyperglycemia causing tissue damage and impairing the immune system.

AIMS

The objective of this work was to evaluate the effects of hyperglycemia and diabetes during Leishmania amazonensis infection and how these conditions alter the immune response to the parasite.

METHODS

An in vitro hyperglycemic stimulus model using THP-1-derived macrophages and an in vivo experimental diabetes with streptozotocin (STZ) in C57BL/6 mice was employed to investigate the impact of diabetes and hyperglicemia in Leishmania amazonensis infection.

RESULTS

We observed that hyperglycemia impair the leishmanicidal capacity of macrophages derived from THP-1 cells and reverse the resistance profile that C57BL/6 mice have against infection by L. amazonensis, inducing more exacerbated lesions compared to non-diabetic animals. In addition, the hyperglycemic stimulus favored the increase of markers related to the phenotype of M2 macrophages. The induction of experimental diabetes in C57BL/6 mice resulted in a failure in the production of nitric oxide (NO) in the face of infection and macrophages from diabetic animals failed to process and present Leishmania antigens, being unable to activate and induce proliferation of antigen-specific lymphocytes.

CONCLUSION

Together, these data demonstrate that diabetes and hyperglycemia can impair the cellular immune response, mainly of macrophages, against infection by parasites of the genus Leishmania.

Prevalence of Diabetes, Ketosis, and Ketoacidosis and Their Correlation With Mortality in Critical COVID-19 Patients: A Single-Center Retrospective Study

Aim We aimed to find out the prevalence of diabetes, ketosis, and ketoacidosis in coronavirus disease 2019 (COVID-19) critically ill patients and to explore the clinical impact of the development of ketosis and ketoacidosis on the outcome of COVID-19 critically ill patients and identify them as potential risk factors for these patients. Methods We collected data on COVID-19 patients admitted to the intensive care unit (ICU) retrospectively. The study population will be classified into two groups based on the presence of diabetes or ketosis. Results The study comprises data on 253 ICU patients admitted with COVID-19 pneumonia. Two hundred patients (79.05%) had diabetes or prediabetes on admission. Seventy-six patients (30%) presented with ketosis. Nine patients had progressed to diabetic ketoacidosis during their ICU stay. Concerning the outcome, among 150 patients who died (59.3%), there was significantly higher mortality among the ketotic patients (69.7%) compared to nonketotic patients (54.8%) with a P-value < 0.027. We noted that the peak blood glucose level during ICU stay was statistically significantly higher in nonsurvivors (mean 345 mg/dl) compared to survivors (mean 298 mg/dl) with a P-value of 0.006. Our data showed that peak serum levels of lactate, procalcitonin (PCT), C-reactive protein, white blood cells (WBC), D dimer, and lactate dehydrogenase strongly positively correlated to the length of ICU stay. We used the ROC curve (receiver operating characteristic curve) to assess the relation between many laboratories and mortality. We noted that uncontrolled hyperglycemia and other laboratory variables are significant predictors of mortality of COVID-19 patients (e.g., peak blood glucose (P = 0.004), PCT (P = 0.047), and P < 0.001 of other laboratories (e.g. lactate, PH, WBC, D dimer, ferritin). Conclusion We reported a high prevalence of diabetes and ketosis among COVID-19 patients admitted to the ICU. Ketosis is associated with an increased mortality risk. Uncontrolled hyperglycemia is a significant predictor of mortality in critically ill COVID-19 patients.

Effect of fasting plasma glucose level in severe fever and thrombocytopenia syndrome patients without diabetes

Hyperglycemia is correlated with worse in-hospital outcomes in acute infectious diseases such as coronavirus disease 2019 (COVID-19) and severe fever with thrombocytopenia syndrome (SFTS). This study assessed the relationship between fasting plasma glucose (FPG) levels and in-hospital mortality, disease type, and secondary infections among individuals with SFTS without preexisting diabetes. The clinical data and laboratory results upon admission of 560 patients with SFTS without preexisting diabetes meeting the inclusion criteria at Wuhan Union Hospital were collected. FPG levels in surviving patients with SFTS subjects were significantly lower than those in patients with SFTS who had died (P<0.0001). In multivariate Cox regression, high FPG level (≥11.1 mmol/L) was a risk factor independently associated with the in-hospital death of patients with SFTS without preexisting diabetes. Similarly, the FPG levels in general patients with SFTS were significantly lower than those in patients with severe SFTS (P<0.0001). Multivariate logistic regression identified high FPG level (7.0-11.1 mmol/L) as a risk factor independently associated with SFTS severity. While FPG levels were comparable between patients with SFTS with and without secondary infection (P = 0.5521), logistic regression analysis revealed that high FPG levels were not a risk factor for secondary infection in patients with SFTS without preexisting diabetes. High FPG level on admission was an independent predictor of in-hospital death and severe disease in individuals with SFTS without preexisting diabetes. FPG screening upon admission and glycemic control are effective methods for improving the prognosis of patients with SFTS.

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.

Does Pre-existing Diabetes Correlate with Long COVID-19 in Europe? Evidence from the Analysis of the Survey of Health, Ageing and Retirement in Europe's Corona Surveys

Background

A substantial proportion of those infected with COVID-19 are presenting with persistent symptoms, referred to as long COVID-19. Emerging evidence suggests that the presence of pre-existing chronic conditions, such as diabetes, may increase the risk of long COVID-19.

Objectives

To investigate whether having pre-existing diabetes increases the risk of developing long COVID-19 in the population of middle-aged and older adults (≥50 years old) in Europe, while assessing if this relationship can be accounted for or is modified by the known long COVID-19 and diabetes risk factors (age, sex, hospitalization, pre-existing hypertension, and weight status).

Methods

A population-based longitudinal prospective study involving a sample of respondents aged 50 years and older (n = 4,004) with probable or confirmed COVID-19 infection from 27 countries that participated in both waves 7 and 8 of the Survey of Health, Ageing and Retirement in Europe and its 2020 and 2021 Corona Surveys. Logistic regression modeling was performed.

Results

Overall, 66.8% of the respondents affected by COVID-19 infection reported at least one long COVID-19 symptom; 55.2% were female, and the average age was 64.6 years; 13.2% had pre-existing diabetes. Respondents with pre-existing diabetes had significantly higher odds of developing long COVID-19, compared to those without diabetes (OR = 1.37; 95% CI = 1.12, 1.68). This relationship remained significant (OR = 2.00; 98% CI = 0.25, 1.14) after adjusting for sex (OR = 1.64 for females; 95% CI = 1.43, 1.88), hospitalization for COVID-19 illness (OR = 3.19; 95% CI = 2.41, 4.23), pre-existing hypertension (OR = 1.17; 95% CI = 1.01, 1.36), and overweight (OR = 1.31; 95% CI = 1.11, 1.56) and obese (OR = 1.77; 95% CI = 1.44, 2.19) weight status. The effect of pre-existing diabetes on the risk of long COVID-19 is moderated by age; it was highest at the age of 50 (OR = 2.00; 95% CI = 1.28, 3.14), and then, it declined with age.

Conclusions

There is a relationship between pre-existing diabetes and long COVID-19, even after controlling for literature-based confounding factors, with age having a moderating effect on this relationship.

Pancreatic and Hepatic Injury in COVID-19: A Worse Prognosis in NAFLD Patients?

The novel disease produced by SARS-CoV-2 mainly harms the respiratory tract, but it has shown the capacity to affect multiple organs. Epidemiologic evidence supports the relationship between Coronavirus Disease 2019 (COVID-19) and pancreatic and hepatic injury development, identified by alterations in these organ function markers. In this regard, it is important to ascertain how the current prevalence of non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) might affect COVID-19 evolution and complications. Although it is not clear how SARS-CoV-2 affects both the pancreas and the liver, a multiplicity of potential pathophysiological mechanisms seem to be implicated; among them, a direct viral-induced injury to the organ involving liver and pancreas ACE2 expression. Additionally, immune system dysregulation, coagulopathies, and drugs used to treat the disease could be key for developing complications associated with the patient's clinical decline. This review aims to provide an overview of the available epidemiologic evidence regarding developing liver and pancreatic alterations in patients with COVID-19, as well as the possible role that NAFLD/NASH might play in the pathophysiological mechanisms underlying some of the complications associated with COVID-19. This review employed a comprehensive search on PubMed using relevant keywords and filters. From the initial 126 articles, those aligning with the research target were selected and evaluated for their methodologies, findings, and conclusions. It sheds light on the potential pathophysiological mechanisms underlying this relationship. As a result, it emphasises the importance of monitoring pancreatic and hepatic function in individuals affected by COVID-19.

Assessment of the Negative Factors for the Clinical Outcome in Patients with SARS-CoV-2 Infection and Type 2 Diabetes Mellitus

Purpose

Patients with diabetes mellitus (DM) are more susceptible to viral and bacterial infections, facing a more severe prognosis and higher mortality rates. The study's main aim was to evaluate the survival and mortality rates of patients with type 2 diabetes (T2DM) and SARS-CoV-2 virus infection alongside the main factors influencing the prognosis.

Patients and Methods

The present study included 186 patients with T2DM and SARS-CoV-2 virus infection admitted to the COVID-19 Department of the "Pius Brînzeu" Emergency Clinical County University Hospital between November 2020 and March 2021. Patients had investigations performed upon arrival in the emergency room and during hospitalization. We analyzed the risk of negative prognosis based on clinical data (oxygen saturation (SatO2), respiratory rate (RR), lung damage), glycemic control (HbA1c, glycemia at hospital admission), and the duration of T2DM.

Results

The mortality rate in the studied group was 36.6%. All deceased patients had previously been diagnosed with hypertension; 95.58% had a body mass index (BMI) greater than 25 kg/m2, and 79.41% presented with cardiovascular disease (CVD). Compared to those who recovered, statistically significant differences were observed in BMI, glycemic levels at admission, glycosylated hemoglobin levels (HbA1c), SatO2, RR, and lung damage. Valid statistically significant predictors for death in T2DM patients with COVID-19 were hyperglycemia at admission > 198mg/dl, HbA1c> 8.6%, and SatO2≤ 87%.

Conclusion

SatO2, glycemia at hospital admission, and HbA1c had the highest sensitivity and specificity to predict the prognosis of T2DM patients with SARS-CoV-2 infection. Glycemic control is essential in the prognosis of patients with DM and COVID-19 infection. The prognosis was worse if other comorbidities were associated, especially hypertension and CVD.

[Features of the course of COVID-19 in patients with type 2 diabetes mellitus]

AIM

To identify the features of the course of COVID-19 in patients with type 2 diabetes mellitus (T2DM), depending on the intake of hypoglycemic therapy at the prehospital stage, in conjunction with the functional state of the kidneys.

MATERIALS AND METHODS

A retrospective analysis of 291 case histories of patients with COVID-19 and T2DM hospitalized in the infection department of Semashko Regional Clinical Hospital from January to December 2021, including the main clinical and laboratory parameters. Results. Among hospitalized patients with COVID-19, patients with T2DM had a higher mortality rate. An analysis of the case histories of deceased patients with COVID-19 and T2DM showed that at admission, body mass index (BMI), C-reactive protein, and creatinine were higher than those of survivors and amounted to BMI - 33 [30; 39] and 33 [28; 36] kg/m3; p=0.039, C-reactive protein - 77 [47.5; 106.0] and 57 [27.0; 89.0] mg/l; p=0.015, in terms of creatinine level - 89 [70.0; 144.0] and 82 [66.0; 101.0] µmol/l; p=0.039, respectively. It was found that in the second week of hospitalization in the group of deceased patients with COVID-19 and T2DM, the creatinine level was statistically significantly higher than in surviving patients and amounted to 94.5 [71.5; 141.0] and 72.5 [57.0; 88.0] µmol/L; p<0.001, respectively. The probability of death in hospitalized patients with type 2 COVID-19 and T2DM depended on BMI and creatinine levels at the second week of hospitalization. Patients with prehospital correction of hyperglycemia dipeptidyl peptidase-4 inhibitors (iDPP-4)/ glucagon-like peptide-1 receptor agonists (agGLP-1)/ sodium-glucose co-transporter 2 inhibitors (iSGLT-2) had significantly lower creatinine levels at week 2 of hospitalization.

CONCLUSION

In patients with moderate to severe COVID-19 with concomitant T2DM, special attention should be paid to the combination of high BMI and creatinine in the second week of hospitalization, which is a prognostically unfavorable predictor of death in such patients.

Lower odds of COVID-19-related mortality in hospitalised patients with type II diabetes mellitus: A single-centre study

BACKGROUND

COVID-19 infection in patients with type 2 diabetes mellitus (T2DM) -a chronic illness in Lebanon-is not well described.

METHODS

This was a single-centre retrospective observational study of 491 patients, including 152 patients with T2DM, who were hospitalised for COVID-19 between 20 August 2020 and 21 April 2021. Data on clinical characteristics, laboratory and radiological findings and outcomes were collected from the electronic medical records. Clinical characteristics and in-hospital mortality between patients with and without T2DM infected with COVID-19 using multivariate analysis were compared.

RESULTS

Patients with T2DM were significantly older than those without T2DM (mean age, 68.7 vs. 60.3 years). Patients with T2DM were more likely to present with a body temperature of <38.3°C (83.9% vs. 69.9%) and less likely to present with chest pain (3.9% vs. 9.1%) and sore throat (2.0% vs. 6.8%). Patients with T2DM were more likely to be hypertensive (76.35% vs. 41%) and dyslipidaemic (58.6% vs. 25.7%) and had more frequent underlying coronary artery disease (33.6% vs. 12.4%). The rates of patients with creatinine levels of ≥1.17 mg/L and troponin T levels of ≥4 ng/dL were higher in the T2DM group than in the non-T2DM group (30.4% vs. 15% and 93.3% vs. 83.1%, respectively). Patients with T2DM were more likely to be admitted to the intensive care unit (ICU) (34.2% vs. 22.1%), require invasive ventilation (18.4% vs. 10.3%) and receive vasopressors (16.4% vs. 10.0%). Increasing age and the use of invasive ventilation and vasopressors were associated with higher odds of mortality (odds ratio (OR), 1.08, 9.95 and 19.83, respectively), whereas longer ICU stay was associated with lower odds of mortality (OR, 0.38). The odds of mortality were lower in the T2DM group than in the non-T2DM group (OR, 0.27).

CONCLUSION

Among patients hospitalised for COVID-19, those with T2DM were older, presented with milder symptoms and had more comorbidities and higher troponin T levels compared with those without T2DM. Despite the worse clinical course, the patients with T2DM had lower odds of mortality than those without T2DM.

Impact of Vaccination on the Course and Outcome of COVID-19 in Patients with Multimorbidity

Vaccination is the most cost-effective method of preventing COVID-19; however, data on its effect on patients with multimorbidity is limited. The aim was to evaluate the effect of vaccination against new coronavirus infection (NCI) in patients with multimorbid pathology in hospital treatment on the outcome of COVID-19 disease. An analysis was carried out of 1832 records of patients in one of the COVID-19 hospitals in Moscow for 2020-2022. Statistical analysis was carried out using the StatTech v. 3.1.3 software, and the binary logistic regression (BLR) method was used to obtain prognostic models. The median age of patients was 69 years, and 76% of them had received two vaccine doses. To assess the outcome of the disease, two prognostic models were obtained depending on the presence of a multimorbidity in patients: cardiovascular pathology and/or atherosclerosis and/or type 2 diabetes mellitus (Model 1) or atherosclerosis and/or type 2 diabetes mellitus and/or encephalopathy (Model 2), against the background of the presence or absence of vaccination against NCI. When assessing the outcome of NCI in Model 1, the odds of death decreased by 3.228 times with two doses of Sputnik V in patients with multimorbidity. According to Model 2, for patients with multimorbidity, the chances of death decreased by 3.281 times with two doses of Sputnik V. The presence of two doses of Sputnik V increased the likelihood of recovery in patients with multimorbidity by more than three times.

The published trend of studies on COVID-19 and diabetes: bibliometric analysis

Background

Since the COVID-19 pandemic outbreak, diabetes mellitus (DM) has been at the core of the confirmed risk factors for fatal or critical care unit-treated COVID-19 and COVID-19 related complications. Although relevant studies on DM have developed rapidly during the COVID-19 pandemic. However, the aforementioned research results have not been systematically quantified by means of bibliometric analysis.

Purpose

The purpose of this study is to provide a comprehensive analysis of the current status and trends of publications related to DM research during the COVID19 epidemic.

Methods

A bibliometric analysis was performed using the Web of Science database. In this study, we used citespace, R software and R-Bibliometrix to analyze keywords, most-cited authors, most-cited countries, most-cited global documents, and co-occurrence and co-citation networks.

Results

A total of 1688 publications was included in this study. Investigators from the United States contributed the most publications. The United States, China and Europe have the most collaboration with the other countries/regions. A total of 3355 institutions made contributions to this study. Of the top 10 institutions with the most publications, N8 Research Partnership showed the most centrality. Among the top 10 journals, Diabetes Research and Clinical Practice published the most articles. Among authors included, Khunti Kamlesh is rated first with 27 papers and has the highest centrality. The most frequently co-cited article is entitled "Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study". The most popular keywords included diabetes, mortality, diabetes, outcome, occurrences, risk, and type 1 diabetes.

Conclusion

This bibliometric study provides an overall picture of DM research and research trends during the COVID-19 pandemic and provides a basis for researchers to develop their next research strategies.

COVID-19 Vaccination and Its Relation to New-Onset Diabetes: A Narrative Review

The COVID-19 vaccination has been effective in preventing a lot of complications caused by SARS-CoV-2 and its variants. Meanwhile, diabetes mellitus, one of the root causes of many co-morbidities, exhibited itself during the COVID-19 pandemic and after COVID-19 vaccination. Diabetes mellitus introduced itself in a new perspective, leading to a variety of presentations and causing a significant number of emergency admissions. Many of the pre-diabetes patients with no prior history of diabetes developed fulminant type 1 diabetes mellitus (T1DM) after the COVID-19 vaccination. Some cases of conversion of type 2 diabetes mellitus (T2DM) into T1DM were reported. Some prediabetes/diabetes patients presented with the development of diabetic ketoacidosis after COVID-19 vaccination, whereas some previously healthy people with no relation to diabetes also developed acute exacerbations of new-onset T1DM or T2DM along with lethal ketoacidosis. The purpose of writing this review was to explore what kind of people are more prone to develop new-onset diabetes or diabetic complications, including diabetic ketoacidosis, the typical presentation of these patients, possible mechanisms that lead to these complications occurring after the COVID-19 vaccination, how they can be managed, and whether there is a good prognosis after management or not.

The value of prospective metabolomic susceptibility endotypes: broad applicability for infectious diseases

BACKGROUND

As new infectious diseases (ID) emerge and others continue to mutate, there remains an imminent threat, especially for vulnerable individuals. Yet no generalizable framework exists to identify the at-risk group prior to infection. Metabolomics has the advantage of capturing the existing physiologic state, unobserved via current clinical measures. Furthermore, metabolomics profiling during acute disease can be influenced by confounding factors such as indications, medical treatments, and lifestyles.

METHODS

We employed metabolomic profiling to cluster infection-free individuals and assessed their relationship with COVID severity and influenza incidence/recurrence.

FINDINGS

We identified a metabolomic susceptibility endotype that was strongly associated with both severe COVID (ORICUadmission = 6.7, p-value = 1.2 × 10-08, ORmortality = 4.7, p-value = 1.6 × 10-04) and influenza (ORincidence = 2.9; p-values = 2.2 × 10-4, βrecurrence = 1.03; p-value = 5.1 × 10-3). We observed similar severity associations when recapitulating this susceptibility endotype using metabolomics from individuals during and after acute COVID infection. We demonstrate the value of using metabolomic endotyping to identify a metabolically susceptible group for two-and potentially more-IDs that are driven by increases in specific amino acids, including microbial-related metabolites such as tryptophan, bile acids, histidine, polyamine, phenylalanine, and tyrosine metabolism, as well as carbohydrates involved in glycolysis.

INTERPRETATIONS

These metabolites may be identified prior to infection to enable protective measures for these individuals.

FUNDING

The Longitudinal EMR and Omics COVID-19 Cohort (LEOCC) and metabolomic profiling were supported by the National Heart, Lung, and Blood Institute and the Intramural Research Program of the National Center for Advancing Translational Sciences, National Institutes of Health.

Virulence traits and novel drug delivery strategies for mucormycosis post-COVID-19: a comprehensive review

The outbreak of a fatal black fungus infection after the resurgence of the cadaverous COVID-19 has exhorted scientists worldwide to develop a nutshell by repurposing or designing new formulations to address the crisis. Patients expressing COVID-19 are more susceptible to Mucormycosis (MCR) and thus fall easy prey to decease accounting for this global threat. Their mortality rates range around 32-70% depending on the organs affected and grow even higher despite the treatment. The many contemporary recommendations strongly advise using liposomal amphotericin B and surgery as first-line therapy whenever practicable. MCR is a dangerous infection that requires an antifungal drug administration on appropriate prescription, typically one of the following: Amphotericin B, Posaconazole, or Isavuconazole since the fungi that cause MCR are resistant to other medications like fluconazole, voriconazole, and echinocandins. Amphotericin B and Posaconazole are administered through veins (intravenously), and isavuconazole by mouth (orally). From last several years so many compounds are developed against invasive fungal disease but only few of them are able to induce effective treatment against the micorals. Adjuvant medicines, more particularly, are difficult to assess without prospective randomized controlled investigations, which are challenging to conduct given the lower incidence and higher mortality from Mucormycosis. The present analysis provides insight into pathogenesis, epidemiology, clinical manifestations, underlying fungal virulence, and growth mechanisms. In addition, current therapy for MCR in Post Covid-19 individuals includes conventional and novel nano-based advanced management systems for procuring against deadly fungal infection. The study urges involving nanomedicine to prevent fungal growth at the commencement of infection, delay the progression, and mitigate fatality risk.

Association between inpatient glycemic variability and COVID-19 mortality: a prospective study

BACKGROUND

This study aimed to determine the association between glycemic variability (GV) and mortality in hospitalized patients with coronavirus disease 2019 (COVID-19).

METHODS

We prospectively analyzed data from inpatients (> 18 years old) with RT-PCR confirmed COVID-19 admitted between March 2020 and July 2021. All patients were hospitalized for more than 48 h and had at least six point-of-care capillary glucose tests obtained three times daily in the pre-prandial period during hospitalization. GV was measured using the glucose standard deviation (SD) and coefficient of variation (CV). ROC curve was adjusted to determine the SD and CV cutoff values associated with mortality (44.7 mg/dL and 27.5%, respectively); values above these were considered indicative of high GV. Logistic regression models were fitted to explore the association between GV and mortality in patients with and without diabetes.

RESULTS

A total of 628 patients were stratified into SD < 44.7 mg/dL (n = 357) versus ≥ 44.7 mg/dL (n = 271) and CV < 27.5% (n = 318) versus ≥ 27.5% (n = 310) groups. After controlling for age, sex, presence of diabetes mellitus (DM) and cardiovascular disease, we found a significant association between high GV and mortality (odds ratio 2.99 [1.88-4.77] for SD and 2.43 [1.54-3.85] for CV; p values < 0.001). The mortality rate was higher with SD ≥ 44.7 mg/dL and CV ≥ 27.5% compared to that with SD < 44.7 mg/dL and CV < 27.5%, regardless of DM (p < 0.001 for all).

CONCLUSION

High glycemic variability was independently associated with mortality in patients with and without DM, who were hospitalized with COVID-19.

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.

Intensive care unit admission and associated factors in patients hospitalised for COVID-19: A national retrospective cohort study in Iran

OBJECTIVES

This study aimed to determine factors associated with intensive care unit (ICU) admission in patients hospitalised due to COVID-19.

DESIGN

Retrospective cohort.

SETTING

Confirmed hospitalised patients from all over Iran were considered for the study.

PARTICIPANTS

All patients with COVID-19 admitted to the hospital from March 2020 to May 2021 were included by census. ICU admission was defined by the following criteria: (1) admission to the ICU ward; (2) level of consciousness (loss of consciousness); and (3) use of invasive ventilation.

METHODS

This is a secondary data analysis from the Medical Care Monitoring Center. The association between different variables and ICU admission was assessed by forward Logistic regression and restricted cubic spline method.

RESULTS

The mean age of the 1 469 620 patients with COVID-19 was 54.49±20.58 years old, and 51.32% of the patients were male. The prevalence of ICU admission was 19.19%. The mean age of patients admitted to the ICU was higher than that of other hospitalised patients (62.49±19.73 vs 52.59±20.31 years). The prevalence of ICU admission was 17.17% in the first, 21.52% in the second, 19.72% in the third, 21.43 in the fourth and 17.4% in the fifth wave. In the multivariable model, age groups, sex, waves of the epidemic, comorbidities and saturation of peripheral oxygen (SpO2) <93% and acute respiratory distress syndrome (ARDS) were associated with an increased odds of ICU admission. The OR for ICU admission indicates a significant protective effect at a young age and then a significant risk factor for admission to the ICU ward at an old age.

CONCLUSIONS

Men, older adults, people who suffer from ARDS, patients with SpO2 levels of less than 93% and cases with comorbidities had the highest odds of ICU admission. Therefore, these groups should take all necessary precautions to avoid contracting COVID-19.

A critical review on brain and heart axis response in COVID-19 patients: Molecular mechanisms, mediators, biomarkers, and therapeutics

Since the outbreak of highly virulent coronaviruses, significant interest was assessed to the brain and heart axis (BHA) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-affected patients. The majority of clinical reports accounted for unusual symptoms associated with SARS-CoV-2 infections which are of the neurological type, such as headache, nausea, dysgeusia, anosmia, and cerebral infarction. The SARS-CoV-2 enters the cells through the angiotensin-converting enzyme (ACE-2) receptor. Patients with prior cardiovascular disease (CVD) have a higher risk of COVID-19 infection and it has related to various cardiovascular (CV) complications. Infected patients with pre-existing CVDs are also particularly exposed to critical health outcomes. Overall, COVID-19 affected patients admitted to intensive care units (ICU) and exposed to stressful environmental constraints, featured with a cluster of neurological and CV complications. In this review, we summarized the main contributions in the literature on how SARS-CoV-2 could interfere with the BHA and its role in affecting multiorgan disorders. Specifically, the central nervous system involvement, mainly in relation to CV alterations in COVID-19-affected patients, is considered. This review also emphasizes the biomarkers and therapy options for COVID-19 patients presenting with CV problems.

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.

Glycemic Dysregulation, Inflammation and Disease Outcomes in Patients Hospitalized with COVID-19: Beyond Diabetes and Obesity

INTRODUCTION

During the COVID-19 pandemic, diabetes mellitus (DM) and obesity were associated with high rates of morbidity and mortality. The aim of this study was to investigate the relationship between markers of inflammation, disease severity, insulin resistance, hyperglycemia, and outcomes in COVID-19 patients with and without diabetes and obesity.

MATERIALS AND METHODS

Epidemiological, clinical, and laboratory data were collected from the University Hospital of Ioannina COVID-19 Registry and included hospitalized patients from March 2020 to December 2022. The study cohort was divided into three subgroups based on the presence of DM, obesity, or the absence of both.

RESULTS

In diabetic patients, elevated CRP, IL-6, TRG/HDL-C ratio, and TyG index, severe pneumonia, and hyperglycemia were associated with extended hospitalization. Increased IL-6, NLR, and decreased PFR were associated with a higher risk of death. In the obese subgroup, lower levels of PFR were associated with longer hospitalization and a higher risk of death, while severe lung disease and hyperglycemia were associated with extended hospitalization. In patients without DM or obesity severe pneumonia, NLR, CRP, IL-6, insulin resistance indices, and hyperglycemia during hospitalization were associated with longer hospitalization.

CONCLUSION

Inflammatory markers and disease severity indices were strongly associated with disease outcomes and hyperglycemia across all subgroups.

Is elevated blood glucose at admission associated with poor outcomes in hospitalized COVID-19 patients?

Objective

Hyperglycemia has been suggested as a risk factor for poor outcomes in coronavirus disease 2019 (COVID-19). The aim of our work was to evaluate the association between blood glucose levels at admission (BGA) and disease outcomes in hospitalized COVID-19 patients.

Subjects and methods

Retrospective study including all adult COVID-19 patients admitted to a Portuguese hospital from March to August 2020 with BGA measurement. Subjects were categorized into two groups: BGA < 140 mg/dL and ≥ 140 mg/dL. Statistical analysis was performed using SPSSv26® (significance defined as p < 0.05).

Results

We included 202 patients: median age 74 (60-86) years; 43.1% female; 31.2% with diabetes. The median BGA was 130.5 (108-158) mg/dL. When compared to normoglycemic, patients with BGA ≥ 140 mg/dL were older (p = 0.013), more vaccinated for influenza (p = 0.025) and had more comorbidities (hypertension, heart failure and peripheral arterial disease, p < 0.05). The last group presented higher leucocyte and neutrophile count, higher procalcitonin and prothrombin time, and lower lymphocyte count. Concerning prognosis, BGA ≥ 140 mg/dL was associated with higher rates of mechanical ventilation requirement and intensive care unit admission (p < 0.001), shock (p = 0.011), in-hospital mortality (p = 0.022) and 30-day mortality (p = 0.037). Considering only non-diabetic patients (n = 139), those with hyperglycemia presented higher rates of severity indicators (polypnea, SatO2 ≤ 93% and PaO2/FiO2 ≤ 300) and an association with poor outcomes was also found, namely mechanical ventilation requirement and in-hospital/30-day mortality (p < 0.05).

Conclusion

Hyperglycemia at admission was associated with poor outcomes in COVID-19 patients, even in those without known pre-existing diabetes. Glycemic testing should be recommended for all COVID-19 patients.

Use of data mining approaches to explore the association between type 2 diabetes mellitus with SARS-CoV-2

BACKGROUND AND OBJECTIVE

Corona virus causes respiratory tract infections in mammals. The latest type of Severe Acute Respiratory Syndrome Corona-viruses 2 (SARS-CoV-2), Corona virus spread in humans in December 2019 in Wuhan, China. The purpose of this study was to investigate the relationship between type 2 diabetes mellitus (T2DM), and their biochemical and hematological factors with the level of infection with COVID-19 to improve the treatment and management of the disease.

MATERIAL AND METHOD

This study was conducted on a population of 13,170 including 5780 subjects with SARS-COV-2 and 7390 subjects without SARS-COV-2, in the age range of 35-65 years. Also, the associations between biochemical factors, hematological factors, physical activity level (PAL), age, sex, and smoking status were investigated with the COVID-19 infection.

RESULT

Data mining techniques such as logistic regression (LR) and decision tree (DT) algorithms were used to analyze the data. The results using the LR model showed that in biochemical factors (Model I) creatine phosphokinase (CPK) (OR: 1.006 CI 95% (1.006,1.007)), blood urea nitrogen (BUN) (OR: 1.039 CI 95% (1.033, 1.047)) and in hematological factors (Model II) mean platelet volume (MVP) (OR: 1.546 CI 95% (1.470, 1.628)) were significant factors associated with COVID-19 infection. Using the DT model, CPK, BUN, and MPV were the most important variables. Also, after adjustment for confounding factors, subjects with T2DM had higher risk for COVID-19 infection.

CONCLUSION

There was a significant association between CPK, BUN, MPV and T2DM with COVID-19 infection and T2DM appears to be important in the development of COVID-19 infection.

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.

Assessment of COVID-19 RT-PCR Positive Symptomatic Patients With Clinical, Hematological, and Radiological Parameters Among Three Groups: A Comparative Study

BACKGROUND

Nearly 70.1 million individuals have been infected by the pandemic viral disease known as coronavirus disease 2019 (COVID-19), which was first discovered in China and is caused by a novel coronavirus known as severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2). This disease is responsible for the deaths of 6 million people. India ranks third in the total number of cases. The purpose of this study was to classify COVID-19 patients according to several criteria and to determine which clinical, hematological, and radiological indicators were most important in their care.

MATERIALS AND METHODS

An analytical cross-sectional study was conducted on a total of 70 symptomatic patients who tested positive for COVID-19 reverse transcription polymerase chain reaction (RT-PCR) and were hospitalized at the Saveetha Medical College and Hospital in Chennai, Tamil Nadu, India, for the duration of the study. Comorbidities and oxygen reliance were taken into consideration while classifying patients into one of three categories. Initial symptoms, as well as hematological (interleukin-6 (IL-6), erythrocyte sedimentation rate (ESR), c-reactive protein (CRP), D-dimer, serum ferritin, and total cell counts) and radiographic (X-ray and computed tomography (CT) of the thorax) characteristics, were taken and analyzed among the different groups.

RESULTS

According to our research, the symptom of fever was the most common, accounting for 84.3% of all cases. This was followed by breathlessness (55.7%), myalgia (31.4%), dry cough (27.1%), sore throat (24.3%), cough with expectoration (20%), loose stools (12.9%), loss of taste (12.9%), and smell (11.4%). Although there was a large amount of variation in D-dimer, with Category C having the highest values, there was only a minor amount of variation in ESR and CRP. The X-ray and CT scans of the chest showed substantial differences between the groups, with CT findings such as COVID-19 Reporting and Data System (CO-RADS) and CT severity score, consolidation, crazy paving pattern, and vascular dilatation showing a wide range of differences between the groups.

CONCLUSIONS

To facilitate easier treatment and place more attention on radiological characteristics using D-dimer, treating physicians are required to categorize COVID-19 patients into several groups. Patients who need oxygen support were included in this category.

Aggravated pneumonia and diabetes in SARS-CoV-2 infected diabetic mice

Multiple clinical and epidemiological studies have shown an interconnection between coronavirus disease 2019 (COVID-19) and diabetes, but experimental evidence is still lacking. Understanding the interplay between them is important because of the global health burden of COVID-19 and diabetes. We found that C57BL/6J mice were susceptible to the alpha strain of SARS-CoV-2. Moreover, diabetic C57BL/6J mice with leptin receptor gene deficiency (db/db mice) showed a higher viral load in the throat and lung and slower virus clearance in the throat after infection than C57BL/6J mice. Histological and multifactor analysis revealed more advanced pulmonary injury and serum inflammation in SARS-CoV-2 infected diabetic mice. Moreover, SARS-CoV-2 infected diabetic mice exhibited more severe insulin resistance and islet cell loss than uninfected diabetic mice. By RNA sequencing analysis, we found that diabetes may reduce the collagen level, suppress the immune response and aggravate inflammation in the lung after infection, which may account for the greater susceptibility of diabetic mice and their more severe lung damage after infection. In summary, we successfully established a SARS-CoV-2 infected diabetic mice model and demonstrated that diabetes and COVID-19 were risk factors for one another.

Alterations of adipokines, pancreatic hormones and incretins in acute and convalescent COVID-19 children

BACKGROUND

The Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), accountable for Coronavirus disease 2019 (COVID-19), may cause hyperglycemia and additional systemic complexity in metabolic parameters. It is unsure even if the virus itself causes type 1 or type 2 diabetes mellitus (T1DM or T2DM). Furthermore, it is still unclear whether even recuperating COVID-19 individuals have an increased chance to develop new-onset diabetes.

METHODS

We wanted to determine the impact of COVID-19 on the levels of adipokines, pancreatic hormones, incretins and cytokines in acute COVID-19, convalescent COVID-19 and control children through an observational study. We performed a multiplex immune assay analysis and compared the plasma levels of adipocytokines, pancreatic hormones, incretins and cytokines of children presenting with acute COVID-19 infection and convalescent COVID-19.

RESULTS

Acute COVID-19 children had significantly elevated levels of adipsin, leptin, insulin, C-peptide, glucagon and ghrelin in comparison to convalescent COVID-19 and controls. Similarly, convalescent COVID-19 children had elevated levels of adipsin, leptin, insulin, C-peptide, glucagon, ghrelin and Glucagon-like peptide-1 (GLP-1) in comparison to control children. On the other hand, acute COVID-19 children had significantly decreased levels of adiponectin and Gastric Inhibitory Peptide (GIP) in comparison to convalescent COVID-19 and controls. Similarly, convalescent COVID-19 children had decreased levels of adiponectin and GIP in comparison to control children. Acute COVID-19 children had significantly elevated levels of cytokines, (Interferon (IFN)) IFNγ, Interleukins (IL)-2, TNFα, IL-1α, IL-1β, IFNα, IFNβ, IL-6, IL-12, IL-17A and Granulocyte-Colony Stimulating Factors (G-CSF) in comparison to convalescent COVID-19 and controls. Convalescent COVID-19 children had elevated levels of IFNγ, IL-2, TNFα, IL-1α, IL-1β, IFNα, IFNβ, IL-6, IL-12, IL-17A and G-CSF in comparison to control children. Additionally, Principal component Analysis (PCA) analysis distinguishes acute COVID-19 from convalescent COVID-19 and controls. The adipokines exhibited a significant correlation with the levels of pro-inflammatory cytokines.

CONCLUSION

Children with acute COVID-19 show significant glycometabolic impairment and exaggerated cytokine responses, which is different from convalescent COVID-19 infection and controls.

Hospitalized COVID-19 patients with diabetes have an increased risk for pneumonia, intensive care unit requirement, intubation, and death: A cross-sectional cohort study in Mexico in 2020

Background

Diabetes mellitus is a chronic health condition that has been linked with an increased risk of severe illness and mortality from COVID-19. In Mexico, the impact of diabetes on COVID-19 outcomes in hospitalized patients has not been fully quantified. Understanding the increased risk posed by diabetes in this patient population can help healthcare providers better allocate resources and improve patient outcomes.

Objective

The objective of this study was to quantify the extent outcomes (pneumonia, intensive care unit [ICU] stay, intubation, and death) are worsened in diabetic patients with COVID-19.

Methods

Between April 14, 2020 and December 20, 2020 (last accessed), data from the open-source COVID-19 database maintained by the Mexican Federal Government were examined. Utilizing hospitalized COVID-19 patients with complete outcome data, a retrospective cohort study (N = 402,388) was carried out. In relation to COVID-19, both univariate and multivariate logistic regression were used to investigate the effect of diabetes on specific outcomes.

Results

The analysis included 402,388 adults (age >18) with confirmed hospitalized COVID-19 cases with mean age 46.16 (standard deviation = 15.55), 214,161 (53%) male. The outcomes delineated included pneumonia (N = 88,064; 22%), ICU requirement (N = 23,670; 6%), intubation (N = 23,670; 6%), and death (N = 55,356; 14%). After controlling for confounding variables diabetes continued to be an independent risk factor for both pneumonia (odds ratio [OR]: 1.8, confidence interval [CI]: 1.76-1.84, p < 0.01), ICU requirement (OR: 1.09, CI: 1.04-1.14, p < 0.01), intubation (OR: 1.07, CI: 1.04-1.11, p < 0.01), and death (OR: 1.88, CI: 1.84-1.93, p < 0.01) in COVID-19 patients.

Conclusions

According to the study, all outcomes (pneumonia, ICU requirement, intubation, and death) were greater among hospitalized individuals with diabetes and COVID-19. Additional study is required to acquire a better understanding of how diabetes affects COVID-19 outcomes and to develop practical mitigation techniques for the risk of severe sickness and complications in this particular patient population.

Global Diabetes Prevalence in COVID-19 Patients and Contribution to COVID-19- Related Severity and Mortality: A Systematic Review and Meta-analysis

BACKGROUND

COVID-19 and diabetes both contribute to large global disease burdens.

PURPOSE

To quantify the prevalence of diabetes in various COVID-19 disease stages and calculate the population attributable fraction (PAF) of diabetes to COVID-19-related severity and mortality.

DATA SOURCES

Systematic review identified 729 studies with 29,874,938 COVID-19 patients.

STUDY SELECTION

Studies detailed the prevalence of diabetes in subjects with known COVID-19 diagnosis and severity.

DATA EXTRACTION

Study information, COVID-19 disease stages, and diabetes prevalence were extracted.

DATA SYNTHESIS

The pooled prevalence of diabetes in stratified COVID-19 groups was 14.7% (95% CI 12.5-16.9) among confirmed cases, 10.4% (7.6-13.6) among nonhospitalized cases, 21.4% (20.4-22.5) among hospitalized cases, 11.9% (10.2-13.7) among nonsevere cases, 28.9% (27.0-30.8) among severe cases, and 34.6% (32.8-36.5) among deceased individuals, respectively. Multivariate metaregression analysis explained 53-83% heterogeneity of the pooled prevalence. Based on a modified version of the comparative risk assessment model, we estimated that the overall PAF of diabetes was 9.5% (7.3-11.7) for the presence of severe disease in COVID-19-infected individuals and 16.8% (14.8-18.8) for COVID-19-related deaths. Subgroup analyses demonstrated that countries with high income levels, high health care access and quality index, and low diabetes disease burden had lower PAF of diabetes contributing to COVID-19 severity and death.

LIMITATIONS

Most studies had a high risk of bias.

CONCLUSIONS

The prevalence of diabetes increases with COVID-19 severity, and diabetes accounts for 9.5% of severe COVID-19 cases and 16.8% of deaths, with disparities according to country income, health care access and quality index, and diabetes disease burden.

Efficient prediction of early-stage diabetes using XGBoost classifier with random forest feature selection technique

Diabetes is one of the most common and serious diseases affecting human health. Early diagnosis and treatment are vital to prevent or delay complications related to diabetes. An automated diabetes detection system assists physicians in the early diagnosis of the disease and reduces complications by providing fast and precise results. This study aims to introduce a technique based on a combination of multiple linear regression (MLR), random forest (RF), and XGBoost (XG) to diagnose diabetes from questionnaire data. MLR-RF algorithm is used for feature selection, and XG is used for classification in the proposed system. The dataset is the diabetic hospital data in Sylhet, Bangladesh. It contains 520 instances, including 320 diabetics and 200 control instances. The performance of the classifiers is measured concerning accuracy (ACC), precision (PPV), recall (SEN, sensitivity), F1 score (F1), and the area under the receiver-operating-characteristic curve (AUC). The results show that the proposed system achieves an accuracy of 99.2%, an AUC of 99.3%, and a prediction time of 0.04825 seconds. The feature selection method improves the prediction time, although it does not affect the accuracy of the four compared classifiers. The results of this study are quite reasonable and successful when compared with other studies. The proposed method can be used as an auxiliary tool in diagnosing diabetes.

Association of COVID-19 with Comorbidities: An Update

Coronavirus disease (COVID-19) is caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) which was identified in Wuhan, China in December 2019 and jeopardized human lives. It spreads at an unprecedented rate worldwide, with serious and still-unfolding health conditions and economic ramifications. Based on the clinical investigations, the severity of COVID-19 appears to be highly variable, ranging from mild to severe infections including the death of an infected individual. To add to this, patients with comorbid conditions such as age or concomitant illnesses are significant predictors of the disease's severity and progression. SARS-CoV-2 enters inside the host cells through ACE2 (angiotensin converting enzyme2) receptor expression; therefore, comorbidities associated with higher ACE2 expression may enhance the virus entry and the severity of COVID-19 infection. It has already been recognized that age-related comorbidities such as Parkinson's disease, cancer, diabetes, and cardiovascular diseases may lead to life-threatening illnesses in COVID-19-infected patients. COVID-19 infection results in the excessive release of cytokines, called "cytokine storm", which causes the worsening of comorbid disease conditions. Different mechanisms of COVID-19 infections leading to intensive care unit (ICU) admissions or deaths have been hypothesized. This review provides insights into the relationship between various comorbidities and COVID-19 infection. We further discuss the potential pathophysiological correlation between COVID-19 disease and comorbidities with the medical interventions for comorbid patients. Toward the end, different therapeutic options have been discussed for COVID-19-infected comorbid patients.

Cognitive dysfunction, diabetes mellitus 2 and arterial hypertension: Sequelae up to one year of COVID-19

BACKGROUND

Covid symptoms reflect its multisystem nature, in addition to its positive relationship between the severity of the condition and the severity of the long COVID.

OBJECTIVE

To identify the factors associated with the prevalence of SEQUELAE DUE TO COVID-19 one year after their hospital discharge due to severe pneumonia.

METHOD

Longitudinal, analytical, prospective and comparative study. 71 covid-19 pneumonia survivors were followed. Two telephone interviews were conducted to each patient; the first at 5 months of discharge and the second at 12 months from the mentioned date. We included questions of 40 symptoms, in addition to the questioning of diabetes mellitus and/or systemic hypertension with a mentioned onset during the hospitalization or after hospital discharge due to COVID-19.

RESULTS

Of the 37 patients without complications and without comorbidities prior to hospitalization, 11 (29.7%) developed arterial hypertension during or after discharge and 17 (45.9%) developed diabetes mellitus before five months. Short-term memory loss was an upward sequel in the two measurements, 24.3% and 41.9% respectively.

CONCLUSIONS

Type 2 diabetes mellitus and high blood pressure detected at five months was temporary and reversed in many cases at twelve months. It will be important to deepen the study of brain damage and cognitive dysfunction, characterized by memory loss.

A rare case of newly diagnosed diabetes mellitus following COVID-19 infection

Several reports showed the likelihood of a relationship between COVID-19 infection and the onset and prognosis of diabetes mellitus (DM) of all types. A 73-year-old female patient who presented to the clinic with respiratory symptoms and was tested positive for COVID-19 and treated for the next three days. Despite having neither a known history of hyperglycemia nor a family history of diabetes, she was unconscious and suffering from polyuria and polydipsia when she was brought to the emergency department. Once her condition was successfully stabilized, she was sent home with COVID-19 medications and oral anti-diabetic therapy. After subsequent viral recovery and continued anti-diabetic medication, the patient was monitored for the following seven months. DM might be linked to the SARS-CoV-2 infection. Further research is necessary to prove a relationship between COVID-19 and newly-onset diabetes.

Relationship between severe acute respiratory syndrome coronavirus 2 and diabetes mellitus (review)

Infections caused by SARE-CoV-2 are complicated with the concurrent pathologies, to name hypertension, diabetes mellitus and cardiovascular diseases. High level of glucose in blood weakens the immunity and increase the SARS-CoV-2 replication. Diabetes mellitus aggravates the COVID-19 outcome. The intrusion of SARS-CoV-2 into a host-cell occurs by means of its association with the angiotensin-converting enzyme-2 (ACE 2). Stimulating immune responses the COVID-19 infection causes the cytokine storm, and may result in the lethal outcome in the diabetics.

Recent laboratory studies demonstrated that the type1 and type2 diabetes mellitus is the main consequence in 14% of the patients after corona infection. Thus, in 2% of 14% diabetes started progressing due to the corona virus. In the other, diabetes debut occurred as the direct and negative consequence of the disease. Hyperglycemia results in the formation of protein molecules known as the advanced glycation end products (AGEs). The AGEs and their receptors (RAGE) are of high significance in the host-cell’s virus invasion. Consequently, more strict glucose control is necessary for optimal outcome and reduction in mortality. The better control for the COVID-19 course can be provided by the targeted effect on the RAGE axis. The review helps elucidate the molecular mechanism underlying the exacerbation of pathophysiology in the diabetic COVID-19 patients.

Association of Lung Fibrotic Changes and Cardiological Dysfunction with Comorbidities in Long COVID-19 Cohort

Background. Long COVID-19 symptoms appeared in many COVID-19 survivors. However, the prevalence and symptoms associated with long COVID-19 and its comorbidities have not been established. Methods. In total, 312 patients with long COVID-19 from 21 primary care centers were included in the study. At the six-month follow-up, their lung function was assessed by computerized tomography (CT) and spirometry, whereas cardiac function was assessed by elec-trocardiogram (ECG), Holter ECG, echocardiography, 24 h blood pressure monitoring, and a six-minute walk test (6MWT). Results. Of the 312 persons investigated, significantly higher sys-tolic and diastolic blood pressure, left ventricular hypertrophy, and elevated NT-proBNP were revealed in participants with hypertension or type 2 diabetes. Left ventricular diastolic dysfunc-tion was more frequently present in patients with hypertension. The most common registered CT abnormalities were fibrotic changes (83, 36.6%) and mediastinal lymphadenopathy (23, 10.1%). Among the tested biochemical parameters, three associations were found in long COVID-19 patients with hypertension but not diabetes: increased hemoglobin, fibrinogen, and ferritin. Nine patients had persisting IgM antibodies to SARS-CoV-2. Conclusions. We demon-strated a strong association between signs of cardiac dysfunction and lung fibrotic changes with comorbidities in a cohort of long COVID-19 subjects.

COVID-19: Diabetes Perspective-Pathophysiology and Management

Recent evidence relating to the impact of COVID-19 on people with diabetes is limited but continues to emerge. COVID-19 pneumonia is a newly identified illness spreading rapidly throughout the world and causes many disabilities and fatal deaths. Over the ensuing 2 years, the indirect effects of the pandemic on healthcare delivery have become prominent, along with the lingering effects of the virus on those directly infected. Diabetes is a commonly identified risk factor that contributes not only to the severity and mortality of COVID-19 patients, but also to the associated complications, including acute respiratory distress syndrome (ARDS) and multi-organ failure. Diabetic patients are highly affected due to increased viral entry into the cells and decreased immunity. Several hypotheses to explain the increased incidence and severity of COVID-19 infection in people with diabetes have been proposed and explained in detail recently. On the other hand, 20-50% of COVID-19 patients reported new-onset hyperglycemia without diabetes and new-onset diabetes, suggesting the two-way interactions between COVID-19 and diabetes. A systematic review is required to confirm diabetes as a complication in those patients diagnosed with COVID-19. Diabetes and diabetes-related complications in COVID-19 patients are primarily due to the acute illness caused during the SARS-CoV-2 infection followed by the release of glucocorticoids, catecholamines, and pro-inflammatory cytokines, which have been shown to drive hyperglycemia positively. This review provides brief insights into the potential mechanisms linking COVID-19 and diabetes, and presents clinical management recommendations for better handling of the disease.

Risk Factors of Severe COVID-19: A Review of Host, Viral and Environmental Factors

The clinical course and outcome of COVID-19 are highly variable, ranging from asymptomatic infections to severe disease and death. Understanding the risk factors of severe COVID-19 is relevant both in the clinical setting and at the epidemiological level. Here, we provide an overview of host, viral and environmental factors that have been shown or (in some cases) hypothesized to be associated with severe clinical outcomes. The factors considered in detail include the age and frailty, genetic polymorphisms, biological sex (and pregnancy), co- and superinfections, non-communicable comorbidities, immunological history, microbiota, and lifestyle of the patient; viral genetic variation and infecting dose; socioeconomic factors; and air pollution. For each category, we compile (sometimes conflicting) evidence for the association of the factor with COVID-19 outcomes (including the strength of the effect) and outline possible action mechanisms. We also discuss the complex interactions between the various risk factors.

Factors Affecting Outcome in Diabetic Patients with COVID-19: A Cross-sectional Study

BACKGROUND: Type-2 diabetes mellitus (T2DM) is a chronic disease and often found as a comorbid in COVID-19. Poor glycemic control might play a role in worsening of clinical outcome in COVID-19 patients who lead to increase morbidity and mortality. AIM: We conducted a study to evaluate relationship between T2DM with or without macrovascular and microvascular complications and cigarette smoking habit with COVID-19 outcomes. METHODS: A cross-sectional study of hospitalized COVID-19 patients was conducted in Dr. Wahidin Sudirohusodo Hospital, Makassar from May 2020 to August 2020. COVID-19 status was obtained using real-time polymerase chain reaction for SARS-CoV-2, T2DM status was obtained using blood glucose or HbA1c, and other characteristic data were obtained. Mortality was the clinical outcome in our study. RESULTS: One hundred and six subjects data were enrolled. Most subjects were male (n = 55; 51.9%), and 55–65 year-old (n = 40; 37.7%). Eighty subjects were survived (75.5%) and 26 subjects did not survive (24.5%). Onset of T2DM ≥ 5 years had a higher mortality rate compared to onset < 5 years (34.9% vs. 17.5%; p = 0.041). Other factors such as gender, age, nutritional status, hypertension, heart disease, smoking habit, and HbA1c did not show significant difference in terms of mortality. CONCLUSION: COVID-19 patients with onset of T2DM for more than 5 years had a worse outcome compared to the onset of T2DM <5 years.

COVID-19 and Diabetes Mellitus: Mutual Interplay of Two Diseases

Currently, when the world is fighting against the rapidly spreading pandemic of COVID-19, the silent epidemic of diabetes should not be set aside. In comparison, while COVID- 19 led to about 6 million deaths in 2021, diabetes caused 6.7 million deaths in the same year. Diabetes mellitus is a serious risk factor for worse outcomes in COVID-19 patients. Moreover, it seems that there is a bidirectional relationship between pre-existing diabetes pandemic and the rapidly spreading COVID-19 pandemic. In this article, we summarize mechanisms by which SARS-CoV-2 infects the host cell and discuss the bidirectional relationship between diabetes and COVID-19. We also focus on clinical variables in which diabetic patients differ from non-diabetic patients and which could have promising predictive value for the course and outcome of diabetic COVID-19 patients' therapy management.

Molecular and Therapeutic Insights of Alpha-Lipoic Acid as a Potential Molecule for Disease Prevention

Alpha-lipoic acid is an organic, sulfate-based compound produced by plants, humans, and animals. As a potent antioxidant and a natural dithiol compound, it performs a crucial role in mitochondrial bioenergetic reactions. A healthy human body, on the other hand, can synthesize enough α-lipoic acid to scavenge reactive oxygen species and increase endogenous antioxidants; however, the amount of α-lipoic acid inside the body decreases significantly with age, resulting in endothelial dysfunction. Molecular orbital energy and spin density analysis indicate that the sulfhydryl (-SH) group of molecules has the greatest electron donating activity, which would be responsible for the antioxidant potential and free radical scavenging activity. α-Lipoic acid acts as a chelating agent for metal ions, a quenching agent for reactive oxygen species, and a reducing agent for the oxidized form of glutathione and vitamins C and E. α-Lipoic acid enantiomers and its reduced form have antioxidant, cognitive, cardiovascular, detoxifying, anti-aging, dietary supplement, anti-cancer, neuroprotective, antimicrobial, and anti-inflammatory properties. α-Lipoic acid has cytotoxic and antiproliferative effects on several cancers, including polycystic ovarian syndrome. It also has usefulness in the context of female and male infertility. Although α-lipoic acid has numerous clinical applications, the majority of them stem from its antioxidant properties; however, its bioavailability in its pure form is low (approximately 30%). However, nanoformulations have shown promise in this regard. The proton affinity and electron donating activity, as a redox-active agent, would be responsible for the antioxidant potential and free radical scavenging activity of the molecule. This review discusses the most recent clinical data on α-lipoic acid in the prevention, management, and treatment of a variety of diseases, including coronavirus disease 2019. Based on current evidence, the preclinical and clinical potential of this molecule is discussed.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s43450-023-00370-1.

Chitosan-Encapsulated Nano-selenium Targeting TCF7L2, PPARγ, and CAPN10 Genes in Diabetic Rats

This study investigates the antidiabetic and antioxidant potential of chitosan-encapsulated selenium nanoparticles in streptozotocin-induced diabetic model. Glibenclamide was used as a reference antidiabetic drug. Forty-eight adult male Wistar rats were used along the study and divided equally into 6 groups of (I) normal control, (II) chitosan-encapsulated selenium nanoparticles (CTS-SeNPs), (III) glibenclamide, (IV) streptozotocin (STZ), (V) STZ + CTS-SeNPs, and (VI) STZ + Glib. The animals were sacrificed on the 35th day of the experiment. Serum glucose, insulin, IGF-1, ALT, AST, CK-MB, oxidative stress, lipid profile, and inflammatory parameters were subsequently assessed. Also, the expression level of TCF7L2, CAPN10, and PPAR-γ genes were evaluated using qPCR. In addition, histopathological studies on pancreatic tissue were carried out. The results revealed that STZ induced both diabetes and oxidative stress in normal rats, manifested by the significant changes in the studied parameters and in the physical structure of pancreatic tissue. Oral administration of CTS-SeNPs or Glib results in a significant amelioration of the levels of serum fasting blood glucose, insulin, IGF-1, AST, ATL, and CK-MB as compared with STZ-induced diabetic rats. CTS-SeNPs and Glib diminished the level of lipid peroxidation, increased total antioxidant capacity level, as well as possessed strong inhibition against serum α-amylase and α-glucosidase activities. Diabetic animals received CTS-SeNPs, or Glib demonstrated a significant (p < 0.05) decrease in the expression level of TCF7L2 and CAPN10 genes with a significant increase in the expression level of PPAR-γ gene, compared to STZ group. The above findings clarify the promising antidiabetic and antioxidant effect of CTS-SeNPs, recommending its inclusion in the currently used protocols for the treatment of diabetes and in the prevention of its related complications.

Assessment of determining factors for severity of NeoCOVIDiabetes in India: A pan India multicentric retrospective study

BACKGROUND AND AIMS

There is a bidirectional relationship between COVID-19 and diabetes. The primary objective of this study was to estimate the prevalence of patients newly detected to have diabetes (NDD) who recovered from COVID-19 in India whilst comparing NDD with patients without diabetes (ND) and those who have known to have diabetes (KD) in terms of glycemic status pre- and post-COVID with disease severity.

MATERIALS & METHODOLOGY

There were 2212 participants enrolled from 15 sites, with 1630 active participants after the respective execution of selection criteria. Data collection was done using a specialized Case Record Form (CRF). Planned statistical analysis and descriptive statistics were concluded for significance between patient groups on various parameters.

RESULT

The differences in age between the study groups were statistically significant. The average blood glucose at COVID-19 onset was significantly higher in KD than in NDD. Significantly more proportion of NDD (83%) had been hospitalized for COVID management when compared to KD (45%) and ND (55%). The NDD group received higher doses of steroids than the other two groups. On average, patients in the NDD group who received at least one vaccination (one dose or two doses) had a higher High-Resolution Computed Tomography (HRCT) score. Patients who had not been vaccinated in ND and KD groups experienced a higher HRCT score.

CONCLUSION

Prospective metabolism studies in post-acute COVID-19 will be required to understand the etiology, prognosis, and treatment opportunities.

Exploring the Implications of New-Onset Diabetes in COVID-19: A Narrative Review

Post-viral new-onset diabetes has been an important feature of the COVID-19 pandemic. It is not always clear if new-onset diabetes is the unmasking of a previously undiagnosed condition, the acceleration of prediabetes, or new-onset diabetes that would not have otherwise occurred. Even asymptomatic cases of COVID-19 have been associated with new-onset diabetes. Diabetes that emerges during acute COVID-19 infection tends to have an atypical presentation, characterized by hyperglycemia and potentially life-threatening diabetic ketoacidosis. It is not always clear if new-onset diabetes is type 1 or type 2 diabetes mellitus. Many cases of COVID-associated diabetes appear to be type 1 diabetes, which is actually an autoimmune disorder. The clinical course varies temporally and with respect to outcomes; in some cases, diabetes resolves completely or improves incrementally after recovery from COVID-19. Disruptions in macrophagy caused by COVID-19 infection along with an exaggerated inflammatory response that can occur in COVID-19 also play a role. Those who survive COVID-19 remain at a 40% elevated risk for diabetes in the first year, even if their case of COVID-19 was not particularly severe. A subsequent post-pandemic wave of new diabetes patients may be expected.

AMPK directly phosphorylates TBK1 to integrate glucose sensing into innate immunity

Nutrient sensing and damage sensing are two fundamental processes in living organisms. While hyperglycemia is frequently linked to diabetes-related vulnerability to microbial infection, how body glucose levels affect innate immune responses to microbial invasion is not fully understood. Here, we surprisingly found that viral infection led to a rapid and dramatic decrease in blood glucose levels in rodents, leading to robust AMPK activation. AMPK, once activated, directly phosphorylates TBK1 at S511, which triggers IRF3 recruitment and the assembly of MAVS or STING signalosomes. Consistently, ablation or inhibition of AMPK, knockin of TBK1-S511A, or increased glucose levels compromised nucleic acid sensing, while boosting AMPK-TBK1 cascade by AICAR or TBK1-S511E knockin improves antiviral immunity substantially in various animal models. Thus, we identify TBK1 as an AMPK substrate, reveal the molecular mechanism coupling a dual sensing of glucose and nuclei acids, and report its physiological necessity in antiviral defense.

SARS-CoV-2 in the pancreas and the impaired islet function in COVID-19 patients

Diabetes mellitus (DM) is one of the most common underlying diseases that may aggravates COVID-19. In the present study, we explored islet function, the presence of SARS-CoV-2 and pathological changes in the pancreas of patients with COVID-19. Oral glucose tolerance tests (OGTTs) and the C-peptide release test demonstrated a decrease in glucose-stimulated C-peptide secretory capacity and an increase in HbA1c levels in patients with COVID-19. The prediabetic conditions appeared to be more significant in the severe group than in the moderate group. SARS-CoV-2 receptors (ACE2, CD147, TMPRSS2 and neuropilin-1) were expressed in pancreatic tissue. In addition to SARS-CoV-2 virus spike protein and virus RNA, coronavirus-like particles were present in the autophagolysosomes of pancreatic acinar cells of a patient with COVID-19. Furthermore, the expression and distribution of various proteins in pancreatic islets of patients with COVID-19 were altered. These data suggest that SARS-CoV-2 in the pancreas may directly or indirectly impair islet function.

Metabolic syndrome and aberrant immune responses to viral infection and vaccination: Insights from small animal models

This review outlines the propensity for metabolic syndrome (MetS) to induce elevated disease severity, higher mortality rates post-infection, and poor vaccination outcomes for viral pathogens. MetS is a cluster of conditions including high blood glucose, an increase in circulating low-density lipoproteins and triglycerides, abdominal obesity, and elevated blood pressure which often overlap in their occurrence. MetS diagnoses are on the rise, as reported cases have increased by greater than 35% since 1988, resulting in one-third of United States adults currently diagnosed as MetS patients. In the aftermath of the 2009 H1N1 pandemic, a link between MetS and disease severity was established. Since then, numerous studies have been conducted to illuminate the impact of MetS on enhancing virally induced morbidity and dysregulation of the host immune response. These correlative studies have emphasized the need for elucidating the mechanisms by which these alterations occur, and animal studies conducted as early as the 1940s have linked the conditions associated with MetS with enhanced viral disease severity and poor vaccine outcomes. In this review, we provide an overview of the importance of considering overall metabolic health in terms of cholesterolemia, glycemia, triglyceridemia, insulin and other metabolic molecules, along with blood pressure levels and obesity when studying the impact of metabolism-related malignancies on immune function. We highlight the novel insights that small animal models have provided for MetS-associated immune dysfunction following viral infection. Such animal models of aberrant metabolism have paved the way for our current understanding of MetS and its impact on viral disease severity, dysregulated immune responses to viral pathogens, poor vaccination outcomes, and contributions to the emergence of viral variants.